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<journal-id journal-id-type="publisher-id">Front. Pharmacol.</journal-id>
<journal-title>Frontiers in Pharmacology</journal-title>
<abbrev-journal-title abbrev-type="pubmed">Front. Pharmacol.</abbrev-journal-title>
<issn pub-type="epub">1663-9812</issn>
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<publisher-name>Frontiers Media S.A.</publisher-name>
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<article-id pub-id-type="publisher-id">1506234</article-id>
<article-id pub-id-type="doi">10.3389/fphar.2025.1506234</article-id>
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<subject>Pharmacology</subject>
<subj-group>
<subject>Systematic Review</subject>
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<title-group>
<article-title>Potential preventive effects of selected traditional Chinese medicine as adjuvant therapy on hypertensive heart disease progression by replenishing qi and activating blood circulation: a systematic review and meta-analysis of clinical trials</article-title>
<alt-title alt-title-type="left-running-head">Hui et al.</alt-title>
<alt-title alt-title-type="right-running-head">
<ext-link ext-link-type="uri" xlink:href="https://doi.org/10.3389/fphar.2025.1506234">10.3389/fphar.2025.1506234</ext-link>
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<contrib-group>
<contrib contrib-type="author">
<name>
<surname>Hui</surname>
<given-names>Jiaqi</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
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<xref ref-type="aff" rid="aff2">
<sup>2</sup>
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<contrib contrib-type="author">
<name>
<surname>Wang</surname>
<given-names>Ya</given-names>
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<xref ref-type="aff" rid="aff3">
<sup>3</sup>
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<contrib contrib-type="author" corresp="yes">
<name>
<surname>Xu</surname>
<given-names>Fengqin</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
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<xref ref-type="aff" rid="aff2">
<sup>2</sup>
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<xref ref-type="corresp" rid="c001">&#x2a;</xref>
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<contrib contrib-type="author" corresp="yes">
<name>
<surname>Zhao</surname>
<given-names>Junnan</given-names>
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<sup>1</sup>
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<sup>2</sup>
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<aff id="aff1">
<sup>1</sup>
<institution>Institute of Geriatrics, Xiyuan Hospital, China Academy of Chinese Medical Sciences</institution>, <addr-line>Beijing</addr-line>, <country>China</country>
</aff>
<aff id="aff2">
<sup>2</sup>
<institution>Laboratory of Combining Diseases and Evidence to Prevent Vascular Aging, National Administration of Traditional Chinese Medicine</institution>, <addr-line>Beijing</addr-line>, <country>China</country>
</aff>
<aff id="aff3">
<sup>3</sup>
<institution>Dongzhimen Hospital, Beijing University of Chinese Medicine</institution>, <addr-line>Beijing</addr-line>, <country>China</country>
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<author-notes>
<fn fn-type="edited-by">
<p>
<bold>Edited by:</bold> <ext-link ext-link-type="uri" xlink:href="https://loop.frontiersin.org/people/1834139/overview">Yu-Qing Zhang</ext-link>, McMaster University, Canada</p>
</fn>
<fn fn-type="edited-by">
<p>
<bold>Reviewed by:</bold> <ext-link ext-link-type="uri" xlink:href="https://loop.frontiersin.org/people/157833/overview">Zeliha Selamoglu</ext-link>, Ni&#x11f;de &#xd6;mer Halisdemir University, T&#xfc;rkiye</p>
<p>
<ext-link ext-link-type="uri" xlink:href="https://loop.frontiersin.org/people/2121166/overview">Qian Li</ext-link>, Dali University, China</p>
</fn>
<corresp id="c001">&#x2a;Correspondence: Junnan Zhao, <email>13240050425@163.com</email>; Fengqin Xu, <email>doctorxu@aliyun.com</email>
</corresp>
</author-notes>
<pub-date pub-type="epub">
<day>02</day>
<month>10</month>
<year>2025</year>
</pub-date>
<pub-date pub-type="collection">
<year>2025</year>
</pub-date>
<volume>16</volume>
<elocation-id>1506234</elocation-id>
<history>
<date date-type="received">
<day>04</day>
<month>10</month>
<year>2024</year>
</date>
<date date-type="accepted">
<day>16</day>
<month>09</month>
<year>2025</year>
</date>
</history>
<permissions>
<copyright-statement>Copyright &#xa9; 2025 Hui, Wang, Xu and Zhao.</copyright-statement>
<copyright-year>2025</copyright-year>
<copyright-holder>Hui, Wang, Xu and Zhao</copyright-holder>
<license xlink:href="http://creativecommons.org/licenses/by/4.0/">
<p>This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.</p>
</license>
</permissions>
<abstract>
<sec>
<title>Objective</title>
<p>Hypertension remained an important public health problem with high morbidity and mortality and was emerging as a risk factor for future heart failure. The transition from hypertension to hypertensive heart disease (HHD) and heart failure grew progressively with time. Traditional Chinese medicine (TCM) has a history of several thousand years, where selected TCM for replenishing qi and activating blood circulation provides an alternative treatment for HHD.</p>
</sec>
<sec>
<title>Methods</title>
<p>An extensive literature search was conducted across eight electronic databases from their inception until 8 September 2023, to evaluate the potential preventive effects of selected TCM as an adjuvant therapy on the progression of HHD. The outcome measures included blood pressure and indicators of cardiac structure and function under cardiac ultrasound. The mean difference (MD) and 95% confidence interval (CI) were used to determine continuous outcomes. Risk ratio (RR) with 95% confidence interval (CI) was used to determine dichotomous outcomes. The information about the overall certainty of the evidence from studies was presented according to specific outcomes using the Grading of Recommendations Assessment, Development and Evaluation (GRADE) Guideline Development Tool (GDT) online software.</p>
</sec>
<sec>
<title>Results</title>
<p>Twenty-one randomized controlled trials (RCTs) involving 2, 055 participants were included. Meta-analyses favored integrated Chinese botanical drugs and Western medicine on blood pressure, New York Heart Association classification, left ventricular ejection fraction, transmitral peak early diastolic velocity/peak late diastolic velocity ratio, left ventricular internal diameters, left ventricular mass index, interventricular septum thickness in diastole, and B-type natriuretic peptide compared with Western medicine alone. Results on cardiac output should be interpreted with caution due to sample size limitations. No severe adverse events were identified. Most of the Chinese botanical drugs originated from classical TCM formulas. The dosage form of Chinese botanical drugs was oral. <italic>Salvia miltiorrhiza</italic> Bunge (Danshen), <italic>Oreocome striata</italic> (DC.) Pimenov &#x26; Kljuykov (Chuanxiong), <italic>Pueraria montana</italic> var. <italic>lobata</italic> (Willd.) Maesen &#x26; S.M.Almeida ex Sanjappa &#x26; Predeep (Gegen), <italic>Astragalus mongholicus</italic> Bunge (Huangqi), and <italic>Typha angustifolia</italic> L. (Puhuang) were the top 5 Chinese botanical drugs, which might be associated with replenishing qi and activating blood circulation.</p>
</sec>
<sec>
<title>Conclusion</title>
<p>Selected TCM had the potential to be effective as an adjuvant therapy for alleviating adverse left ventricular remodeling and improving cardiac function after HHD, and therapy of replenishing qi and activating blood circulation may serve as a potential reference for treatment. To better assess Chinese botanical drugs&#x2019; preventative effects, more long-term, high-quality RCTs are still necessary.</p>
</sec>
<sec>
<title>Systematic Review Registration</title>
<p>
<ext-link ext-link-type="uri" xlink:href="https://www.crd.york.ac.uk/PROSPERO/#myprospero">https://www.crd.york.ac.uk/PROSPERO/&#x23;myprospero</ext-link>, identifier CRD42022346030.</p>
</sec>
</abstract>
<abstract abstract-type="graphical">
<title>Graphical Abstract</title>
<p>
<graphic xlink:href="FPHAR_fphar-2025-1506234_wc_abs.tif" position="anchor">
<alt-text content-type="machine-generated">A flowchart and illustration detail the effects of traditional Chinese medicine on hypertensive heart disease. It includes study selection data from 21 RCTs with 2055 participants, highlighting primary and secondary outcomes like blood pressure and LVMI. The image features five medicinal plants: Salvia miltiorrhiza, Oenanthe striata, Pueraria montana var. lobata, Astragalus mongholicus, and Typha angustifolia, each linked to specific therapeutic effects, such as protecting vascular endothelium and regulating blood pressure. These measures help transition from hypertension to heart failure management.</alt-text>
</graphic>
</p>
</abstract>
<kwd-group>
<kwd>traditional Chinese medicine</kwd>
<kwd>therapy of replenishing qi and activating bloodcirculation</kwd>
<kwd>hypertensive heart disease</kwd>
<kwd>randomized controlled trial</kwd>
<kwd>systematic review</kwd>
<kwd>meta-analysis</kwd>
</kwd-group>
<counts>
<page-count count="26"/>
</counts>
<custom-meta-wrap>
<custom-meta>
<meta-name>section-at-acceptance</meta-name>
<meta-value>Ethnopharmacology</meta-value>
</custom-meta>
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</front>
<body>
<sec id="s1">
<title>1 Introduction</title>
<p>Hypertensive Heart Disease (HHD), defined as symptomatic heart failure (HF) due to direct and long-term exposure to hypertension, was one of the most serious effects with its nonfatal burden derived from the model of HF (<xref ref-type="bibr" rid="B19">Escaned and Lerman, 2020</xref>; <xref ref-type="bibr" rid="B67">Roth et al., 2017</xref>). In a 20-year follow-up of 5, 143 participants from the Framingham Heart Study cohort, of all newly diagnosed HF patients, 91% had hypertension before developing HF (<xref ref-type="bibr" rid="B39">Levy et al., 1996</xref>). A recent study brought attention to the importance of early-stage hypertension as a significant aetiological risk factor for the development of early HF (<xref ref-type="bibr" rid="B79">Tromp et al., 2021</xref>) that compared the age variation in incident HF risk variables in the general population. In young participants, hypertension was associated with a threefold increase in the chance of developing HF later on. In contrast to a 1.4-fold risk in elderly participants (&#x3e;65 years), in young participants (&#x3c;55 years), hypertension was associated with a three-fold increase in the chance of developing HF later on (<xref ref-type="bibr" rid="B2">Bay&#xe9;s-Gen&#xed;s and D&#xed;ez, 2022</xref>). Thus, elevated blood pressure (BP) was an essential risk factor for HF and, at the same time, a preventable cause (<xref ref-type="bibr" rid="B80">Virani et al., 2020</xref>; <xref ref-type="bibr" rid="B22">GBD, 2017 Risk Factor Collaborators, 2018</xref>). However, the early identification of patients with hypertension at risk of developing HF remains a challenge for clinicians (<xref ref-type="bibr" rid="B19">Escaned and Lerman, 2020</xref>). Long-term hypertension could cause hemodynamic stress that eventually changes the structure and metabolism of the myocardium. This could lead to cardiac remodeling, which showed up as HF and left ventricular (LV) dysfunction, and irregularities in myocardial perfusion and cardiac rhythm (<xref ref-type="bibr" rid="B14">Drazner, 2011</xref>; <xref ref-type="bibr" rid="B24">Gonz&#xe1;lez et al., 2018</xref>; <xref ref-type="bibr" rid="B2">Bay&#xe9;s-Gen&#xed;s and D&#xed;ez, 2022</xref>). Based on the clinical effects and pathophysiology of hypertension in the heart, HHD was divided into four ascending categories, including Degree &#x2160; (Isolated LV diastolic dysfunction with no LV hypertrophy (LVH)), Degree &#x2161; (LV diastolic dysfunction with concentric LVH), Degree &#x2162; (Clinical HF (dyspnea and pulmonary edema with preserved ejection fraction)), Degree &#x2163; (Dilated cardiomyopathy with HF and reduced ejection fraction) (<xref ref-type="bibr" rid="B56">Messerli et al., 2017</xref>; <xref ref-type="bibr" rid="B34">Iriarte et al., 1993</xref>). Therefore, HHD could be clinically asymptomatic or present with palpitations, chest tightness, dyspnea, biventricular failure, and sudden death (<xref ref-type="bibr" rid="B10">Dai et al., 2021</xref>). The results in the diagnosis of HHD largely rely on echocardiography and electrocardiogram (<xref ref-type="bibr" rid="B10">Dai et al., 2021</xref>; <xref ref-type="bibr" rid="B11">Devereux et al., 1993</xref>). Transthoracic echocardiography is the gold standard for noninvasive evaluation of cardiac structure and function. This provides a basis for assessing changes in cardiac structure during the shift from hypertension to HHD and HF. Previous studies suggested the adverse effects of hypertension on the heart (<xref ref-type="bibr" rid="B17">Ekhteiari Salmas et al., 2018</xref>; <xref ref-type="bibr" rid="B68">Salmas et al., 2017</xref>; <xref ref-type="bibr" rid="B69">Selamoglu Talas, 2014</xref>). Propolis is a resinous product collected by honeybees from various plant sources, which decreases tyrosine hydroxylase activity of the heart in nitric oxide synthase-inhibited hypertensive rats and thereby may modulate the synthesis of catecholamine and BP (<xref ref-type="bibr" rid="B23">Gogebakan et al., 2012</xref>). Antihypertensive medications, by definition, reduce BP, and when used as initial therapy, the majority of antihypertensive medications slowed the progression from hypertension to HF. However, examining the research on antihypertensive medications showed that not all of them have the same ability to prevent HF, for example, once-daily, low-dose hydrochlorothiazide was not recommended (<xref ref-type="bibr" rid="B56">Messerli et al., 2017</xref>). Thus, it was urgently needed to search for supplementary and alternative medical treatments for more effective control of HHD.</p>
<p>The investigation of traditional Chinese medicine (TCM) has the potential to lay an invaluable foundation for the development of new therapeutics. Multiple traditional botanical drugs and their metabolites, which are well-known for their proven excellent pharmacological effects, have long been utilized to treat different diseases, specifically cardiovascular disorders (<xref ref-type="bibr" rid="B78">Tavolinejad et al., 2019</xref>; <xref ref-type="bibr" rid="B94">Yousefsani et al., 2021</xref>). With the increasingly clinical application of selected TCM for replenishing qi and activating blood circulation in the therapy and prevention of cardiovascular diseases (<xref ref-type="bibr" rid="B48">Liu and Huang, 2016</xref>), therapy of replenishing qi and activating blood circulation has become an important role as a supplement and alternative treatment in clinical practice. Up till now, some randomized controlled trials (RCTs) have reported the effect of TCM on patients with HHD. The impact of selected TCM as an adjuvant therapy for the advancement of HHD disease was examined in this meta-analysis.</p>
</sec>
<sec sec-type="materials|methods" id="s2">
<title>2 Materials and methods</title>
<p>The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) reporting guideline recommendations were adhered to in this systematic review (<xref ref-type="bibr" rid="B61">Page et al., 2021</xref>), and <xref ref-type="sec" rid="s13">Supplementary Table S1</xref> contained the PRISMA checklist. The systematic review protocol was registered with International Prospective Register of Systematic Reviews (PROSPERO) (CRD42022346030) on 23 July 2022, prior to the initiation of study screening. Since this study involved a meta-analysis of data that had already been published, Ethics and Institutional Review Board approval was not necessary.</p>
<sec id="s2-1">
<title>2.1 Search strategy</title>
<p>Eight electronic databases were systematically searched, including PubMed, the Cochrane Library, Embase, Web of Science, Wanfang Database, China National Knowledge Infrastructure (CNKI), Chinese Scientific Journal Database (Chinese VIP Information), and Chinese Biomedical Database (SinoMed) from inception to 8 September 2023, with no language or publication restrictions applied. Grey literature searches included Web of Science Conference Proceedings Citation Index-Science (CPCI-S), <ext-link ext-link-type="uri" xlink:href="http://ClinicalTrials.gov">ClinicalTrials.gov</ext-link> (<ext-link ext-link-type="uri" xlink:href="http://www.clinicaltrials.gov/">www.clinicaltrials.gov/</ext-link>), the World Health Organization International Clinical Trials Registry Platform (WHO ICTRP) (<ext-link ext-link-type="uri" xlink:href="http://www.who.int/ictrp/en/">www.who.int/ictrp/en/</ext-link>), and International Traditional Medicine Clinical Trial Registry (ITMCTR) (itmctr.ccebtcm.org.cn/) using key terms and scanning reference lists of relevant reviews. &#x2018;Medicine, Chinese Traditional&#x2019; was used as the Medical Subject Heading and matched with corresponding free words for enhancing accuracy. Given the discrepancy between databases, the keywords were adjusted flexibly for &#x2018;hypertensive heart disease&#x2019; and &#x2018;hypertensive cardiovascular disease.&#x2019; Search strategies were adapted to the specific syntax and controlled vocabulary of each database. Finally, all retrieval expressions were formed by logically connecting AND or OR. For example, the PubMed Database was searched as follows:</p>
<p>&#x23;1 (hypertensive heart disease [Title/Abstract]) OR (hypertensive cardiovascular disease [Title/Abstract])</p>
<p>&#x23;2 &#x201c;Medicine, Chinese Traditional&#x201d; [Mesh]</p>
<p>&#x23;3 (((((((((Traditional Chinese Medicine [Title/Abstract]) OR (Chung I Hsueh [Title/Abstract])) OR (Hsueh, Chung I [Title/Abstract])) OR (Traditional Medicine, Chinese [Title/Abstract])) OR (Zhong Yi Xue [Title/Abstract])) OR (Chinese Traditional Medicine [Title/Abstract])) OR (Chinese Medicine, Traditional [Title/Abstract])) OR (Drugs, Chinese Herbal [Title/Abstract])) OR (Complementary Therapies [Title/Abstract])) OR (Alternative Medicine [Title/Abstract])</p>
<p>&#x23;4 &#x23;2 OR &#x23;3.</p>
<p>&#x23;5 &#x23;1 AND &#x23;4.</p>
<p>The full search strategy is shown in <xref ref-type="sec" rid="s13">Supplementary Table S2</xref>.</p>
</sec>
<sec id="s2-2">
<title>2.2 Inclusion and exclusion criteria</title>
<p>Study eligibility criteria were defined using the PICOS (Participants, Intervention, Comparators, Outcomes, Study design) approach. The inclusion criteria were as follows: (1) patients received a diagnosis of HHD without restrictions on gender, age, ethnicity, or disease stage; (2) patients in the TCM group were treated with Chinese botanical drugs based on those in the control group. Chinese botanical drugs was administered orally at least two-week-long treatment interventions, including Chinese patent medicine, single botanical drug, or TCM prescription; (3) the control group received conventional pharmacological interventions (Western medicine (WM); (4) the primary outcomes included BP (including systolic blood pressure (SBP) and diastolic blood pressure (DBP)), New York Heart Association (NYHA) classification, and left ventricular ejection fraction (LVEF); the secondary outcomes included cardiac output (CO), transmitral peak early diastolic velocity (E)/peak late diastolic velocity (A) ratio (E/A ratio), left ventricular internal diameters (including left ventricular end-diastolic diameter (LVEDD) and left ventricular end-systolic diameter (LVESD)), left ventricular mass index (LVMI), interventricular septum thickness in diastole (IVSTD), B-type natriuretic peptide (BNP), and adverse events; (5) the included RCTs were reported in completed paper article. To prevent duplication, we kept the most current publication or the most informative single article where the same population was published in multiple publications.</p>
<p>The exclusion criteria were as follows: (1) interventions included nonoral Chinese botanical drugs or appropriate TCM techniques; (2) it was not reported which botanical drugs were included in the TCM prescription containing multiple botanical drugs, nor the dosage of each type of botanical drug used; (3) it was not reported the administration method of the Chinese patent medicine, including the frequency of administration and the single oral dosage; (4) no relevant outcomes or no available data were reported; (5) the intervention period was less than 2&#xa0;weeks or not reported; (6) the types of studies were reviews, case reports, retrospective studies, etc.</p>
</sec>
<sec id="s2-3">
<title>2.3 Study selection and data extraction</title>
<p>All identified indexed records were downloaded into EndNote X9, and duplicates were removed. After that, two review authors (J. Hui and Y. Wang) separately went through the titles and abstracts and evaluated the full-text publications to look for studies that might be included. Following PRISMA criteria, a flow chart contained the records of the research selection within the systematic review. Until data extractors achieved convergence and agreement, a standard data extraction form was created and tested. Independently, two review authors retrieved study characteristics and outcome data, including characteristics of the author, year, patients (e.g., age, gender, sample size), medication details for the experimental and control group, and outcome indicators. When there were several endpoint indicators in the literature, the longest one was chosen. If any clarification or further information was required, the corresponding authors of the original studies were contacted. Conflicts in data extraction were handled by the third review author (J. Zhao).</p>
</sec>
<sec id="s2-4">
<title>2.4 Methodological quality assessment</title>
<p>Two review authors (J. Hui and Y. Wang) independently assessed the risk of bias of all included RCTs using the Cochrane tool for assessing the risk of bias (<xref ref-type="bibr" rid="B28">Higgins et al., 2011</xref>). We resolved differences by discussion or by appeal to a third review author (J. Zhao). Following the recommendations of the Cochrane Handbook, the methodological quality was evaluated using seven domains: incomplete outcome data (attrition bias), selective reporting (reporting bias), blinding of participants and personnel (performance bias), random sequence generation (selection bias), allocation concealment (selection bias), and other bias. Three categories were used to classify each domain: low risk of bias, high risk of bias, and uncertain risk of bias. The original authors were contacted to verify and authenticate the randomization and allocation concealment procedures. If the original authors did not communicate, disagreements were settled by debate.</p>
</sec>
<sec id="s2-5">
<title>2.5 Data synthesis and statistical analysis</title>
<p>Statistical analysis was carried out using Review Manager 5.3 software (Cochrane Collaboration, Denmark). The mean difference (MD) or standardized mean difference (SMD) with 95% confidence interval (CI) was used to integrate continuous outcomes. SMD was used when different scales were used across studies. Dichotomous outcomes were calculated as risk ratio (RR) with 95% CI. We used the Chi<sup>2</sup> (&#x3c7;<sup>2</sup>) test and I<sup>2</sup> statistic to quantify heterogeneity across included studies, where an I<sup>2</sup> of 25% or less was regarded as low heterogeneity, an I<sup>2</sup> of 26%&#x2013;50% was regarded as moderate heterogeneity, and an I<sup>2</sup> of over 50% was regarded as substantial heterogeneity (<xref ref-type="bibr" rid="B27">Higgins et al., 2003</xref>). When there was little to no heterogeneity (I<sup>2</sup> &#x2264; 50%), a fixed-effects model was employed; when there was significant heterogeneity (I<sup>2</sup> &#x2c3; 50%), a random-effects model was used. All two-tailed P &#x3c; 0.05 were considered statistically significant. Numerous participant- or intervention-related characteristics might be connected to heterogeneity among studies. If substantial heterogeneity was detected, we would perform subgroup and sensitivity analyses to investigate possible sources of heterogeneity between studies. Subsequently, sensitivity analyses were carried out by repeating the meta-analysis and removing each study one at a time to assess the robustness and dependability of the findings.</p>
</sec>
<sec id="s2-6">
<title>2.6 Quality of evidence</title>
<p>We summarized the quality of the evidence using the Grading of Recommendations Assessment, Development and Evaluation (GRADE) Guideline Development Tool (GDT) (<ext-link ext-link-type="uri" xlink:href="http://www.gradepro.org">www.gradepro.org</ext-link>). A final quality rating of high, moderate, low, or very poor was assigned to the evidence based on factors such as research design, risk of bias, inconsistency, indirectness, imprecision, and other factors.</p>
</sec>
<sec id="s2-7">
<title>2.7 Publication bias</title>
<p>The assessment of publication bias may be limited if there are insufficient studies for the outcomes. Using Stata 12.0 software, a visual assessment of the funnel plot was used to assess publication bias. Asymmetry indicated publication bias. In the meantime, funnel plot asymmetry was statistically demonstrated using Egger&#x2019;s test. Publication bias does not exist if P &#x3e; 0.05, and <italic>vice versa</italic>. The study&#x2019;s analysis was adjusted for the impact of publication bias using the Duval and Tweedie trim-and-fill method.</p>
</sec>
</sec>
<sec sec-type="results" id="s3">
<title>3 Results</title>
<sec id="s3-1">
<title>3.1 Study selection</title>
<p>The literature searching process and research identification are summarized in <xref ref-type="fig" rid="F1">Figure 1</xref>. A total of 1, 408 records were identified; 1, 407 from the database search approach, and one more study was found by looking through the reviews&#x2019; recognized references. In brief, for the 1,407 records via databases, following the initial database search and the removal of duplicate records, 1, 230 records were found. 1, 176 records were removed after additional title and abstract screening, mostly due to their lack of relevance to the study&#x2019;s objectives. 33 of the 54 records that were subjected to a full-text review were eliminated because 21 of them contained only outcomes that were not relevant, three did not provide available outcome data, seven did not report the specific TCM prescription, and the other 2 records an unclear intervention periods or were of less than 2 weeks. Lastly, 21 studies were included in the review. Additionally, one study that was found by manually scanning the reference list was eliminated because it had no bearing on the goal of the investigation.</p>
<fig id="F1" position="float">
<label>FIGURE 1</label>
<caption>
<p>Flow diagram of the study selection process. Abbreviation: CNKI: China National Knowledge Infrastructure; HHD: hypertensive heart disease; RCT: randomized controlled trial; TCM: traditional Chinese medicine; VIP: Chinese Scientific Journal Database (Chinese VIP Information); SinoMed: Chinese Biomedical Database.</p>
</caption>
<graphic xlink:href="fphar-16-1506234-g001.tif">
<alt-text content-type="machine-generated">Flowchart depicting the identification, screening, and inclusion process of studies. From databases, 1,407 records were identified, with 177 duplicates removed. After screening, 1,176 records were excluded for reasons like being non-HHD or non-TCM. From other methods, 1 record was identified but excluded for not being TCM. Finally, 21 studies were included in the review.</alt-text>
</graphic>
</fig>
</sec>
<sec id="s3-2">
<title>3.2 Characteristics of included studies</title>
<p>The baseline characteristics of included 21 RCTs were summarized in <xref ref-type="table" rid="T1">Table 1</xref> (<xref ref-type="bibr" rid="B4">Cai, 2016</xref>; <xref ref-type="bibr" rid="B9">Cui, 2022</xref>; <xref ref-type="bibr" rid="B15">Du, 2016</xref>; <xref ref-type="bibr" rid="B29">Hou et al., 2015</xref>; <xref ref-type="bibr" rid="B30">Hu, 2012</xref>; <xref ref-type="bibr" rid="B36">Jin and Wu, 2006</xref>; <xref ref-type="bibr" rid="B42">Li et al., 2019</xref>; <xref ref-type="bibr" rid="B47">Liu, 2012</xref>; <xref ref-type="bibr" rid="B63">Peng, 2015</xref>; <xref ref-type="bibr" rid="B71">Song, 2011</xref>; <xref ref-type="bibr" rid="B72">Song, 2019</xref>; <xref ref-type="bibr" rid="B76">Tan, 2019</xref>; <xref ref-type="bibr" rid="B77">Tao, 2021</xref>; <xref ref-type="bibr" rid="B82">Wang and Wang, 2012</xref>; <xref ref-type="bibr" rid="B83">Wang et al., 2012</xref>; <xref ref-type="bibr" rid="B81">Wang and Sun, 2018</xref>; <xref ref-type="bibr" rid="B90">Yang and Zhou, 2002</xref>; <xref ref-type="bibr" rid="B95">Yuan, 2018</xref>; <xref ref-type="bibr" rid="B96">Zhang, 2013</xref>; <xref ref-type="bibr" rid="B99">Zhao, 2022</xref>; <xref ref-type="bibr" rid="B100">Zhu et al., 2019</xref>). The studies were published between 2002 and 2022. The demographics and clinical features of the population that was part of the meta-analysis were homogenous. A total of 2,055 individuals were involved in the research, with 1, 177 males and 878 females. The ages of the participants varied from 18 to 83 years. In 15 studies, the course of disease was reported, but not in the others. With 1, 041 patients in the CHM group and 1, 014 patients in the control group, the sample sizes of the included trials varied from 48 to 210. The control group received only WM treatment, while all CHM groups received oral CHM plus WM. The included studies&#x2019; treatment durations varied from 25 days to 12 months. For outcome measures, 6 (6/21, 28.6%) RCTs (<xref ref-type="bibr" rid="B4">Cai, 2016</xref>; <xref ref-type="bibr" rid="B63">Peng, 2015</xref>; <xref ref-type="bibr" rid="B76">Tan, 2019</xref>; <xref ref-type="bibr" rid="B81">Wang and Sun, 2018</xref>; <xref ref-type="bibr" rid="B90">Yang and Zhou, 2002</xref>; <xref ref-type="bibr" rid="B95">Yuan, 2018</xref>) reported BP, including SBP and DBP; 11 (11/21, 52.4%) RCTs (<xref ref-type="bibr" rid="B4">Cai, 2016</xref>; <xref ref-type="bibr" rid="B30">Hu, 2012</xref>; <xref ref-type="bibr" rid="B42">Li et al., 2019</xref>; <xref ref-type="bibr" rid="B63">Peng, 2015</xref>; <xref ref-type="bibr" rid="B71">Song, 2011</xref>; <xref ref-type="bibr" rid="B76">Tan, 2019</xref>; <xref ref-type="bibr" rid="B82">Wang and Wang, 2012</xref>; <xref ref-type="bibr" rid="B83">Wang et al., 2012</xref>; <xref ref-type="bibr" rid="B81">Wang and Sun, 2018</xref>; <xref ref-type="bibr" rid="B90">Yang and Zhou, 2002</xref>; <xref ref-type="bibr" rid="B99">Zhao, 2022</xref>) reported NYHA classification; 13 (13/21, 61.9%) RCTs (<xref ref-type="bibr" rid="B9">Cui, 2022</xref>; <xref ref-type="bibr" rid="B15">Du, 2016</xref>; <xref ref-type="bibr" rid="B36">Jin and Wu, 2006</xref>; <xref ref-type="bibr" rid="B42">Li et al., 2019</xref>; <xref ref-type="bibr" rid="B72">Song, 2019</xref>; <xref ref-type="bibr" rid="B76">Tan, 2019</xref>; <xref ref-type="bibr" rid="B77">Tao, 2021</xref>; <xref ref-type="bibr" rid="B83">Wang et al., 2012</xref>; <xref ref-type="bibr" rid="B81">Wang and Sun, 2018</xref>; <xref ref-type="bibr" rid="B90">Yang and Zhou, 2002</xref>; <xref ref-type="bibr" rid="B95">Yuan, 2018</xref>; <xref ref-type="bibr" rid="B96">Zhang, 2013</xref>; <xref ref-type="bibr" rid="B100">Zhu et al., 2019</xref>) reported LVEF; 2 (2/21, 9.5%) RCTs (<xref ref-type="bibr" rid="B15">Du, 2016</xref>; <xref ref-type="bibr" rid="B77">Tao, 2021</xref>) reported CO; 3 (3/21, 14.3%) RCTs (<xref ref-type="bibr" rid="B4">Cai, 2016</xref>; <xref ref-type="bibr" rid="B42">Li et al., 2019</xref>; <xref ref-type="bibr" rid="B82">Wang and Wang, 2012</xref>) reported E/A ratio; 9 (9/21, 42.9%) RCTs (<xref ref-type="bibr" rid="B29">Hou et al., 2015</xref>; <xref ref-type="bibr" rid="B47">Liu, 2012</xref>; <xref ref-type="bibr" rid="B72">Song, 2019</xref>; <xref ref-type="bibr" rid="B76">Tan, 2019</xref>; <xref ref-type="bibr" rid="B81">Wang and Sun, 2018</xref>; <xref ref-type="bibr" rid="B95">Yuan, 2018</xref>; <xref ref-type="bibr" rid="B96">Zhang, 2013</xref>; <xref ref-type="bibr" rid="B99">Zhao, 2022</xref>; <xref ref-type="bibr" rid="B100">Zhu et al., 2019</xref>) reported LVEDD; 4 (4/21, 19.0%) RCTs (<xref ref-type="bibr" rid="B76">Tan, 2019</xref>; <xref ref-type="bibr" rid="B81">Wang and Sun, 2018</xref>; <xref ref-type="bibr" rid="B99">Zhao, 2022</xref>; <xref ref-type="bibr" rid="B100">Zhu et al., 2019</xref>) reported LVESD; 2 (2/21, 9.5%) RCTs (<xref ref-type="bibr" rid="B29">Hou et al., 2015</xref>; <xref ref-type="bibr" rid="B47">Liu, 2012</xref>) reported LVMI; 3 (3/21, 14.3%) RCTs (<xref ref-type="bibr" rid="B42">Li et al., 2019</xref>; <xref ref-type="bibr" rid="B76">Tan, 2019</xref>; <xref ref-type="bibr" rid="B81">Wang and Sun, 2018</xref>) reported IVSTD; 3 (3/21, 14.3%) RCTs (<xref ref-type="bibr" rid="B71">Song, 2011</xref>; <xref ref-type="bibr" rid="B81">Wang and Sun, 2018</xref>; <xref ref-type="bibr" rid="B99">Zhao, 2022</xref>) reported BNP; and 8 (8/21, 38.1%) RCTs (<xref ref-type="bibr" rid="B4">Cai, 2016</xref>; <xref ref-type="bibr" rid="B9">Cui, 2022</xref>; <xref ref-type="bibr" rid="B30">Hu, 2012</xref>; <xref ref-type="bibr" rid="B63">Peng, 2015</xref>; <xref ref-type="bibr" rid="B71">Song, 2011</xref>; <xref ref-type="bibr" rid="B83">Wang et al., 2012</xref>; <xref ref-type="bibr" rid="B81">Wang and Sun, 2018</xref>; <xref ref-type="bibr" rid="B90">Yang and Zhou, 2002</xref>) reported adverse events.</p>
<table-wrap id="T1" position="float">
<label>TABLE 1</label>
<caption>
<p>Characteristics of included studies.</p>
</caption>
<table>
<thead valign="top">
<tr>
<th rowspan="2" align="left">References</th>
<th colspan="2" align="left">Age (mean &#xb1; SD, year)</th>
<th rowspan="2" align="left">Gender (male/female)</th>
<th rowspan="2" align="left">Sample size (T/C)</th>
<th colspan="2" align="left">Course of disease (mean &#xb1; SD, year)</th>
<th rowspan="2" align="left">Intervention (T/C)</th>
<th rowspan="2" align="left">Duration</th>
<th rowspan="2" align="left">Outcome indicator</th>
</tr>
<tr>
<th align="left">T</th>
<th align="left">C</th>
<th align="left">T</th>
<th align="left">C</th>
</tr>
</thead>
<tbody valign="top">
<tr>
<td align="left">
<xref ref-type="bibr" rid="B4">Cai (2016)</xref>
</td>
<td align="left">56&#x2013;76<break/>(63.1 &#xb1; 2.2)</td>
<td align="left">55&#x2013;78<break/>(63.5 &#xb1; 2.1)</td>
<td align="left">41/34</td>
<td align="left">38/37</td>
<td align="left">NR</td>
<td align="left">NR</td>
<td align="left">TCM &#x2b; WM/WM</td>
<td align="left">2 months</td>
<td align="left">&#x2460;&#x2461;&#x2464;&#x246a;</td>
</tr>
<tr>
<td align="left">
<xref ref-type="bibr" rid="B9">Cui (2022)</xref>
</td>
<td align="left">52&#x2013;82<break/>(67.13 &#xb1; 14.87)</td>
<td align="left">49&#x2013;83<break/>(66.23 &#xb1; 16.77)</td>
<td align="left">61/61</td>
<td align="left">61/61</td>
<td align="left">4&#x2013;16 (10.33 &#xb1; 5.67)</td>
<td align="left">5&#x2013;15<break/>(10.24 &#xb1; 4.76)</td>
<td align="left">TCM &#x2b; WM/WM</td>
<td align="left">3 months</td>
<td align="left">&#x2462;&#x246a;</td>
</tr>
<tr>
<td align="left">
<xref ref-type="bibr" rid="B15">Du (2016)</xref>
</td>
<td align="left">30&#x2013;81<break/>(55.3 &#xb1; 7.2)</td>
<td align="left">31&#x2013;78<break/>(52.3 &#xb1; 6.8)</td>
<td align="left">105/105</td>
<td align="left">105/105</td>
<td align="left">1&#x2013;15<break/>(7.8 &#xb1; 3.9)</td>
<td align="left">1&#x2013;16<break/>(7.9 &#xb1; 3.8)</td>
<td align="left">TCM &#x2b; WM/WM</td>
<td align="left">90 days</td>
<td align="left">&#x2462;&#x2463;</td>
</tr>
<tr>
<td align="left">
<xref ref-type="bibr" rid="B29">Hou et al. (2015)</xref>
</td>
<td align="left">40&#x2013;80<break/>(59.44 &#xb1; 11.27)</td>
<td align="left">39&#x2013;78<break/>(58.89 &#xb1; 11.39)</td>
<td align="left">60/38</td>
<td align="left">49/49</td>
<td align="left">NR</td>
<td align="left">NR</td>
<td align="left">TCM &#x2b; WM/WM</td>
<td align="left">1 month</td>
<td align="left">&#x2465;&#x2467;</td>
</tr>
<tr>
<td align="left">
<xref ref-type="bibr" rid="B30">Hu (2012)</xref>
</td>
<td align="left">34&#x2013;75<break/>(55 &#xb1; 6.7)</td>
<td align="left">33&#x2013;77<break/>(55 &#xb1; 7.6)</td>
<td align="left">95/47</td>
<td align="left">72/70</td>
<td align="left">1&#x2013;21<break/>(14 &#xb1; 2.1)</td>
<td align="left">1&#x2013;23<break/>(14 &#xb1; 2.3)</td>
<td align="left">TCM &#x2b; WM/WM</td>
<td align="left">25 days</td>
<td align="left">&#x2461;&#x246a;</td>
</tr>
<tr>
<td align="left">
<xref ref-type="bibr" rid="B36">Jin and Wu (2006)</xref>
</td>
<td align="left">53&#x2013;78</td>
<td align="left">55&#x2013;78</td>
<td align="left">36/28</td>
<td align="left">34/30</td>
<td align="left">NR</td>
<td align="left">NR</td>
<td align="left">TCM &#x2b; WM/WM</td>
<td align="left">6 months</td>
<td align="left">&#x2461;&#x2462;</td>
</tr>
<tr>
<td align="left">
<xref ref-type="bibr" rid="B42">Li et al. (2019)</xref>
</td>
<td align="left">18&#x2013;70<break/>(62.13 &#xb1; 8.24)</td>
<td align="left">18&#x2013;70<break/>(61.02 &#xb1; 9.02)</td>
<td align="left">71/41</td>
<td align="left">56/56</td>
<td align="left">6.88 &#xb1; 1.26</td>
<td align="left">7.21 &#xb1; 1.37</td>
<td align="left">TCM &#x2b; WM/WM</td>
<td align="left">2 months</td>
<td align="left">&#x2461;&#x2462;&#x2464;&#x2468;</td>
</tr>
<tr>
<td align="left">
<xref ref-type="bibr" rid="B47">Liu (2012)</xref>
</td>
<td align="left">39&#x2013;79<break/>(56.3 &#xb1; 6.4)</td>
<td align="left">36&#x2013;78<break/>(56.2 &#xb1; 6.5)</td>
<td align="left">121/75</td>
<td align="left">98/98</td>
<td align="left">NR</td>
<td align="left">NR</td>
<td align="left">TCM &#x2b; WM/WM</td>
<td align="left">12 weeks</td>
<td align="left">&#x2465;&#x2467;</td>
</tr>
<tr>
<td align="left">
<xref ref-type="bibr" rid="B63">Peng (2015)</xref>
</td>
<td align="left">32&#x2013;76<break/>(61.8 &#xb1; 10.2)</td>
<td align="left">32&#x2013;74<break/>(60.2 &#xb1; 11.4)</td>
<td align="left">44/52</td>
<td align="left">48/48</td>
<td align="left">NR</td>
<td align="left">NR</td>
<td align="left">TCM &#x2b; WM/WM</td>
<td align="left">12 months</td>
<td align="left">&#x2460;&#x2461;&#x246a;</td>
</tr>
<tr>
<td align="left">
<xref ref-type="bibr" rid="B71">Song (2011)</xref>
</td>
<td colspan="2" align="left">48&#x2013;65</td>
<td align="left">50/35</td>
<td align="left">42/43</td>
<td align="left">NR</td>
<td align="left">NR</td>
<td align="left">TCM &#x2b; WM/WM</td>
<td align="left">4 weeks</td>
<td align="left">&#x2461;&#x2469;&#x246a;</td>
</tr>
<tr>
<td align="left">
<xref ref-type="bibr" rid="B72">Song (2019)</xref>
</td>
<td align="left">41&#x2013;72<break/>(62.6 &#xb1; 7.3)</td>
<td align="left">40&#x2013;72<break/>(62.5 &#xb1; 7.2)</td>
<td align="left">57/39</td>
<td align="left">48/48</td>
<td align="left">1&#x2013;6<break/>(2.4 &#xb1; 0.5)</td>
<td align="left">1&#x2013;6<break/>(2.3 &#xb1; 0.6)</td>
<td align="left">TCM &#x2b; WM/WM</td>
<td align="left">4 weeks</td>
<td align="left">&#x2462;&#x2465;</td>
</tr>
<tr>
<td align="left">
<xref ref-type="bibr" rid="B76">Tan (2019)</xref>
</td>
<td align="left">53&#x2013;78<break/>(65.5 &#xb1; 2.2)</td>
<td align="left">51&#x2013;76<break/>(63.5 &#xb1; 1.8)</td>
<td align="left">46/34</td>
<td align="left">40/40</td>
<td align="left">1&#x2013;8<break/>(4.5 &#xb1; 2.2)</td>
<td align="left">1&#x2013;6<break/>(3.5 &#xb1; 1.5)</td>
<td align="left">TCM &#x2b; WM/WM</td>
<td align="left">3 months</td>
<td align="left">&#x2460;&#x2461;&#x2462;&#x2465;&#x2466;&#x2468;</td>
</tr>
<tr>
<td align="left">
<xref ref-type="bibr" rid="B77">Tao (2021)</xref>
</td>
<td align="left">31&#x2013;74<break/>(55.98 &#xb1; 8.7)</td>
<td align="left">30&#x2013;75<break/>(56.23 &#xb1; 7.6)</td>
<td align="left">33/27</td>
<td align="left">30/30</td>
<td align="left">1&#x2013;16<break/>(8.45 &#xb1; 0.94)</td>
<td align="left">1&#x2013;15<break/>(8.49 &#xb1; 0.93)</td>
<td align="left">TCM &#x2b; WM/WM</td>
<td align="left">2 months</td>
<td align="left">&#x2462;&#x2463;</td>
</tr>
<tr>
<td align="left">
<xref ref-type="bibr" rid="B82">Wang and Wang (2012)</xref>
</td>
<td align="left">59&#x2013;78</td>
<td align="left">62&#x2013;82</td>
<td align="left">58/48</td>
<td align="left">53/53</td>
<td align="left">2&#x2013;6</td>
<td align="left">2&#x2013;6</td>
<td align="left">TCM &#x2b; WM/WM</td>
<td align="left">2 months</td>
<td align="left">&#x2461;&#x2464;</td>
</tr>
<tr>
<td align="left">
<xref ref-type="bibr" rid="B83">Wang et al. (2012)</xref>
</td>
<td align="left">42&#x2013;56</td>
<td align="left">40&#x2013;58</td>
<td align="left">33/27</td>
<td align="left">30/30</td>
<td colspan="2" align="left">2&#x2013;7</td>
<td align="left">TCM &#x2b; WM/WM</td>
<td align="left">24 weeks</td>
<td align="left">&#x2461;&#x2462;&#x246a;</td>
</tr>
<tr>
<td align="left">
<xref ref-type="bibr" rid="B81">Wang and Sun (2018)</xref>
</td>
<td align="left">42&#x2013;76<break/>(68.59 &#xb1; 8.13)</td>
<td align="left">40&#x2013;81<break/>(65.06 &#xb1; 7.28)</td>
<td align="left">47/43</td>
<td align="left">45/45</td>
<td align="left">1&#x2013;5<break/>(2.19 &#xb1; 0.46)</td>
<td align="left">1&#x2013;6<break/>(2.38 &#xb1; 0.61)</td>
<td align="left">TCM &#x2b; WM/WM</td>
<td align="left">2 months</td>
<td align="left">&#x2460;&#x2461;&#x2462;&#x2465;&#x2466;&#x2468;&#x2469;&#x246a;</td>
</tr>
<tr>
<td align="left">
<xref ref-type="bibr" rid="B90">Yang and Zhou (2002)</xref>
</td>
<td align="left">32&#x2013;72<break/>(58.88 &#xb1; 9.64)</td>
<td align="left">34&#x2013;73<break/>(56.98 &#xb1; 8.52)</td>
<td align="left">54/31</td>
<td align="left">56/29</td>
<td align="left">0.5&#x2013;30<break/>(4.00 &#xb1; 5.64)</td>
<td align="left">0.67&#x2013;32<break/>(4.10 &#xb1; 4.82)</td>
<td align="left">TCM &#x2b; WM/WM</td>
<td align="left">2 months</td>
<td align="left">&#x2460;&#x2462;&#x246a;</td>
</tr>
<tr>
<td align="left">
<xref ref-type="bibr" rid="B95">Yuan (2018)</xref>
</td>
<td align="left">46&#x2013;77<break/>(61.4 &#xb1; 8.5)</td>
<td align="left">48&#x2013;79<break/>(63.0 &#xb1; 9.3)</td>
<td align="left">59/33</td>
<td align="left">46/46</td>
<td align="left">1&#x2013;5<break/>(3.2 &#xb1; 1.7)</td>
<td align="left">1&#x2013;6<break/>(3.5 &#xb1; 1.5)</td>
<td align="left">TCM &#x2b; WM/WM</td>
<td align="left">2 months</td>
<td align="left">&#x2460;&#x2462;&#x2465;</td>
</tr>
<tr>
<td align="left">
<xref ref-type="bibr" rid="B96">Zhang (2013)</xref>
</td>
<td colspan="2" align="left">41&#x2013;73 (63.9 &#xb1; 7.2)</td>
<td align="left">41/27</td>
<td align="left">30/38</td>
<td colspan="2" align="left">1&#x2013;5 (1.5 &#xb1; 0.4)</td>
<td align="left">TCM &#x2b; WM/WM</td>
<td align="left">4 weeks</td>
<td align="left">&#x2462;&#x2465;</td>
</tr>
<tr>
<td align="left">
<xref ref-type="bibr" rid="B99">Zhao (2022)</xref>
</td>
<td align="left">44&#x2013;76<break/>(63.58 &#xb1; 7.92)</td>
<td align="left">43&#x2013;75<break/>(63.45 &#xb1; 7.89)</td>
<td align="left">37/33</td>
<td align="left">35/35</td>
<td align="left">1&#x2013;6.5<break/>(2.40 &#xb1; 0.49)</td>
<td align="left">1.5&#x2013;6<break/>(2.32 &#xb1; 0.52)</td>
<td align="left">TCM &#x2b; WM/WM</td>
<td align="left">2 months</td>
<td align="left">&#x2461;&#x2465;&#x2466;&#x2469;</td>
</tr>
<tr>
<td align="left">
<xref ref-type="bibr" rid="B100">Zhu et al. (2019)</xref>
</td>
<td align="left">45&#x2013;75<break/>(58.2 &#xb1; 6.5)</td>
<td align="left">45&#x2013;75<break/>(56.5 &#xb1; 6.0)</td>
<td align="left">28/20</td>
<td align="left">25/23</td>
<td align="left">21.5 &#xb1; 2.5</td>
<td align="left">18.5 &#xb1; 1.8</td>
<td align="left">TCM &#x2b; WM/WM</td>
<td align="left">6 months</td>
<td align="left">&#x2462;&#x2465;&#x2466;</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn>
<p>C: the control group; NR: not reported; T: the TCM group; TCM: traditional Chinese medicine; WM: western medicine; &#x2460;: Blood pressure (including systolic and diastolic blood pressure); &#x2461;: New York Heart Association classification; &#x2462;: left ventricular ejection fraction; &#x2463;: cardiac output; &#x2464;: E/A ratio; &#x2465;: left ventricular end-diastolic diameter; &#x2466;: left ventricular end-systolic diameter; &#x2467;: left ventricular mass index; &#x2468;: interventricular septum thickness in diastole; &#x2469;: B-type natriuretic peptide; &#x246a;: adverse events.</p>
</fn>
</table-wrap-foot>
</table-wrap>
</sec>
<sec id="s3-3">
<title>3.3 Risk of bias</title>
<p>Two review authors evaluated the risk of bias of the included 21 RCTs and discrepancies were resolved via consensus. The results are shown in <xref ref-type="fig" rid="F2">Figure 2</xref>. Among 21 RCTs, eight studies (<xref ref-type="bibr" rid="B4">Cai, 2016</xref>; <xref ref-type="bibr" rid="B29">Hou et al., 2015</xref>; <xref ref-type="bibr" rid="B36">Jin and Wu, 2006</xref>; <xref ref-type="bibr" rid="B42">Li et al., 2019</xref>; <xref ref-type="bibr" rid="B76">Tan, 2019</xref>; <xref ref-type="bibr" rid="B90">Yang and Zhou, 2002</xref>; <xref ref-type="bibr" rid="B95">Yuan, 2018</xref>; <xref ref-type="bibr" rid="B100">Zhu et al., 2019</xref>) presented a low risk of bias in the sequence generation process, one study (<xref ref-type="bibr" rid="B42">Li et al., 2019</xref>) presented a low risk of bias in allocation concealment, and one study (<xref ref-type="bibr" rid="B83">Wang et al., 2012</xref>) presented a low risk of bias in reporting blinding of participants. The studies did not describe blinding of outcome assessors and were thus judged as a high risk of bias. Twenty-one studies exhibited a low risk of attrition bias with complete outcome data. In terms of selective reporting bias, 19 trials (<xref ref-type="bibr" rid="B4">Cai, 2016</xref>; <xref ref-type="bibr" rid="B9">Cui, 2022</xref>; <xref ref-type="bibr" rid="B15">Du, 2016</xref>; <xref ref-type="bibr" rid="B29">Hou et al., 2015</xref>; <xref ref-type="bibr" rid="B30">Hu, 2012</xref>; <xref ref-type="bibr" rid="B42">Li et al., 2019</xref>; <xref ref-type="bibr" rid="B47">Liu, 2012</xref>; <xref ref-type="bibr" rid="B63">Peng, 2015</xref>; <xref ref-type="bibr" rid="B71">Song, 2011</xref>; <xref ref-type="bibr" rid="B72">Song, 2019</xref>; <xref ref-type="bibr" rid="B76">Tan, 2019</xref>; <xref ref-type="bibr" rid="B77">Tao, 2021</xref>; <xref ref-type="bibr" rid="B82">Wang and Wang, 2012</xref>; <xref ref-type="bibr" rid="B83">Wang et al., 2012</xref>; <xref ref-type="bibr" rid="B81">Wang and Sun, 2018</xref>; <xref ref-type="bibr" rid="B90">Yang and Zhou, 2002</xref>; <xref ref-type="bibr" rid="B96">Zhang, 2013</xref>; <xref ref-type="bibr" rid="B99">Zhao, 2022</xref>; <xref ref-type="bibr" rid="B100">Zhu et al., 2019</xref>) provided a low risk of bias and included all the outcomes specified in the methods section, while two trials (<xref ref-type="bibr" rid="B36">Jin and Wu, 2006</xref>; <xref ref-type="bibr" rid="B95">Yuan, 2018</xref>) showed a high risk of bias. We regarded all included studies as having a low risk of bias because we were unable to find any further sources of bias in any of them.</p>
<fig id="F2" position="float">
<label>FIGURE 2</label>
<caption>
<p>Risk of bias graph <bold>(a)</bold> and bias summary <bold>(b)</bold>. Note: <xref ref-type="bibr" rid="B82">Wang and Wang, 2012</xref>; <xref ref-type="bibr" rid="B83">Wang et al., 2012</xref>.</p>
</caption>
<graphic xlink:href="fphar-16-1506234-g002.tif">
<alt-text content-type="machine-generated">Bar chart (a) and matrix chart (b) assessing bias risks in studies. Bar chart shows proportions of bias risks: low (green), unclear (yellow), and high (red). Matrix chart displays bias risk assessments across studies by categories such as selection, performance, and detection biases.</alt-text>
</graphic>
</fig>
</sec>
<sec id="s3-4">
<title>3.4 Description of TCM</title>
<p>In this study, sixteen TCM formulations were included, including Danxiong Tongluo decoction (<italic>Salvia miltiorrhiza</italic> Bunge (Danshen), <italic>Pueraria montana</italic> var. <italic>lobata</italic> (Willd.) Maesen &#x26; S.M.Almeida ex Sanjappa &#x26; Predeep (Gegen), <italic>Crataegus monogyna</italic> Jacq. (Shanzha), <italic>Typha angustifolia</italic> L. (Puhuang), <italic>Oreocome striata</italic> (DC.) Pimenov &#x26; Kljuykov (Chuanxiong), <italic>Xanthium strumarium</italic> L. (Gualoupi), <italic>Allium chinense</italic> G.Don (Xiebai), and <italic>Pinellia ternata</italic> (Thunb.) Makino (Banxia)), Tongqiao Huoxue decoction (<italic>O. striata</italic> (DC.) Pimenov &#x26; Kljuykov (Chuanxiong), <italic>Carthamus tinctorius</italic> L. (Honghua), <italic>S. miltiorrhiza</italic> Bunge (Danshen), <italic>Paeonia lactiflora</italic> Pall. (Chishao), <italic>Juglans regia</italic> L. (Taoren), <italic>P. montana</italic> var. <italic>lobata</italic> (Willd.) Maesen &#x26; S.M.Almeida ex Sanjappa &#x26; Predeep (Gegen), <italic>Typha angustifolia</italic> L. (Puhuang), <italic>Astragalus mongholicus</italic> Bunge (Huangqi), and <italic>Codonopsis pilosula</italic> (Franch.) Nannf. (Dangshen)), Wenxin granule (<italic>C. pilosula</italic> (Franch.) Nannf. (Dangshen), <italic>Vitex negundo</italic> L. (Huangjing), <italic>Basella alba</italic> L. (Sanqi), <italic>Cannabis sativa</italic> L. (Hupo), and <italic>Nardostachys jatamansi</italic> (D.Don) DC. (Gansong)), Danshen Dropping pill (<italic>S. miltiorrhiza</italic> Bunge (Danshen), <italic>B. alba</italic> L. (Sanqi), and <italic>Camphora officinarum</italic> Nees (Bingpian)), Tianma Gouteng Yin formula (<italic>Gastrodia elata</italic> Blume (Tianma), <italic>Uncaria rhynchophylla</italic> (Miq.) Miq. (Gouteng), <italic>Prosthechea radiata</italic> (Lindl.) W.E.Higgins (Shijueming), <italic>Scutellaria baicalensis</italic> Georgi (Huangqin), <italic>Eucommia ulmoides</italic> Oliv. (Duzhong), <italic>Taxillus chinensis</italic> (DC.) Danser (Sangjisheng), <italic>Panax quinquefolius</italic> L. (Xiyangshen), <italic>Ziziphus jujuba</italic> Mill. (Suanzaoren), <italic>Panax ginseng</italic> C.A.Mey. (Fushen), <italic>S. miltiorrhiza</italic> Bunge (Danshen), and <italic>Achyranthes bidentata</italic> Blume (Niuxi)), Shexiang Baoxin pill (<italic>Liquidambar orientalis</italic> Mill. (Shexiang), <italic>P. ginseng</italic> C.A.Mey. (Renshen), <italic>P. ginseng</italic> C.A.Mey. (Niuhuang), <italic>Neolitsea cassia</italic> (L.). Kosterm. (Rougui), <italic>L. orientalis</italic> Mill. (Suhexiang), <italic>Tagetes erecta</italic> L. (Chansu), and <italic>C. officinarum</italic> Nees (Bingpian)), Shengmai Yin (<italic>P. ginseng</italic> C.A.Mey. (Renshen), <italic>Rehmannia glutinosa</italic> (Gaertn.) DC. (Shudihuang), <italic>Ophiopogon japonicus</italic> (Thunb.) Ker Gawl. (Maidong), <italic>Atractylodes macrocephala</italic> Koidz. (Baizhu), <italic>Schisandra chinensis</italic> (Turcz.) Baill. (Wuweizi), <italic>A. mongholicus</italic> Bunge (Huangqi), <italic>S. miltiorrhiza</italic> Bunge (Danshen), and <italic>Smilax glabra</italic> Roxb. (Fuling)), Diju Pinggan capsule (Without reporting each botanical drug and dosage), and others. The botanical drug names have been checked with <ext-link ext-link-type="uri" xlink:href="http://mpns.kew.org">http://mpns.kew.org</ext-link> and <ext-link ext-link-type="uri" xlink:href="http://www.worldfloraonline.org">http://www.worldfloraonline.org</ext-link> on 30 April 2024. The species involved have been taxonomically validated by searching their Latin names in the electronic version of Flora of China (<ext-link ext-link-type="uri" xlink:href="http://www.efloras.org">http://www.efloras.org</ext-link>) to obtain descriptions of their morphological characteristics, type specimen information, and taxonomic status. Additionally, the original images of the type specimens of the species can be consulted through the International Plant Names Index (IPNI, <ext-link ext-link-type="uri" xlink:href="https://www.ipni.org">https://www.ipni.org</ext-link>) or herbarium databases such as the Herbarium of the Institute of Botany, Chinese Academy of Sciences (PE, <ext-link ext-link-type="uri" xlink:href="http://pe.ibcas.ac.cn/">http://pe.ibcas.ac.cn</ext-link>). TCM formula Danxiong Tongluo decoction was the most commonly utilized (4/16, 25.00%), followed by Tongqiao Huoxue decoction (3/16, 18.75%).</p>
<p>Each Chinese botanical drug&#x2019;s frequency in this review was described using a manual summary. There were 72 Chinese botanical drugs in all. The top five ranked Chinese botanical drugs were <italic>S. miltiorrhiza</italic> Bunge (Danshen) (16/72, 22.22%), <italic>O. striata</italic> (DC.) Pimenov &#x26; Kljuykov (Chuanxiong) (11/72, 15.28%), <italic>P. montana</italic> var. <italic>lobata</italic> (Willd.) Maesen &#x26; S.M.Almeida ex Sanjappa &#x26; Predeep (Gegen) (7/72, 9.72%), <italic>A. mongholicus</italic> Bunge (Huangqi) (7/72, 9.72%), and <italic>Typha angustifolia</italic> L. (Puhuang) (7/72, 9.72%). The provided formulations contained three to 14 Chinese botanical drugs. Among these formulas, Diju Pinggan capsule (batch number: 100,605) was provided by the pharmaceutical preparation room in Shanxi Academy of TCM without reporting each botanical drug and dosage.</p>
<p>Four dosage formulations of TCM reported, including decoction, pill, capsule, and granule, were all administered orally. The decoction was the most commonly used dosage formulation (17/21, 80.95%), followed by pill (2/21, 9.52%), granule (1/21, 4.76%), and capsule (1/21, 4.76%). The decoction was orally taken one dose every day. The TCM formulas and the specific botanical drugs are summarized concretely in <xref ref-type="table" rid="T2">Table 2</xref>.</p>
<table-wrap id="T2" position="float">
<label>TABLE 2</label>
<caption>
<p>The botanical drugs of TCM used in the included studies.</p>
</caption>
<table>
<thead valign="top">
<tr>
<th align="left">References</th>
<th align="left">Name of TCM</th>
<th align="left">The botanical drugs of TCM</th>
</tr>
</thead>
<tbody valign="top">
<tr>
<td align="left">
<xref ref-type="bibr" rid="B4">Cai (2016)</xref>
</td>
<td align="left">Danxiong Tongluo decoction</td>
<td align="left">
<italic>Salvia miltiorrhiza</italic> Bunge (Danshen) 30&#xa0;g, <italic>Pueraria montana</italic> var. <italic>lobata</italic> (Willd.) Maesen &#x26; S.M.Almeida ex Sanjappa &#x26; Predeep (Gegen) 30&#xa0;g, <italic>Crataegus monogyna</italic> Jacq. (Shanzha) 15&#xa0;g, <italic>Typha angustifolia</italic> L. (Puhuang) 15&#xa0;g, <italic>Oreocome striata</italic> (DC.) Pimenov &#x26; Kljuykov (Chuanxiong) 10&#xa0;g, <italic>Xanthium strumarium</italic> L. (Gualoupi) 10&#xa0;g, <italic>Allium chinense</italic> G.Don (Xiebai) 10&#xa0;g, and <italic>Pinellia ternata</italic> (Thunb.) Makino (Banxia)10&#xa0;g</td>
</tr>
<tr>
<td align="left">
<xref ref-type="bibr" rid="B9">Cui (2022)</xref>
</td>
<td align="left">Wenxin granule (Z10950026)</td>
<td align="left">Chinese patent medicine: <italic>Codonopsis pilosula</italic> (Franch.) Nannf. (Dangshen), <italic>Vitex negundo</italic> L. (Huangjing), <italic>Basella alba</italic> L. (Sanqi), <italic>Cannabis sativa</italic> L. (Hupo), and <italic>Nardostachys jatamansi</italic> (D.Don) DC. (Gansong). <font color="#EE0000">9&#xa0;g three times a day</font>
</td>
</tr>
<tr>
<td align="left">
<xref ref-type="bibr" rid="B15">Du (2016)</xref>
</td>
<td align="left">Danshen Dropping pill (Z10950111)</td>
<td align="left">Chinese patent medicine: <italic>Salvia miltiorrhiza</italic> Bunge (Danshen), <italic>Basella alba</italic> L. (Sanqi), and <italic>Camphora officinarum</italic> Nees (Bingpian). 270&#xa0;mg three times a day</td>
</tr>
<tr>
<td align="left">
<xref ref-type="bibr" rid="B29">Hou et al. (2015)</xref>
</td>
<td align="left">TCM decoction</td>
<td align="left">
<italic>Gastrodia elata</italic> Blume (Tianma) 15&#xa0;g, <italic>Oreocome striata</italic> (DC.) Pimenov &#x26; Kljuykov (Chuanxiong) 15&#xa0;g, <italic>Uncaria rhynchophylla</italic> (Miq.) Miq. (Gouteng) 15&#xa0;g, <italic>Salvia miltiorrhiza</italic> Bunge (Danshen) 15&#xa0;g, <italic>Achyranthes bidentata</italic> Blume (Niuxi) 15&#xa0;g, <italic>Taxillus chinensis</italic> (DC.) Danser (Sangjisheng) 9&#xa0;g, <italic>Plantago asiatica</italic> L. (Cheqianzi) 9&#xa0;g, <italic>Epimedium sagittatum</italic> (Siebold &#x26; Zucc.) Maxim. (Yinyanghuo) 9&#xa0;g, <italic>Ligustrum lucidum</italic> W.T.Aiton (Nvzhenzi) 9&#xa0;g, and <italic>Glycyrrhiza glabra</italic> L. (Gancao) 9&#xa0;g</td>
</tr>
<tr>
<td align="left">
<xref ref-type="bibr" rid="B30">Hu (2012)</xref>
</td>
<td align="left">TCM decoction</td>
<td align="left">
<italic>Neolitsea cassia</italic> (L.) Kosterm. (Guizhi) 15&#xa0;g, <italic>Panax ginseng</italic> C.A.Mey. (Renshen) 9&#xa0;g, <italic>Ophiopogon japonicus</italic> (Thunb.) Ker Gawl. (Maidong) 12&#xa0;g, <italic>Lycium barbarum</italic> L. (Gouqizi) 12&#xa0;g, <italic>Rehmannia glutinosa</italic> (Gaertn.) DC. (Shudihuang) 12&#xa0;g, <italic>Angelica sinensis</italic> (Oliv.) Diels (Danggui) 12&#xa0;g, <italic>Ziziphus jujuba</italic> Mill. (Suanzaoren) 15&#xa0;g, <italic>Polygala tenuifolia</italic> Willd. (Yuanzhi) 12&#xa0;g, <italic>Juglans regia</italic> L. (Taoren) 12&#xa0;g, and <italic>Oreocome striata</italic> (DC.) Pimenov &#x26; Kljuykov (Chuanxiong) 12&#xa0;g</td>
</tr>
<tr>
<td align="left">
<xref ref-type="bibr" rid="B36">Jin and Wu (2006)</xref>
</td>
<td align="left">Tianma Gouteng Yin formula</td>
<td align="left">
<italic>Gastrodia elata</italic> Blume (Tianma) 10&#xa0;g, <italic>Uncaria rhynchophylla</italic> (Miq.) Miq. (Gouteng) 20&#xa0;g, <italic>Prosthechea radiata</italic> (Lindl.) W.E.Higgins (Shijueming) 15&#xa0;g, <italic>Scutellaria baicalensis</italic> Georgi (Huangqin) 10&#xa0;g, <italic>Eucommia ulmoides</italic> Oliv. (Duzhong) 15&#xa0;g, <italic>Taxillus chinensis</italic> (DC.) Danser (Sangjisheng) 15&#xa0;g, <italic>Panax quinquefolius</italic> L. (Xiyangshen) 6&#xa0;g, <italic>Ziziphus jujuba</italic> Mill. (Suanzaoren) 20&#xa0;g, <italic>Panax ginseng</italic> C.A.Mey. (Fushen) 10&#xa0;g, <italic>Salvia miltiorrhiza</italic> Bunge (Danshen) 15&#xa0;g, and <italic>Achyranthes bidentata</italic> Blume (Niuxi) 10&#xa0;g</td>
</tr>
<tr>
<td align="left">
<xref ref-type="bibr" rid="B42">Li et al. (2019)</xref>
</td>
<td align="left">Danxiong Tongluo decoction</td>
<td align="left">
<italic>Salvia miltiorrhiza</italic> Bunge (Danshen) 30&#xa0;g, <italic>Pueraria montana</italic> var. <italic>lobata</italic> (Willd.) Maesen &#x26; S.M.Almeida ex Sanjappa &#x26; Predeep (Gegen) 30&#xa0;g, <italic>Oreocome striata</italic> (DC.) Pimenov &#x26; Kljuykov (Chuanxiong) 15&#xa0;g, <italic>Typha angustifolia</italic> L. (Puhuang) 15&#xa0;g, <italic>Citrus &#xd7; aurantium f. aurantium</italic> (Zhishi) 15&#xa0;g, <italic>Crataegus monogyna</italic> Jacq. (Shanzha) 15&#xa0;g, <italic>Basella alba</italic> L. (Sanqi) 15&#xa0;g, <italic>Pinellia ternata</italic> (Thunb.) Makino (Banxia) 10&#xa0;g, <italic>Allium chinense</italic> G.Don (Xiebai) 10&#xa0;g, <italic>Xanthium strumarium</italic> L. (Gualoupi) 10&#xa0;g, and <italic>Juglans regia</italic> L. (Taoren) 10&#xa0;g</td>
</tr>
<tr>
<td align="left">
<xref ref-type="bibr" rid="B47">Liu (2012)</xref>
</td>
<td align="left">TCM decoction</td>
<td align="left">
<italic>Gastrodia elata</italic> Blume (Tianma) 15&#xa0;g, <italic>Uncaria rhynchophylla</italic> (Miq.) Miq. (Gouteng) 15&#xa0;g, <italic>Taxillus chinensis</italic> (DC.) Danser (Sangjisheng) 12&#xa0;g, <italic>Ligustrum lucidum</italic> W.T.Aiton (Nvzhenzi) 12&#xa0;g, <italic>Epimedium sagittatum</italic> (Siebold &#x26; Zucc.) Maxim. (Yinyanghuo) 12&#xa0;g, <italic>Achyranthes bidentata</italic> Blume (Niuxi) 15&#xa0;g, <italic>Salvia miltiorrhiza</italic> Bunge (Danshen) 15&#xa0;g, <italic>Oreocome striata</italic> (DC.) Pimenov &#x26; Kljuykov (Chuanxiong) 15&#xa0;g, <italic>Lathyrus sativus</italic> L. (Guijia) 9&#xa0;g, <italic>Plantago asiatica</italic> L. (Cheqianzi) 12&#xa0;g, and <italic>Glycyrrhiza glabra</italic> L. (Gancao) 9&#xa0;g</td>
</tr>
<tr>
<td align="left">
<xref ref-type="bibr" rid="B63">Peng (2015)</xref>
</td>
<td align="left">Shexiang Baoxin pill<font color="#EE0000">
</font>(Z31020068)</td>
<td align="left">Chinese patent medicine: <italic>Liquidambar orientalis</italic> Mill. (Shexiang), <italic>Panax ginseng</italic> C.A.Mey. (Renshen), <italic>Panax ginseng</italic> C.A.Mey. (Niuhuang), <italic>Neolitsea cassia</italic> (L.) Kosterm. (Rougui), <italic>Liquidambar orientalis</italic> Mill. (Suhexiang), <italic>Tagetes erecta</italic> L. (Chansu), and <italic>Camphora officinarum</italic> Nees (Bingpian). 45&#xa0;mg three times a day</td>
</tr>
<tr>
<td align="left">
<xref ref-type="bibr" rid="B71">Song (2011)</xref>
</td>
<td align="left">Yuyin Qianyang decoction</td>
<td align="left">
<italic>Uncaria rhynchophylla</italic> (Miq.) Miq. (Gouteng) 9&#xa0;g, <italic>Senna tora</italic> (L.) Roxb. (Juemingzi) 30&#xa0;g, <italic>Prosthechea radiata</italic> (Lindl.) W.E.Higgins (Shijueming) 30&#xa0;g, <italic>Cannabis sativa</italic> L. (Muli) 30&#xa0;g, <italic>Zanthoxylum asiaticum</italic> (L.) Appelhans, Groppo &#x26; J.Wen (Dilong) 9&#xa0;g, <italic>Xanthium strumarium</italic> L. (Gualoupi) 15&#xa0;g, <italic>Pinellia ternata</italic> (Thunb.) Makino (Banxia) 9&#xa0;g, <italic>Citrus reticulata</italic> Blanco (Chenpi) 12&#xa0;g, <italic>Smilax glabra</italic> Roxb. (Fuling) 15&#xa0;g, <italic>Salvia miltiorrhiza</italic> Bunge (Danshen) 15&#xa0;g, <italic>Oreocome striata</italic> (DC.) Pimenov &#x26; Kljuykov (Chuanxiong) 9&#xa0;g, <italic>Carthamus tinctorius</italic> L. (Honghua) 6&#xa0;g, <italic>Rehmannia glutinosa</italic> (Gaertn.) DC. (Dihuang) 12&#xa0;g, and <italic>Paeonia lactiflora</italic> Pall. (Baishaoyao) 12&#xa0;g</td>
</tr>
<tr>
<td align="left">
<xref ref-type="bibr" rid="B72">Song (2019)</xref>
</td>
<td align="left">TCM decoction</td>
<td align="left">
<italic>Angelica sinensis</italic> (Oliv.) Diels (Danggui) 30&#xa0;g, <italic>Scutellaria baicalensis</italic> Georgi (Huangqin) 30&#xa0;g, <italic>Salvia miltiorrhiza</italic> Bunge (Danshen) 15&#xa0;g, <italic>Gastrodia elata</italic> Blume (Tianma) 15&#xa0;g, <italic>Epimedium sagittatum</italic> (Siebold &#x26; Zucc.) Maxim. (Yinyanghuo) 12&#xa0;g, <italic>Paeonia lactiflora</italic> Pall. (Baishaoyao) 12&#xa0;g, <italic>Lathyrus sativus</italic> L. (Guijia) 9&#xa0;g, <italic>Achyranthes bidentata</italic> Blume (Niuxi) 6&#xa0;g, <italic>Panax ginseng</italic> C.A.Mey. (Renshen) 6&#xa0;g, and <italic>Asarum heterotropoides</italic> F.Schmidt (Xixin) 5&#xa0;g</td>
</tr>
<tr>
<td align="left">
<xref ref-type="bibr" rid="B76">Tan (2019)</xref>
</td>
<td align="left">Tongqiao Huoxue decoction</td>
<td align="left">
<italic>Oreocome striata</italic> (DC.) Pimenov &#x26; Kljuykov (Chuanxiong) 10&#xa0;g, <italic>Carthamus tinctorius</italic> L. (Honghua) 9&#xa0;g, <italic>Salvia miltiorrhiza</italic> Bunge (Danshen) 10&#xa0;g, <italic>Paeonia lactiflora</italic> Pall. (Chishao) 10&#xa0;g, <italic>Juglans regia</italic> L. (Taoren) 9&#xa0;g, <italic>Pueraria montana</italic> var. <italic>lobata</italic> (Willd.) Maesen &#x26; S.M.Almeida ex Sanjappa &#x26; Predeep (Gegen) 10&#xa0;g, <italic>Typha angustifolia</italic> L. (Puhuang) 10&#xa0;g, <italic>Astragalus mongholicus</italic> Bunge (Huangqi) 20&#xa0;g, and <italic>Codonopsis pilosula</italic> (Franch.) Nannf. (Dangshen) 15&#xa0;g</td>
</tr>
<tr>
<td align="left">
<xref ref-type="bibr" rid="B77">Tao (2021)</xref>
</td>
<td align="left">TCM decoction</td>
<td align="left">
<italic>Glycyrrhiza glabra</italic> L. (Gancao) 6&#xa0;g, <italic>Pinellia ternata</italic> (Thunb.) Makino (Banxia) 6&#xa0;g, <italic>Atractylodes macrocephala</italic> Koidz. (Baizhu) 9&#xa0;g, <italic>Gastrodia elata</italic> Blume (Tianma) 9&#xa0;g, <italic>Smilax glabra</italic> Roxb. (Fuling) 12&#xa0;g, <italic>Arisaema erubescens</italic> (Wall.) Schott (Dannanxing) 12&#xa0;g, <italic>Citrus reticulata</italic> Blanco (Chenpi) 12&#xa0;g, and Citrus &#xd7; aurantium L. (Zhike) 12&#xa0;g</td>
</tr>
<tr>
<td align="left">
<xref ref-type="bibr" rid="B82">Wang and Wang (2012)</xref>
</td>
<td align="left">Shengmai Yin</td>
<td align="left">
<italic>Panax ginseng</italic> C.A.Mey. (Renshen) 15&#x2013;20&#xa0;g, <italic>Rehmannia glutinosa</italic> (Gaertn.) DC. (Shudihuang) 20&#xa0;g, <italic>Ophiopogon japonicus</italic> (Thunb.) Ker Gawl. (Maidong) 15&#xa0;g, <italic>Atractylodes macrocephala</italic> Koidz. (Baizhu) 15&#xa0;g, <italic>Schisandra chinensis</italic> (Turcz.) Baill. (Wuweizi) 10&#xa0;g, <italic>Astragalus mongholicus</italic> Bunge (Huangqi) 30&#xa0;g, <italic>Salvia miltiorrhiza</italic> Bunge (Danshen) 30&#xa0;g, and <italic>Smilax glabra</italic> Roxb. (Fuling) 30&#xa0;g</td>
</tr>
<tr>
<td align="left">
<xref ref-type="bibr" rid="B83">Wang et al. (2012)</xref>
</td>
<td align="left">Diju Pinggan capsule</td>
<td align="left">Diju Pinggan capsule (batch number: 100,605) was provided by the pharmaceutical preparation room in Shanxi Academy of Traditional Chinese Medicine without reporting each botanical drug and dosage. 1.5&#xa0;g three times a day</td>
</tr>
<tr>
<td align="left">
<xref ref-type="bibr" rid="B81">Wang and Sun (2018)</xref>
</td>
<td align="left">Tongqiao Huoxue decoction</td>
<td align="left">
<italic>Paeonia lactiflora</italic> Pall. (Chishao) 10&#xa0;g, <italic>Oreocome striata</italic> (DC.) Pimenov &#x26; Kljuykov (Chuanxiong) 10&#xa0;g, <italic>Juglans regia</italic> L. (Taoren) 9&#xa0;g, <italic>Ziziphus jujuba</italic> Mill. (Dazao) 7, <italic>Carthamus tinctorius</italic> L. (Honghua) 9&#xa0;g, <italic>Andrographis paniculata</italic> (Burm.f.) Wall. ex Nees (Cong) 3, <italic>Zingiber officinale</italic> Roscoe (Shengjiang) 9&#xa0;g, <italic>Liquidambar orientalis</italic> Mill. (Shexiang) 0.15 g, <italic>Salvia miltiorrhiza</italic> Bunge (Danshen) 10&#xa0;g, <italic>Pueraria montana</italic> var. <italic>lobata</italic> (Willd.) Maesen &#x26; S.M.Almeida ex Sanjappa &#x26; Predeep (Gegen) 10&#xa0;g, <italic>Typha angustifolia</italic> L. (Puhuang) 10&#xa0;g, <italic>Astragalus mongholicus</italic> Bunge (Huangqi) 20&#xa0;g, and <italic>Codonopsis pilosula</italic> (Franch.) Nannf. (Dangshen) 15&#xa0;g</td>
</tr>
<tr>
<td align="left">
<xref ref-type="bibr" rid="B90">Yang and Zhou (2002)</xref>
</td>
<td align="left">Danxiong Tongluo decoction</td>
<td align="left">
<italic>Salvia miltiorrhiza</italic> Bunge (Danshen) 30&#xa0;g, <italic>Oreocome striata</italic> (DC.) Pimenov &#x26; Kljuykov (Chuanxiong) 10&#xa0;g, <italic>Pueraria montana</italic> var. <italic>lobata</italic> (Willd.) Maesen &#x26; S.M.Almeida ex Sanjappa &#x26; Predeep (Gegen) 30&#xa0;g, <italic>Typha angustifolia</italic> L. (Puhuang) 15&#xa0;g, <italic>Xanthium strumarium</italic> L. (Gualoupi) 10&#xa0;g, <italic>Allium chinense</italic> G.Don (Xiebai) 10&#xa0;g, <italic>Pinellia ternata</italic> (Thunb.) Makino (Banxia) 10&#xa0;g, and <italic>Crataegus monogyna</italic> Jacq. (Shanzha) 15&#xa0;g</td>
</tr>
<tr>
<td align="left">
<xref ref-type="bibr" rid="B95">Yuan (2018)</xref>
</td>
<td align="left">Danxiong Tongluo decoction</td>
<td align="left">
<italic>Xanthium strumarium</italic> L. (Gualoupi) 9&#xa0;g, <italic>Pinellia ternata</italic> (Thunb.) Makino (Banxia) 9&#xa0;g, <italic>Oreocome striata</italic> (DC.) Pimenov &#x26; Kljuykov (Chuanxiong) 10&#xa0;g, <italic>Allium chinense</italic> G.Don (Xiebai) 11&#xa0;g, <italic>Crataegus monogyna</italic> Jacq. (Shanzha) 14&#xa0;g, <italic>Typha angustifolia</italic> L. (Puhuang) 14&#xa0;g, <italic>Pueraria montana</italic> var. <italic>lobata</italic> (Willd.) Maesen &#x26; S.M.Almeida ex Sanjappa &#x26; Predeep (Gegen) 28&#xa0;g, and <italic>Salvia miltiorrhiza</italic> Bunge (Danshen) 28&#xa0;g</td>
</tr>
<tr>
<td align="left">
<xref ref-type="bibr" rid="B96">Zhang (2013)</xref>
</td>
<td align="left">TCM decoction</td>
<td align="left">
<italic>Panax ginseng</italic> C.A.Mey. (Renshen) 6&#xa0;g, <italic>Astragalus mongholicus</italic> Bunge (Huangqi) 30&#xa0;g, <italic>Angelica sinensis</italic> (Oliv.) Diels (Danggui) 30&#xa0;g, <italic>Asarum heterotropoides</italic> F.Schmidt (Xixin) 5&#xa0;g, <italic>Salvia miltiorrhiza</italic> Bunge (Danshen) 15&#xa0;g, <italic>Gastrodia elata</italic> Blume (Tianma) 15&#xa0;g, <italic>Paeonia lactiflora</italic> Pall. (Baishaoyao) 12&#xa0;g, <italic>Achyranthes bidentata</italic> Blume (Niuxi) 6&#xa0;g, <italic>Epimedium sagittatum</italic> (Siebold &#x26; Zucc.) Maxim. (Yinyanghuo) 12&#xa0;g, and <italic>Lathyrus sativus</italic> L. (Guijia) 9&#xa0;g</td>
</tr>
<tr>
<td align="left">
<xref ref-type="bibr" rid="B99">Zhao (2022)</xref>
</td>
<td align="left">Tongqiao Huoxue decoction</td>
<td align="left">
<italic>Codonopsis pilosula</italic> (Franch.) Nannf. (Dangshen) 15&#xa0;g, <italic>Astragalus mongholicus</italic> Bunge (Huangqi) 20&#xa0;g, <italic>Pueraria montana</italic> var. <italic>lobata</italic> (Willd.) Maesen &#x26; S.M.Almeida ex Sanjappa &#x26; Predeep (Gegen) 10&#xa0;g, <italic>Typha angustifolia</italic> L. (Puhuang) 10&#xa0;g, <italic>Salvia miltiorrhiza</italic> Bunge (Danshen) 10&#xa0;g, <italic>Paeonia lactiflora</italic> Pall. (Chishao) 10&#xa0;g, <italic>Oreocome striata</italic> (DC.) Pimenov &#x26; Kljuykov (Chuanxiong) 10&#xa0;g, <italic>Juglans regia</italic> L. (Taoren) 9&#xa0;g, <italic>Carthamus tinctorius</italic> L. (Honghua) 9&#xa0;g, <italic>Zingiber officinale</italic> Roscoe (Shengjiang) 9&#xa0;g, <italic>Liquidambar orientalis</italic> Mill. (Shexiang) 0.15 g, <italic>Andrographis paniculata</italic> (Burm.f.) Wall. ex Nees (Cong) 3, and <italic>Ziziphus jujuba</italic> Mill. (Dazao) 7</td>
</tr>
<tr>
<td align="left">
<xref ref-type="bibr" rid="B100">Zhu et al. (2019)</xref>
</td>
<td align="left">Yiqi Wenyang Tongluo decoction</td>
<td align="left">
<italic>Astragalus mongholicus</italic> Bunge (Huangqi) 30&#xa0;g, <italic>Panax ginseng</italic> C.A.Mey. (Hongshen) 15&#xa0;g, <italic>Cyperus rotundus</italic> L. (Fuzi) 12&#xa0;g, <italic>Neolitsea cassia</italic> (L.) Kosterm. (Guizhi) 10&#xa0;g, <italic>Carthamus tinctorius</italic> L. (Honghua) 12&#xa0;g, <italic>Terminalia chebula</italic> Retz. (Shuizhi) 5&#xa0;g, <italic>Salvia miltiorrhiza</italic> Bunge (Danshen) 30&#xa0;g, <italic>Descurainia sophia</italic> (L.) Webb ex Prantl (Tinglizi) 15&#xa0;g, and <italic>Eleutherococcus senticosus</italic> (Rupr. &#x26; Maxim.) Maxim. (Wujiapi) 12&#xa0;g</td>
</tr>
</tbody>
</table>
</table-wrap>
</sec>
<sec id="s3-5">
<title>3.5 Primary outcomes</title>
<sec id="s3-5-1">
<title>3.5.1 BP</title>
<p>In total, six RCTs (<xref ref-type="bibr" rid="B4">Cai, 2016</xref>; <xref ref-type="bibr" rid="B63">Peng, 2015</xref>; <xref ref-type="bibr" rid="B76">Tan, 2019</xref>; <xref ref-type="bibr" rid="B81">Wang and Sun, 2018</xref>; <xref ref-type="bibr" rid="B90">Yang and Zhou, 2002</xref>; <xref ref-type="bibr" rid="B95">Yuan, 2018</xref>) reported the effect of TCM on BP. The results of the meta-analysis indicated that SBP was lower in the TCM group as compared to the control group (MD &#x3d; &#x2212;5.69; 95% CI: 10.79 to &#x2212;0.59; P &#x3d; 0.03), although the random-effects model exhibited statistical heterogeneity (&#x3c7;<sup>2</sup> &#x3d; 88.70; I<sup>2</sup> &#x3d; 94%; P &#x3c; 0.00001) (<xref ref-type="fig" rid="F3">Figure 3a</xref>). Sensitivity analyses were performed to evaluate the robustness of the results. Thus, we repeated the meta-analysis after excluding, one by one, four studies (<xref ref-type="bibr" rid="B4">Cai, 2016</xref>; <xref ref-type="bibr" rid="B63">Peng, 2015</xref>; <xref ref-type="bibr" rid="B76">Tan, 2019</xref>; <xref ref-type="bibr" rid="B95">Yuan, 2018</xref>), P &#x3e; 0.05 suggested nonsignificant difference and the unreliability of the result of SBP. In addition, another meta-analysis showed the efficacy of TCM on DBP (MD &#x3d; &#x2212;5.88; 95% CI: 10.98 to &#x2212;0.77; P &#x3d; 0.02), and also represented statistical heterogeneity (&#x3c7;<sup>2</sup> &#x3d; 83.31; I<sup>2</sup> &#x3d; 94%; P &#x3c; 0.00001) with the random-effects model (<xref ref-type="fig" rid="F3">Figure 3b</xref>). The pooled effect estimates showed no significant difference for DBP after excluding Cai&#x2019;s, Peng&#x2019;s, and Tan&#x2019;s studies (<xref ref-type="bibr" rid="B4">Cai, 2016</xref>; <xref ref-type="bibr" rid="B63">Peng, 2015</xref>; <xref ref-type="bibr" rid="B76">Tan, 2019</xref>) one by one, which suggested that the result was not robust.</p>
<fig id="F3" position="float">
<label>FIGURE 3</label>
<caption>
<p>Forest plots for the meta-analysis of BP in the TCM group vs. the control group: <bold>(a)</bold> SBP and <bold>(b)</bold> DBP. Abbreviation: BP: blood pressure; DBP: diastolic blood pressure; SBP: systolic blood pressure; TCM: traditional Chinese medicine.</p>
</caption>
<graphic xlink:href="fphar-16-1506234-g003.tif">
<alt-text content-type="machine-generated">Forest plots depict comparisons of traditional Chinese medicine (TCM) versus control for systolic (a) and diastolic blood pressure (b). Each plot shows study names, sample sizes, means, standard deviations, weights, and mean differences with 95% confidence intervals. Both plots favor TCM with significant heterogeneity, indicated by substantial p-values and I-squared statistics.</alt-text>
</graphic>
</fig>
</sec>
<sec id="s3-5-2">
<title>3.5.2 NYHA classification</title>
<p>In total, eleven RCTs (<xref ref-type="bibr" rid="B4">Cai, 2016</xref>; <xref ref-type="bibr" rid="B30">Hu, 2012</xref>; <xref ref-type="bibr" rid="B42">Li et al., 2019</xref>; <xref ref-type="bibr" rid="B63">Peng, 2015</xref>; <xref ref-type="bibr" rid="B71">Song, 2011</xref>; <xref ref-type="bibr" rid="B76">Tan, 2019</xref>; <xref ref-type="bibr" rid="B82">Wang and Wang, 2012</xref>; <xref ref-type="bibr" rid="B83">Wang et al., 2012</xref>; <xref ref-type="bibr" rid="B81">Wang and Sun, 2018</xref>; <xref ref-type="bibr" rid="B90">Yang and Zhou, 2002</xref>; <xref ref-type="bibr" rid="B99">Zhao, 2022</xref>) reported the effect of TCM on NYHA classification. A meta-analysis revealed that the TCM group&#x2019;s NYHA classification was substantially better than that of the control group (RR &#x3d; 1.25; 95% CI: 1.18 to 1.33; P &#x3c; 0.00001). There was moderate heterogeneity (&#x3c7;<sup>2</sup> &#x3d; 14.80; I<sup>2</sup> &#x3d; 32%; P &#x3d; 0.14) and the fixed-effects model was used (<xref ref-type="fig" rid="F4">Figure 4</xref>). Sensitivity analyses indicated that the I<sup>2</sup> dropped to 0% (P &#x3c; 0.00001) by excluding Wang&#x2019;s study (<xref ref-type="bibr" rid="B82">Wang and Wang, 2012</xref>), which might significantly impact the effect value and be the primary cause of heterogeneity.</p>
<fig id="F4" position="float">
<label>FIGURE 4</label>
<caption>
<p>Forest plot for the meta-analysis of NYHA classification. Abbreviation: NYHA: New York Heart Association; TCM: traditional Chinese medicine. Note: Wang 2012a: <xref ref-type="bibr" rid="B82">Wang and Wang, 2012</xref>; Wang 2012b: <xref ref-type="bibr" rid="B83">Wang et al., 2012</xref>.</p>
</caption>
<graphic xlink:href="fphar-16-1506234-g004.tif">
<alt-text content-type="machine-generated">Forest plot showing a meta-analysis of eleven studies comparing TCM and control groups. The plot displays risk ratios with confidence intervals, weights, and totals for each study. The overall risk ratio is 1.25, favoring TCM, with statistical significance indicated by Z = 7.28 (P &#x3C; 0.00001). Heterogeneity statistics are reported with Chi&#xB2; = 14.80, df = 10, and I&#xB2; = 32%.</alt-text>
</graphic>
</fig>
</sec>
<sec id="s3-5-3">
<title>3.5.3 LVEF</title>
<p>In total, thirteen RCTs (<xref ref-type="bibr" rid="B9">Cui, 2022</xref>; <xref ref-type="bibr" rid="B15">Du, 2016</xref>; <xref ref-type="bibr" rid="B36">Jin and Wu, 2006</xref>; <xref ref-type="bibr" rid="B42">Li et al., 2019</xref>; <xref ref-type="bibr" rid="B72">Song, 2019</xref>; <xref ref-type="bibr" rid="B76">Tan, 2019</xref>; <xref ref-type="bibr" rid="B77">Tao, 2021</xref>; <xref ref-type="bibr" rid="B83">Wang et al., 2012</xref>; <xref ref-type="bibr" rid="B81">Wang and Sun, 2018</xref>; <xref ref-type="bibr" rid="B90">Yang and Zhou, 2002</xref>; <xref ref-type="bibr" rid="B95">Yuan, 2018</xref>; <xref ref-type="bibr" rid="B96">Zhang, 2013</xref>; <xref ref-type="bibr" rid="B100">Zhu et al., 2019</xref>) reported the effect of TCM on LVEF. Two RCTs (<xref ref-type="bibr" rid="B9">Cui, 2022</xref>; <xref ref-type="bibr" rid="B77">Tao, 2021</xref>) were excluded because they did not measure or report baseline LVEF. The meta-analysis was performed with the 11 remaining studies containing 1, 005 patients (<xref ref-type="bibr" rid="B15">Du, 2016</xref>; <xref ref-type="bibr" rid="B36">Jin and Wu, 2006</xref>; <xref ref-type="bibr" rid="B42">Li et al., 2019</xref>; <xref ref-type="bibr" rid="B72">Song, 2019</xref>; <xref ref-type="bibr" rid="B76">Tan, 2019</xref>; <xref ref-type="bibr" rid="B83">Wang et al., 2012</xref>; <xref ref-type="bibr" rid="B81">Wang and Sun, 2018</xref>; <xref ref-type="bibr" rid="B90">Yang and Zhou, 2002</xref>; <xref ref-type="bibr" rid="B95">Yuan, 2018</xref>; <xref ref-type="bibr" rid="B96">Zhang, 2013</xref>; <xref ref-type="bibr" rid="B100">Zhu et al., 2019</xref>). The results of the meta-analysis indicated that LVEF of the TCM group was substantially greater than that of the control group (MD &#x3d; 0.14; 95% CI: 0.07 to 0.21; P &#x3d; 0.0001). However, the random-effects model exhibited statistical heterogeneity (&#x3c7;<sup>2</sup> &#x3d; 261.06; I<sup>2</sup> &#x3d; 96%; P &#x3c; 0.00001) (<xref ref-type="fig" rid="F5">Figure 5</xref>). Sensitivity analyses demonstrated the robust results for LVEF.</p>
<fig id="F5" position="float">
<label>FIGURE 5</label>
<caption>
<p>Forest plot for the meta-analysis of LVEF. Abbreviation: LVEF: left ventricular ejection fraction; TCM: traditional Chinese medicine. Note: Wang 2012b: <xref ref-type="bibr" rid="B83">Wang et al., 2012</xref>.</p>
</caption>
<graphic xlink:href="fphar-16-1506234-g005.tif">
<alt-text content-type="machine-generated">Forest plot showing meta-analysis of studies comparing TCM to control. It lists study year, mean, standard deviation, total for TCM and control groups, weight, mean difference, and confidence intervals. Plots indicate average effect size and confidence intervals for each study with an overall estimate. The test for overall effect is statistically significant.</alt-text>
</graphic>
</fig>
</sec>
</sec>
<sec id="s3-6">
<title>3.6 Secondary outcomes</title>
<sec id="s3-6-1">
<title>3.6.1 CO</title>
<p>In total, two RCTs (<xref ref-type="bibr" rid="B15">Du, 2016</xref>; <xref ref-type="bibr" rid="B77">Tao, 2021</xref>) reported the effect of TCM on CO. One RCT (<xref ref-type="bibr" rid="B77">Tao, 2021</xref>) was excluded because it did not measure or report baseline CO. The meta-analysis was not performed due to insufficient available data. Only one study (<xref ref-type="bibr" rid="B15">Du, 2016</xref>) showed statistically significant difference in CO when comparing the TCM group to the control group. Given a lack of included trials, sensitivity analysis was not performed.</p>
</sec>
<sec id="s3-6-2">
<title>3.6.2 E/A ratio</title>
<p>In total, three RCTs (<xref ref-type="bibr" rid="B4">Cai, 2016</xref>; <xref ref-type="bibr" rid="B42">Li et al., 2019</xref>; <xref ref-type="bibr" rid="B82">Wang and Wang, 2012</xref>) reported the effect of TCM on E/A ratio. According to a meta-analysis, the TCM group&#x2019;s E/A ratio improved when compared to the control group (MD &#x3d; 0.17; 95% CI: 0.14 to 0.20; P &#x3c; 0.00001). There was low heterogeneity (&#x3c7;<sup>2</sup> &#x3d; 2.16; I<sup>2</sup> &#x3d; 7%; P &#x3d; 0.34) and the fixed-effects model was used (<xref ref-type="fig" rid="F6">Figure 6</xref>). Sensitivity analyses demonstrated the robust results for E/A ratio.</p>
<fig id="F6" position="float">
<label>FIGURE 6</label>
<caption>
<p>Forest plot for the meta-analysis of E/A ratio. Abbreviation: E/A: transmitral peak early diastolic velocity (E)/peak late diastolic velocity (A); TCM: traditional Chinese medicine. Note: Wang 2012a: <xref ref-type="bibr" rid="B82">Wang and Wang, 2012</xref>.</p>
</caption>
<graphic xlink:href="fphar-16-1506234-g006.tif">
<alt-text content-type="machine-generated">Forest plot displaying the mean differences and 95% confidence intervals for three studies comparing TCM and control groups. The results indicate a positive mean difference favoring TCM, with individual study differences ranging from 0.15 to 0.20. The overall pooled mean difference is 0.17 with a 95% confidence interval of 0.14 to 0.20. Statistical heterogeneity shows Chi-squared equals 2.16, degrees of freedom equals 2, P equals 0.34, and I-squared equals 7%. The test for overall effect has a Z-score of 10.23 with P less than 0.00001.</alt-text>
</graphic>
</fig>
</sec>
<sec id="s3-6-3">
<title>3.6.3 LVEDD</title>
<p>In total, nine RCTs (<xref ref-type="bibr" rid="B29">Hou et al., 2015</xref>; <xref ref-type="bibr" rid="B47">Liu, 2012</xref>; <xref ref-type="bibr" rid="B72">Song, 2019</xref>; <xref ref-type="bibr" rid="B76">Tan, 2019</xref>; <xref ref-type="bibr" rid="B81">Wang and Sun, 2018</xref>; <xref ref-type="bibr" rid="B95">Yuan, 2018</xref>; <xref ref-type="bibr" rid="B96">Zhang, 2013</xref>; <xref ref-type="bibr" rid="B99">Zhao, 2022</xref>; <xref ref-type="bibr" rid="B100">Zhu et al., 2019</xref>) reported the effect of TCM on LVEDD. Three RCTs (<xref ref-type="bibr" rid="B29">Hou et al., 2015</xref>; <xref ref-type="bibr" rid="B47">Liu, 2012</xref>; <xref ref-type="bibr" rid="B95">Yuan, 2018</xref>) were excluded because they did not measure or report baseline LVEDD. The meta-analysis was performed with the six remaining studies containing 452 patients (<xref ref-type="bibr" rid="B72">Song, 2019</xref>; <xref ref-type="bibr" rid="B76">Tan, 2019</xref>; <xref ref-type="bibr" rid="B81">Wang and Sun, 2018</xref>; <xref ref-type="bibr" rid="B96">Zhang, 2013</xref>; <xref ref-type="bibr" rid="B99">Zhao, 2022</xref>; <xref ref-type="bibr" rid="B100">Zhu et al., 2019</xref>). The results of the meta-analysis indicated that the TCM group&#x2019;s LVEDD was considerably lower than that of the control group (MD &#x3d; &#x2212;7.18; 95% CI: 10.56 to &#x2212;3.81; P &#x3c; 0.0001). However, the random-effects model exhibited statistical heterogeneity (&#x3c7;<sup>2</sup> &#x3d; 45.13; I<sup>2</sup> &#x3d; 89%; P &#x3c; 0.00001) (<xref ref-type="fig" rid="F7">Figure 7a</xref>). Sensitivity analyses demonstrated the robust results for LVEDD.</p>
<fig id="F7" position="float">
<label>FIGURE 7</label>
<caption>
<p>Forest plot for the meta-analysis of LVEDD <bold>(a)</bold> and LVESD <bold>(b)</bold>. Abbreviation: LVEDD: left ventricular end-diastolic diameter; LVESD: left ventricular end-systolic diameter; TCM: traditional Chinese medicine.</p>
</caption>
<graphic xlink:href="fphar-16-1506234-g007.tif">
<alt-text content-type="machine-generated">Forest plots comparing TCM and control groups for two measures: (a) LVEDD and (b) LVESD. Each plot includes individual study data with mean differences, confidence intervals, and weights. Significant results favor the TCM group for both measures, shown by pooled mean differences of -7.18 for LVEDD and -6.98 for LVESD, with confidence intervals not crossing zero.</alt-text>
</graphic>
</fig>
</sec>
<sec id="s3-6-4">
<title>3.6.4 LVESD</title>
<p>In total, four RCTs (<xref ref-type="bibr" rid="B76">Tan, 2019</xref>; <xref ref-type="bibr" rid="B81">Wang and Sun, 2018</xref>; <xref ref-type="bibr" rid="B99">Zhao, 2022</xref>; <xref ref-type="bibr" rid="B100">Zhu et al., 2019</xref>) reported the effect of TCM on LVESD. The results of the meta-analysis demonstrated that the TCM group&#x2019;s LVESD was considerably lower than that of the control group (MD &#x3d; &#x2212;6.98; 95% CI: 9.30 to &#x2212;4.67; P &#x3c; 0.00001). However, the random-effects model indicated statistical heterogeneity (&#x3c7;<sup>2</sup> &#x3d; 13.89; I<sup>2</sup> &#x3d; 78%; P &#x3d; 0.003) (<xref ref-type="fig" rid="F7">Figure 7b</xref>). Sensitivity analyses showed that the I<sup>2</sup> dropped to 2% (P &#x3c; 0.00001) by excluding Zhao&#x2019;s study (<xref ref-type="bibr" rid="B99">Zhao, 2022</xref>), which might significantly impact the effect value and be the primary cause of heterogeneity.</p>
</sec>
<sec id="s3-6-5">
<title>3.6.5 LVMI</title>
<p>In total, two RCTs (<xref ref-type="bibr" rid="B29">Hou et al., 2015</xref>; <xref ref-type="bibr" rid="B47">Liu, 2012</xref>) reported the effect of TCM on LVMI. A meta-analysis revealed that the TCM group&#x2019;s LVMI was considerably lower than that of the control group (MD &#x3d; &#x2212;8.50; 95% CI: 11.88 to &#x2212;5.11; P &#x3c; 0.00001). The fixed-effects model was applied, and there was low heterogeneity (&#x3c7;<sup>2</sup> &#x3d; 0.30; I<sup>2</sup> &#x3d; 0%; P &#x3d; 0.58) (<xref ref-type="fig" rid="F8">Figure 8a</xref>). Given a lack of included trials, sensitivity analysis was not performed.</p>
<fig id="F8" position="float">
<label>FIGURE 8</label>
<caption>
<p>Forest plot for the meta-analysis of LVMI <bold>(a)</bold> and IVSTD <bold>(b)</bold>. Abbreviation: LVMI: left ventricular mass index; IVSTD: interventricular septum thickness in diastole; TCM: traditional Chinese medicine.</p>
</caption>
<graphic xlink:href="fphar-16-1506234-g008.tif">
<alt-text content-type="machine-generated">Meta-analysis forest plots comparing TCM and control groups. (a) LVMI: Includes studies by Hou (2015) and Liu (2012), showing a mean difference favoring TCM (-8.50, 95% CI: -11.88 to -5.11). (b) IVSTD: Includes studies by Li (2019), Tan (2019), and Wang (2018), showing a mean difference favoring TCM (-3.12, 95% CI: -3.72 to -2.53). Statistical homogeneity is indicated with I&#xB2; = 0% for both plots.</alt-text>
</graphic>
</fig>
</sec>
<sec id="s3-6-6">
<title>3.6.6 IVSTD</title>
<p>In total, three RCTs (<xref ref-type="bibr" rid="B42">Li et al., 2019</xref>; <xref ref-type="bibr" rid="B76">Tan, 2019</xref>; <xref ref-type="bibr" rid="B81">Wang and Sun, 2018</xref>) reported the effect of TCM on IVSTD. A meta-analysis revealed that the TCM group&#x2019;s IVSTD was considerably lower than that of the control group (MD &#x3d; &#x2212;3.12; 95% CI: 3.72 to &#x2212;2.53; P &#x3c; 0.00001). The fixed-effects model was applied, and there was low heterogeneity (&#x3c7;<sup>2</sup> &#x3d; 0.12; I<sup>2</sup> &#x3d; 0%; P &#x3d; 0.94) (<xref ref-type="fig" rid="F8">Figure 8b</xref>). Sensitivity analyses demonstrated the robust results for IVSTD.</p>
</sec>
<sec id="s3-6-7">
<title>3.6.7 BNP</title>
<p>In total, three RCTs (<xref ref-type="bibr" rid="B71">Song, 2011</xref>; <xref ref-type="bibr" rid="B81">Wang and Sun, 2018</xref>; <xref ref-type="bibr" rid="B99">Zhao, 2022</xref>) reported the effect of TCM on BNP. The results of the meta-analysis indicated that BNP was lower in the TCM group as compared to the control group (MD &#x3d; &#x2212;60.78; 95% CI: 101.00 to &#x2212;20.56; P &#x3d; 0.003), however, the random-effects model exhibited statistical heterogeneity (&#x3c7;<sup>2</sup> &#x3d; 11.97; I<sup>2</sup> &#x3d; 83%; P &#x3d; 0.003) (<xref ref-type="fig" rid="F9">Figure 9</xref>). According to the results of the sensitivity analyses, after excluding Wang&#x2019;s study (<xref ref-type="bibr" rid="B81">Wang and Sun, 2018</xref>), I<sup>2</sup> dropped to 0% (P &#x3c; 0.00001). In addition, after excluding Song&#x2019;s study (<xref ref-type="bibr" rid="B71">Song, 2011</xref>), the statistically significant difference did not exist between the control group and the TCM group. These unrobust results showed that the meta-analysis of BNP was not reliable.</p>
<fig id="F9" position="float">
<label>FIGURE 9</label>
<caption>
<p>Forest plot for the meta-analysis of BNP. Abbreviation: BNP: B-type natriuretic peptide; TCM: traditional Chinese medicine.</p>
</caption>
<graphic xlink:href="fphar-16-1506234-g009.tif">
<alt-text content-type="machine-generated">Forest plot comparing TCM and control groups across three studies (Song 2011, Wang 2018, Zhao 2022) with effect sizes favoring TCM. The pooled mean difference is -60.78, with a 95% confidence interval of [-101.00, -20.56] and significant heterogeneity (I&#xB2; = 83%, P = 0.003).</alt-text>
</graphic>
</fig>
</sec>
<sec id="s3-6-8">
<title>3.6.8 Adverse events</title>
<p>In total, eight RCTs (<xref ref-type="bibr" rid="B4">Cai, 2016</xref>; <xref ref-type="bibr" rid="B9">Cui, 2022</xref>; <xref ref-type="bibr" rid="B30">Hu, 2012</xref>; <xref ref-type="bibr" rid="B63">Peng, 2015</xref>; <xref ref-type="bibr" rid="B71">Song, 2011</xref>; <xref ref-type="bibr" rid="B83">Wang et al., 2012</xref>; <xref ref-type="bibr" rid="B81">Wang and Sun, 2018</xref>; <xref ref-type="bibr" rid="B90">Yang and Zhou, 2002</xref>) reported adverse events, 16 in the TCM group, and 31 in the control group. According to a meta-analysis, individuals in the TCM group experienced fewer adverse events than those in the control group (RR &#x3d; 0.51; 95% CI: 0.29 to 0.91; P &#x3d; 0.02). The heterogeneity test showed low heterogeneity (&#x3c7;<sup>2</sup> &#x3d; 1.46; I<sup>2</sup> &#x3d; 0%; P &#x3d; 0.83), so the fixed-effects model was used (<xref ref-type="fig" rid="F10">Figure 10</xref>). Sensitivity analyses revealed the unrobust results for adverse events. After excluding Hu&#x2019;s study (<xref ref-type="bibr" rid="B30">Hu, 2012</xref>), the statistically significant difference did not exist between the control group and the TCM group. The most common adverse events included gastrointestinal symptoms, headache, arrhythmia, abnormal liver function, electrolyte imbalance, and respiratory failure. Of the eight studies, three studies (<xref ref-type="bibr" rid="B71">Song, 2011</xref>; <xref ref-type="bibr" rid="B83">Wang et al., 2012</xref>; <xref ref-type="bibr" rid="B90">Yang and Zhou, 2002</xref>) reported that there were no adverse events during the research period between the TCM and the control group.</p>
<fig id="F10" position="float">
<label>FIGURE 10</label>
<caption>
<p>Forest plot for the meta-analysis of adverse events. Abbreviation: TCM: traditional Chinese medicine. Note: Wang 2012b: <xref ref-type="bibr" rid="B83">Wang et al., 2012</xref>.</p>
</caption>
<graphic xlink:href="fphar-16-1506234-g010.tif">
<alt-text content-type="machine-generated">Forest plot showing a meta-analysis of studies comparing TCM and control groups. Individual studies report risk ratios with 95% confidence intervals, some are not estimable. The overall effect has a risk ratio of 0.51 [0.29, 0.91], with heterogeneity Chi&#xB2; = 1.46, I&#xB2; = 0%. The plot favors TCM over the control.</alt-text>
</graphic>
</fig>
</sec>
</sec>
<sec id="s3-7">
<title>3.7 Quality assessment of the evidence</title>
<p>The evidence profile was displayed in <xref ref-type="table" rid="T3">Table 3</xref> and the degree of certainty of the evidence was evaluated using GRADEpro GDT. There was moderate-quality evidence on NYHA classification, E/A ratio, LVMI, IVSTD, and adverse events; low-quality evidence on LVEDD, LVESD, and BNP; and very low-quality evidence on BP (SBP and DBP) and LVEF. The most frequent sources of bias in randomized trials were the lack of blinding for study personnel and participants and the outcome assessment blinding. Thus, the &#x2018;Risk of bias&#x2019; domain was judged to be at serious risk of bias. For the research inconsistency, there was high heterogeneity in six pieces of evidence, and the &#x2018;Inconsistency&#x2019; domain was judged to be at serious inconsistency. Regarding the study&#x2019;s imprecision, none of the indices went over the invalid line or received a downgrading. Regarding research indirectness, there was some inconsistency among the included studies in terms of interventions. However, there were no significant differences in their research purposes and no downgrades. The literature was carefully retrieved concerning publication bias, and no disclosed commercial conflicts of interest were present. In addition, publication bias was assessed for BP (SBP and DBP), NYHA classification, and LVEF. For BP (SBP and DBP) and LVEF, the assessment of publication bias was limited due to the insufficient number of studies for the outcomes. Thus, publication bias is strongly suspected.</p>
<table-wrap id="T3" position="float">
<label>TABLE 3</label>
<caption>
<p>The GRADE evidence profile for TCM in the treatment of patients with HHD.</p>
</caption>
<table>
<thead valign="top">
<tr>
<th colspan="7" align="center">Certainty assessment</th>
<th colspan="2" align="center">No of patients</th>
<th colspan="2" align="center">Effect</th>
<th rowspan="2" align="center">Certainty</th>
<th rowspan="2" align="center">Importance</th>
</tr>
<tr>
<th align="center">No of studies</th>
<th align="center">Study design</th>
<th align="center">Risk of bias</th>
<th align="center">Inconsistency</th>
<th align="center">Indirectness</th>
<th align="center">Imprecision</th>
<th align="center">Other considerations</th>
<th align="center">TCM</th>
<th align="center">Control</th>
<th align="center">Relative (a95% CI)</th>
<th align="center">Absolute (95% CI)</th>
</tr>
</thead>
<tbody valign="top">
<tr style="background-color:#CCCCCC">
<td colspan="13" align="left">SBP</td>
</tr>
<tr>
<td align="center">6</td>
<td align="center">Randomized trials</td>
<td align="center">Serious<sup>a</sup>
</td>
<td align="center">Serious<sup>b</sup>
</td>
<td align="center">Not serious</td>
<td align="center">Not serious</td>
<td align="center">Publication bias strongly suspected</td>
<td align="center">273</td>
<td align="center">245</td>
<td align="center">-</td>
<td align="center">MD 5.69 lower (10.79 lower to 0.59 lower)</td>
<td align="center">&#x2a01;&#x25cb;&#x25cb;&#x25cb;<break/>Very low</td>
<td align="center">CRITICAL</td>
</tr>
<tr style="background-color:#CCCCCC">
<td colspan="13" align="left">DBP</td>
</tr>
<tr>
<td align="center">6</td>
<td align="center">Randomized trials</td>
<td align="center">Serious<sup>a</sup>
</td>
<td align="center">Serious<sup>b</sup>
</td>
<td align="center">Not serious</td>
<td align="center">Not serious</td>
<td align="center">Publication bias strongly suspected</td>
<td align="center">273</td>
<td align="center">245</td>
<td align="center">-</td>
<td align="center">MD 5.88 lower (10.98 lower to 0.77 lower)</td>
<td align="center">&#x2a01;&#x25cb;&#x25cb;&#x25cb;<break/>Very low</td>
<td align="center">CRITICAL</td>
</tr>
<tr style="background-color:#CCCCCC">
<td colspan="13" align="left">NYHA classification</td>
</tr>
<tr>
<td align="center">11</td>
<td align="center">Randomized trials</td>
<td align="center">Serious<sup>a</sup>
</td>
<td align="center">Not serious</td>
<td align="center">Not serious</td>
<td align="center">Not serious</td>
<td align="center">None</td>
<td align="center">468/515 (90.9%)</td>
<td align="center">354/486 (72.8%)</td>
<td align="center">RR 1.25 (1.18&#x2013;1.33)</td>
<td align="center">182 more per 1,000 (from 131 more to 240 more)</td>
<td align="center">&#x2a01;&#x2a01;&#x2a01;&#x25cb;<break/>Moderate</td>
<td align="center">CRITICAL</td>
</tr>
<tr style="background-color:#CCCCCC">
<td colspan="13" align="left">LVEF</td>
</tr>
<tr>
<td align="center">11</td>
<td align="center">Randomized trials</td>
<td align="center">Serious<sup>a</sup>
</td>
<td align="center">Serious<sup>b</sup>
</td>
<td align="center">Not serious</td>
<td align="center">Not serious</td>
<td align="center">Publication bias strongly suspected</td>
<td align="center">515</td>
<td align="center">490</td>
<td align="center">-</td>
<td align="center">MD 0.14 higher (0.07 higher to 0.21 higher)</td>
<td align="center">&#x2a01;&#x25cb;&#x25cb;&#x25cb;<break/>Very low</td>
<td align="center">CRITICAL</td>
</tr>
<tr style="background-color:#CCCCCC">
<td colspan="13" align="left">E/A ratio</td>
</tr>
<tr>
<td align="center">3</td>
<td align="center">Randomized trials</td>
<td align="center">Serious<sup>a</sup>
</td>
<td align="center">Not serious</td>
<td align="center">Not serious</td>
<td align="center">Not serious</td>
<td align="center">None<sup>c</sup>
</td>
<td align="center">147</td>
<td align="center">146</td>
<td align="center">-</td>
<td align="center">MD 0.17 higher (0.14 higher to 0.2 higher)</td>
<td align="center">&#x2a01;&#x2a01;&#x2a01;&#x25cb;<break/>Moderate</td>
<td align="center">IMPORTANT</td>
</tr>
<tr style="background-color:#CCCCCC">
<td colspan="13" align="left">LVEDD</td>
</tr>
<tr>
<td align="center">6</td>
<td align="center">Randomized trials</td>
<td align="center">Serious<sup>a</sup>
</td>
<td align="center">Serious<sup>b</sup>
</td>
<td align="center">Not serious</td>
<td align="center">Not serious</td>
<td align="center">None<sup>c</sup>
</td>
<td align="center">223</td>
<td align="center">229</td>
<td align="center">-</td>
<td align="center">MD 7.18 lower (10.56 lower to 3.81 lower)</td>
<td align="center">&#x2a01;&#x2a01;&#x25cb;&#x25cb;<break/>Low</td>
<td align="center">IMPORTANT</td>
</tr>
<tr style="background-color:#CCCCCC">
<td colspan="13" align="left">LVESD</td>
</tr>
<tr>
<td align="center">4</td>
<td align="center">Randomized trials</td>
<td align="center">Serious<sup>a</sup>
</td>
<td align="center">Serious<sup>b</sup>
</td>
<td align="center">Not serious</td>
<td align="center">Not serious</td>
<td align="center">None<sup>c</sup>
</td>
<td align="center">145</td>
<td align="center">143</td>
<td align="center">-</td>
<td align="center">MD 6.98 lower (9.3 lower to 4.67 lower)</td>
<td align="center">&#x2a01;&#x2a01;&#x25cb;&#x25cb;<break/>Low</td>
<td align="center">IMPORTANT</td>
</tr>
<tr style="background-color:#CCCCCC">
<td colspan="13" align="left">LVMI</td>
</tr>
<tr>
<td align="center">2</td>
<td align="center">Randomized trials</td>
<td align="center">Serious<sup>a</sup>
</td>
<td align="center">Not serious</td>
<td align="center">Not serious</td>
<td align="center">Not serious</td>
<td align="center">None<sup>c</sup>
</td>
<td align="center">147</td>
<td align="center">147</td>
<td align="center">-</td>
<td align="center">MD 8.5 lower (11.88 lower to 5.11 lower)</td>
<td align="center">&#x2a01;&#x2a01;&#x2a01;&#x25cb;<break/>Moderate</td>
<td align="center">IMPORTANT</td>
</tr>
<tr style="background-color:#CCCCCC">
<td colspan="13" align="left">IVSTD</td>
</tr>
<tr>
<td align="center">3</td>
<td align="center">Randomized trials</td>
<td align="center">Serious<sup>a</sup>
</td>
<td align="center">Not serious</td>
<td align="center">Not serious</td>
<td align="center">Not serious</td>
<td align="center">None<sup>c</sup>
</td>
<td align="center">141</td>
<td align="center">141</td>
<td align="center">-</td>
<td align="center">MD 3.12 lower (3.72 lower to 2.53 lower)</td>
<td align="center">&#x2a01;&#x2a01;&#x2a01;&#x25cb;<break/>Moderate</td>
<td align="center">IMPORTANT</td>
</tr>
<tr style="background-color:#CCCCCC">
<td colspan="13" align="left">BNP</td>
</tr>
<tr>
<td align="center">3</td>
<td align="center">Randomized trials</td>
<td align="center">Serious<sup>a</sup>
</td>
<td align="center">Serious<sup>b</sup>
</td>
<td align="center">Not serious</td>
<td align="center">Not serious</td>
<td align="center">None<sup>c</sup>
</td>
<td align="center">122</td>
<td align="center">123</td>
<td align="center">-</td>
<td align="center">MD 60.78 lower (101 lower to 20.56 lower)</td>
<td align="center">&#x2a01;&#x2a01;&#x25cb;&#x25cb;<break/>Low</td>
<td align="center">IMPORTANT</td>
</tr>
<tr style="background-color:#CCCCCC">
<td colspan="13" align="left">Adverse events</td>
</tr>
<tr>
<td align="center">8</td>
<td align="center">Randomized trials</td>
<td align="center">Serious<sup>a</sup>
</td>
<td align="center">Not serious</td>
<td align="center">Not serious</td>
<td align="center">Not serious</td>
<td align="center">None<sup>c</sup>
</td>
<td align="center">16/392 (4.1%)</td>
<td align="center">31/363 (8.5%)</td>
<td align="center">RR 0.51 (0.29&#x2013;0.91)</td>
<td align="center">42 fewer per 1,000 (from 61 fewer to 8 fewer)</td>
<td align="center">&#x2a01;&#x2a01;&#x2a01;&#x25cb;<break/>Moderate</td>
<td align="center">IMPORTANT</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn>
<p>
<sup>
<italic>a</italic>
</sup> The quality of the majority of trials was not high. <sup>
<italic>b</italic>
</sup> Unexplained heterogeneity. <sup>
<italic>c</italic>
</sup> Funnel plots not completed due to<italic>&#x3c;</italic>10 studies in the meta-analysis. BNP: B-type natriuretic peptide; CI: confidence interval; DBP: diastolic blood pressure; E/A: transmitral peak early diastolic velocity/peak late diastolic velocity; IVSTD: interventricular septum thickness in diastole; LVEDD: left ventricular end-diastolic diameter; LVEF: left ventricular ejection fraction; LVESD: left ventricular end-systolic diameter; LVMI: left ventricular mass index; MD: mean difference; NYHA: new york heart association; RR: risk ratio; SBP: systolic blood pressure; TCM, traditional Chinese medicine.</p>
</fn>
</table-wrap-foot>
</table-wrap>
</sec>
<sec id="s3-8">
<title>3.8 Publication bias</title>
<p>The Egger&#x2019;s test was used for the funnel plot to evaluate publication bias. There was no risk of publication bias in the NYHA classification, according to the symmetrical funnel plot (<xref ref-type="fig" rid="F11">Figure 11a</xref>), whereas the asymmetric funnel plot implied a higher risk of publication bias in LVEF (<xref ref-type="fig" rid="F11">Figure 11b</xref>), SBP (<xref ref-type="fig" rid="F11">Figure 11c</xref>), and DBP (<xref ref-type="fig" rid="F11">Figure 11d</xref>). The results of the meta-analysis were not significantly impacted by publication bias if the trim and fill strategy was applied (<xref ref-type="table" rid="T4">Table 4</xref>).</p>
<fig id="F11" position="float">
<label>FIGURE 11</label>
<caption>
<p>Funnel plots of NYHA classification <bold>(a)</bold>, LVEF <bold>(b)</bold>, SBP <bold>(c)</bold>, and DBP <bold>(d)</bold>. Abbreviation: DBP: diastolic blood pressure; LVEF: left ventricular ejection fraction; NYHA: New York Heart Association; SBP: systolic blood pressure.</p>
</caption>
<graphic xlink:href="fphar-16-1506234-g011.tif">
<alt-text content-type="machine-generated">Four funnel plots with pseudo 95% confidence limits. (a) NYHA classification shows a symmetrical distribution around the line of no effect on a logarithmic scale. (b) LVEF plot displays points around the mean difference, slightly skewed right. (c) SBP plot shows data points skewed left. (d) DBP plot exhibits scattered data, slightly skewed left. Each plot uses standard error against the effect measure.</alt-text>
</graphic>
</fig>
<table-wrap id="T4" position="float">
<label>TABLE 4</label>
<caption>
<p>The results of Egger&#x2019;s test and trim and fill analysis.</p>
</caption>
<table>
<thead valign="top">
<tr>
<th rowspan="2" align="center">Outcomes</th>
<th colspan="2" align="center">Egger&#x2019;s test</th>
<th rowspan="2" align="center">Trim and fill analysis</th>
</tr>
<tr>
<th align="center">T</th>
<th align="center">P</th>
</tr>
</thead>
<tbody valign="top">
<tr>
<td align="center">SBP</td>
<td align="center">&#x2212;3.39</td>
<td align="center">0.027</td>
<td align="center">MD &#x3d; &#x2212;1.312; 95% CI: 2.332 to &#x2212;0.293; P &#x3d; 0.012 &#x3c; 0.05</td>
</tr>
<tr>
<td align="center">DBP</td>
<td align="center">&#x2212;4.33</td>
<td align="center">0.012</td>
<td align="center">MD &#x3d; &#x2212;1.454; 95% CI: 2.553 to &#x2212;0.355; P &#x3d; 0.010 &#x3c; 0.05</td>
</tr>
<tr>
<td align="center">NYHA classification</td>
<td align="center">2.11</td>
<td align="center">0.064</td>
<td align="center">&#x2014;</td>
</tr>
<tr>
<td align="center">LVEF</td>
<td align="center">5.23</td>
<td align="center">0.001</td>
<td align="center">MD &#x3d; 1.514; 95% CI: 0.946 to 2.081; P &#x3d; 0.000 &#x3c; 0.05</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn>
<p>CI: confidence interval; DBP: diastolic blood pressure; LVEF: left ventricular ejection fraction; MD: mean difference; NYHA: new york heart association; SBP: systolic blood pressure.</p>
</fn>
</table-wrap-foot>
</table-wrap>
</sec>
</sec>
<sec sec-type="discussion" id="s4">
<title>4 Discussion</title>
<sec id="s4-1">
<title>4.1 Summary of evidence</title>
<p>This meta-analysis included 21 studies that revealed the potential preventive effects of selected TCM as adjuvant therapy on HHD progression. In terms of BP, TCM as an adjunct in the treatment of hypertension could reduce BP to a certain extent. For the cardiac function, integrated TCM and WM significantly improved NYHA classification, LVEF, E/A ratio, and decreased LVEDD, LVESD, LVMI, IVSTD, and BNP, which indicated that TCM as adjuvant therapy played an important role in attenuating adverse LV remodeling and enhancing the heart&#x2019;s diastolic and systolic functions to a certain extent. Furthermore, adverse events did not appear to be occurring more frequently linked to WM in the TCM group. In general, patients treated with TCM experienced fewer adverse events overall than those in comparator groups.</p>
<p>Vascular incidents were closely associated with elevated BP. A meta-analysis by Ettehad and colleagues (<xref ref-type="bibr" rid="B20">Ettehad et al., 2016</xref>) reported that a 10&#xa0;mmHg decrease in SBP was associated with a 20% lower risk of major cardiovascular disease events, HF by 28%, and all-cause mortality by 13%. For patients having the greatest absolute risk of heart-related incidents, reducing BP would have the most overall benefits. This meta-analysis suggested that TCM as a potential adjuvant therapy effectively reduced BP. However, the results were not robust. It was necessary to conduct more research on the impact of TCM, especially in patients with LVH and hypertension.</p>
<p>The NYHA functional classification was used to assess symptom status, which was characterized as asymptomatic for NYHA &#x2160; and symptomatic for NYHA &#x2161;-&#x2163; (<xref ref-type="bibr" rid="B16">Egbe et al., 2020</xref>). This meta-analysis showed that TCM improved the NYHA classification, indicating that TCM could reduce symptoms and improve cardiac function in HHD patients.</p>
<p>Moreover, it was critical to observe the change in clinical, comprehensive imaging, and biomarker characteristics from simple hypertension to symptomatic HF with preserved ejection fraction (HFpEF) (<xref ref-type="bibr" rid="B18">Ekstr&#xf6;m et al., 2020</xref>). Echocardiography, one of the cardiac imaging modalities, was essential for quantifying changes in the heart structure and function without invasive methods as HF progressed. In terms of LV structure, the most intuitive markers of LV diastolic function were LV size as determined by LVEDD and LVESD. LVMI and IVSTD were used to assess LVH. LV systolic function was assessed using LVEF. CO was used to measure the strength and normality of cardiac ejection function. Due to sample size limitations, results on CO should be interpreted with caution. E/A ratio &#x3c;1 indicated diastolic dysfunction. However, the E/A ratio was affected by age and decreased with older age, which influenced the accuracy of the result to a certain extent. According to the above, TCM as an adjunct played a significant role in the progression of cardiac hypertrophy and ventricular remodeling after HHD, which probably delayed the transition from HHD to HF.</p>
<p>Additionally, BNP could be used to screen patients with multiple HF risk factors and show a downward trend in HF and asymptomatic LV systolic dysfunction (<xref ref-type="bibr" rid="B37">Ledwidge et al., 2013</xref>; <xref ref-type="bibr" rid="B70">Slivnick and Lampert, 2019</xref>). This meta-analysis revealed that TCM combined with WM therapy effectively decreased BNP. Although the certainty of evidence about BNP was low and the result lacked robustness owing to the risk of bias, inconsistency, and insufficient data, this is an interesting proof-of-concept study that deserves further investigation (<xref ref-type="bibr" rid="B70">Slivnick and Lampert, 2019</xref>).</p>
<p>For the results with high heterogeneity, we explored several potential sources of heterogeneity, including the age of patients, the variations in TCM prescriptions, dosages, forms of dosage, modes of treatment, treatment duration, and different stages of HHD. These factors might also contribute to publication bias. However, subgroup age and TCM analysis were not possible owing to the small subgroup size. Some studies did not record the precise course of the disease, and none of the included RCTs mentioned the stage of HHD. In addition, despite doing additional sensitivity analyses to investigate the origins of heterogeneity, we were incapable of explaining the significant heterogeneity observed in the majority of our investigations. Thus, given the evidence overall ranged from moderate to very low certainty, care should be used when interpreting the findings.</p>
</sec>
<sec id="s4-2">
<title>4.2 The progression from hypertension to HHD and HF</title>
<p>Hypertension, characterized by raised systemic arterial pressure, is a chronic disease that has been considered an independent risk factor for cardiovascular disease and is associated with the development of HF (<xref ref-type="bibr" rid="B51">Liu et al., 2022</xref>; <xref ref-type="bibr" rid="B18">Ekstr&#xf6;m et al., 2020</xref>). Prolonged hypertension and the corresponding neurohormonal stimulation resulted in the malfunctioning of cardiomyocytes and the irregular build-up of cardiac extracellular matrix, which in turn caused cardiac fibrosis (<xref ref-type="bibr" rid="B25">G&#xfc;lhan Mehmet et al., 2021</xref>; <xref ref-type="bibr" rid="B55">Mann and Felker, 2016</xref>; <xref ref-type="bibr" rid="B68">Salmas et al., 2017</xref>; <xref ref-type="bibr" rid="B69">Selamoglu Talas, 2014</xref>). Besides, the overactivated renin-angiotensin-aldosterone system (RAAS) and sympathetic nervous system also played an idiopathic role in cardiac fibrosis and LVH, which increased myocardial stiffness, caused aberrant myocardial systolic and diastolic function in the end by reducing ventricular compliance and restricting myocardial activity (<xref ref-type="bibr" rid="B12">Di Palo and Barone, 2020</xref>; <xref ref-type="bibr" rid="B88">Wright et al., 2008</xref>). HHD encompasses a spectrum of illnesses ranging from unmanaged hypertension to the ultimate development of HF (<xref ref-type="bibr" rid="B70">Slivnick and Lampert, 2019</xref>). Simple hypertension initiated the development of extracellular alterations and myocardial fibrosis, perhaps serving as a precursory mechanism in the development of HHD and HF from hypertension (<xref ref-type="bibr" rid="B18">Ekstr&#xf6;m et al., 2020</xref>). Diastolic dysfunction was thought to be the early developmental stage of HHD, and LVH was thought to be the trigger for the condition (<xref ref-type="bibr" rid="B12">Di Palo and Barone, 2020</xref>; <xref ref-type="bibr" rid="B70">Slivnick and Lampert, 2019</xref>). Persistent pressure overload in the heart due to persistent hypertension caused LVH and myocardial fibrosis, leading to progressive diastolic dysfunction, decompensation, increasing LV dilatation, and eccentric hypertrophy caused by sustained volume overload thereby causing systolic dysfunction to arise (<xref ref-type="bibr" rid="B56">Messerli et al., 2017</xref>). The heart is better protected and cardiac function is maintained in the early stages of cardiac hypertrophy (<xref ref-type="bibr" rid="B31">Hu et al., 2022</xref>; <xref ref-type="bibr" rid="B3">Bernardo et al., 2010</xref>). Prolonged hypertrophy, however, brought about inflammation, myocardial fibrosis, cardiomyocyte enlargement, and cardiac contractile dysfunction, all of which contributed to the development of chronic HF (<xref ref-type="bibr" rid="B66">Ritter and Neyses, 2003</xref>; <xref ref-type="bibr" rid="B45">Lieu and Koch, 2019</xref>; <xref ref-type="bibr" rid="B31">Hu et al., 2022</xref>). Once hypertensive LVH develops, the risk of developing heart failure, especially HFpHF, increases dramatically (<xref ref-type="bibr" rid="B92">Yao et al., 2017</xref>). Aggressive treatment might be able to reverse the development of LVH if it is identified early. However, the existence of LVH hastened the transition to HF and was irreversible once HF occurred (<xref ref-type="bibr" rid="B70">Slivnick and Lampert, 2019</xref>).</p>
</sec>
<sec id="s4-3">
<title>4.3 Pharmacological effects of TCM</title>
<p>TCM, referred to as botanical medicine, phytomedicine, or phytotherapy, is the practice for medicinal purposes with the roots, seeds, bark, leaves, or flowers of plants, which is regarded as TCM in China. According to the World Health Organization (WHO) (<xref ref-type="bibr" rid="B86">WHO Traditional, 2021</xref>), botanical drugs, TCM preparations, and complete metabolites are considered to be part of TCM. The field of medicine has given TCM, as one of the complementary and alternative medicines, considerable attention, with a primary focus on active pharmaceutical metabolites. In this meta-analysis, the top 5 Chinese botanical drugs for replenishing qi and activating blood circulation were <italic>S. miltiorrhiza</italic> Bunge (Danshen), <italic>O. striata</italic> (DC.) Pimenov &#x26; Kljuykov (Chuanxiong), <italic>P. montana</italic> var. <italic>lobata</italic> (Willd.) Maesen &#x26; S.M.Almeida ex Sanjappa &#x26; Predeep (Gegen), <italic>A. mongholicus</italic> Bunge (Huangqi), and <italic>Typha angustifolia</italic> L. (Puhuang) (<xref ref-type="fig" rid="F12">Figure 12</xref>). The five botanical drugs possess the effects of replenishing qi and activating blood circulation. They are used in the treatment of the development of HHD and HF from hypertension. Studies have shown that the method of replenishing qi and activating blood circulation can improve cardiac fibrosis after pressure overload-induced cardiac hypertrophy (<xref ref-type="bibr" rid="B1">Anwaier et al., 2022</xref>). The QiShenYiQi pill is a Chinese medicine approved by the China State Food and Drug Administration in 2003 for the treatment of cardiac dysfunction, and it includes <italic>A. mongholicus</italic> Bunge (Huangqi), <italic>Panax notoginseng</italic> (Burkill) F. H. Chen (Sanqi), <italic>S. miltiorrhiza</italic> Bunge (Danshen), and <italic>Dalbergia odorifera</italic> T. C. Chen (Jiangxiang). It inhibited myocardial fibrosis after pressure overload, which was mediated by ribosomal protein S19-mediated transforming growth factor &#x3b2;1 signaling and decreased four-and-a-half LIM domains protein 2 (<xref ref-type="bibr" rid="B1">Anwaier et al., 2022</xref>). The QiShenYiQi pill can also relieve fatigue-induced cardiac hypertrophy and enhance heart function, which is correlated with its potential to improve energy metabolism by regulating insulin-like growth factor-1 receptor signaling (<xref ref-type="bibr" rid="B32">Huang et al., 2019</xref>).</p>
<fig id="F12" position="float">
<label>FIGURE 12</label>
<caption>
<p>Pharmacological effects of TCM on HHD progression. Abbreviation: HHD: hypertensive heart disease; TCM: traditional Chinese medicine.</p>
</caption>
<graphic xlink:href="fphar-16-1506234-g012.tif">
<alt-text content-type="machine-generated">Diagram illustrating the pharmacological effects of Chinese botanical drugs on the progression of hypertensive heart disease. It shows five plants: Salvia miltiorrhiza, Conioselinum anthriscoides, Pueraria montana, Astragalus mongholicus, and Typha angustifolia. The pathways involve mechanisms like protecting vascular endothelium, inhibiting cardiomyocyte apoptosis, regulating blood pressure, and inhibiting cardiac fibrosis and vascular restenosis. Effects include anti-atherosclerosis and pro-angiogenic outcomes, aiming to reduce hypertension progression to heart failure.</alt-text>
</graphic>
</fig>
<p>
<italic>Salvia miltiorrhiza</italic> Bunge (Danshen) was a traditional and precious Chinese botanical drug with high medicinal value, which was widely utilized to treat a variety of cardiovascular diseases. Clinically, <italic>S. miltiorrhiza</italic> Bunge (Danshen) could effectively enhance circulation, eliminate blood stasis, ameliorate inflammation, exert anti-oxidation, and inhibit vascular remodeling (<xref ref-type="bibr" rid="B60">Orgah et al., 2020</xref>). Maintaining endothelial function has been shown in earlier research to be a viable treatment approach for reducing pressure overload-induced heart damage (<xref ref-type="bibr" rid="B84">Wang et al., 2013</xref>; <xref ref-type="bibr" rid="B73">Su et al., 2015</xref>). Through endothelial protection, salvianolic acid, the main pharmacologic metabolites in <italic>S. miltiorrhiza</italic> Bunge (Danshen), reduced the effects of pressure overload-induced ventricular chamber expansion, cardiac dysfunction, and fibrosis. According to network pharmacology, salvianolic acid A (<xref ref-type="fig" rid="F13">Figure 13a</xref>) was speculated the obstruct the important target proteins that mediate inflammatory responses such as apolipoprotein E, low-density lipoprotein cholesterol, and tumor necrosis factor, and protection for vascular endothelium in many ways (<xref ref-type="bibr" rid="B75">Sun et al., 2021</xref>). One experimental study in mice demonstrated that through an HIF1&#x3b1;/HSF1/CD31 pathway, salvianolic acid shielded cardiac endothelial cells from pressure overload, suggesting a possible use for salvianolic acid in HHD (<xref ref-type="bibr" rid="B44">Li N et al., 2022</xref>). In addition, A study revealed the role of salvianolic acid A in lowering cardiac fibrosis and hypertrophy in rats with spontaneous hypertension by inhibiting MMP-9 (<xref ref-type="bibr" rid="B35">Jiang et al., 2013</xref>). Neocryptotanshinone (NCTS) is a metabolite derived from <italic>S. miltiorrhiza</italic> Bunge (Danshen). It enhanced mitochondrial transcription factor A levels, promoted mitochondrial biogenesis, and increased myocardial adenosine triphosphate levels by activating retinoid X receptor &#x3b1;. The study has shown that NCTS improves myocardial energy metabolism, including fatty acid oxidation and mitochondrial biogenesis, by regulating the retinoid X receptor alpha &#x3b1;/peroxisome proliferator-activated receptor &#x3b1; pathway in mice with heart failure post-acute myocardial infarction (<xref ref-type="bibr" rid="B54">Ma et al., 2023</xref>).</p>
<fig id="F13" position="float">
<label>FIGURE 13</label>
<caption>
<p>Chemical structures of main metabolites in the top 5 Chinese botanical drugs for the treatment of HHD: <bold>(a)</bold> Salvianolic acid A, <bold>(b)</bold> 2,3,5,6-Tetramethylpyrazine, <bold>(c)</bold> Puerarin, <bold>(d)</bold> Astragaloside IV, and <bold>(e)</bold> (2S)-naringenin.</p>
</caption>
<graphic xlink:href="fphar-16-1506234-g013.tif">
<alt-text content-type="machine-generated">Chemical structure diagrams of five compounds: (a) Salvianolic acid A, showing interconnected rings and oxygen atoms. (b) 2,3,5,6-Tetramethylpyrazine with a nitrogen-containing ring. (c) Puerarin, featuring complex rings and hydroxyl groups. (d) Astragaloside IV, a large structure with multiple rings and attached sugars. (e) (2S)-Naringenin, displaying a central ring system with side groups.</alt-text>
</graphic>
</fig>
<p>
<italic>Oreocome striata</italic> (DC.) Pimenov &#x26; Kljuykov (Chuanxiong) is a member of the Umbelliferae family and is grown mostly in Sichuan Province, China. It is a frequently prescribed TCM. In Shen Nong&#x2019;s Materia Medica (Shen Nong Ben Cao Jing), <italic>O. striata</italic> (DC.) Pimenov &#x26; Kljuykov (Chuanxiong) could activate the blood, relieve pain, and remove blood stasis. The bioactive metabolites contained in <italic>O. striata</italic> (DC.) Pimenov &#x26; Kljuykov (Chuanxiong) primarily included alkaloids, phenols and organic acids, phthalides, and polysaccharides (<xref ref-type="bibr" rid="B46">Lin et al., 2022</xref>). Among these, Tetramethylpyrazine (<xref ref-type="fig" rid="F13">Figure 13b</xref>) has been isolated as an alkaloid from the rhizome of <italic>O. striata</italic> (DC.) Pimenov &#x26; Kljuykov (Chuanxiong) and has multiple bioactivities (<xref ref-type="bibr" rid="B91">Yang et al., 2019</xref>). Tetramethylpyrazine has been shown in prior research to have a wide range of physiological effects, including protection against endothelial damage, antioxidative stress, anti-inflammatory, antiapoptotic, and antiplatelet aggregation, as well as improvements in microcirculation, vascular smooth muscle cell proliferation and migration, and vasodilation (<xref ref-type="bibr" rid="B74">Su et al., 2019</xref>; <xref ref-type="bibr" rid="B46">Lin et al., 2022</xref>). Besides, Liguzinediol, as a novel para-dihydroxy derivative of Tetramethylpyrazine extracted from the TCM Chuanxiong, demonstrated the effect on increasing heart function and preventing myocardial cell apoptosis, which was linked to controlling the expression of Bcl-s, Bax, caspase-s, and NF-&#x3ba;B expression in the rat model of HF (<xref ref-type="bibr" rid="B40">Li et al., 2014</xref>).</p>
<p>
<italic>Pueraria montana</italic> var. <italic>lobata</italic> (Willd.) Maesen &#x26; S.M.Almeida ex Sanjappa &#x26; Predeep (Gegen) originated from Shen Nong&#x2019;s Materia Medica (Shen Nong Ben Cao Jing) and is a notable TCM botanical drug. It is used to stimulate Spleen Yang to stop diarrhea and promote the production of bodily fluids. It has a sweet and acrid flavor (<xref ref-type="bibr" rid="B87">Wong et al., 2011</xref>). In clinical application, <italic>P. montana</italic> var. <italic>lobata</italic> (Willd.) Maesen &#x26; S.M.Almeida ex Sanjappa &#x26; Predeep (Gegen) is frequently used as a necessary botanical drug in TCM formulas to treat cardiovascular diseases, including hypertension, cardiac infarction, and angina pectoris. <italic>Pueraria montana</italic> var. <italic>lobata</italic> (Willd.) Maesen &#x26; S.M.Almeida ex Sanjappa &#x26; Predeep (Gegen) contains more than 70 metabolites, of which isoflavones and triterpenoids make up the majority. Puerarin (<xref ref-type="fig" rid="F13">Figure 13c</xref>), the main bioactive metabolite and approximately 60% of all isoflavones, has a broad range of pharmacological characteristics, such as cardioprotection, vasodilation, anti-inflammatory effects, antioxidant activity, etc. (<xref ref-type="bibr" rid="B97">Zhang et al., 2020</xref>). Numerous animal models and cell cultures have shown puerarin&#x2019;s pharmacological impacts on the cardiovascular system (<xref ref-type="bibr" rid="B87">Wong et al., 2011</xref>). A previous experiment revealed that puerarin inhibited &#x3b2;-adrenoceptors to provide its anti-hypertensive action (<xref ref-type="bibr" rid="B52">Lu et al., 1987</xref>). In another study, puerarin had a comparable impact to verapamil. Angiotensin &#x2161; type 1 receptor (AT1) and angiotensin-converting enzyme 2 (ACE2) mRNA expressions were considerably upregulated in hepatic tissues, while AT1 and ACE2 mRNA expressions in cardiac tissues were suppressed (<xref ref-type="bibr" rid="B93">Ye et al., 2008</xref>).</p>
<p>
<italic>Astragalus mongholicus</italic> Bunge (Huangqi) is Chinese medicine with tonic, diuretic, blood-nourishing, and detoxifying properties recorded originally in Shen Nong&#x2019;s Materia Medica (Shen Nong Ben Cao Jing) (<xref ref-type="bibr" rid="B8">Chinese Pharmacopoeia Commission, 2015</xref>). Previous study summarized that <italic>A. mongholicus</italic> Bunge (Huangqi) has obvious therapeutic effects on hypertension, cardiac hypertrophy, chronic HF, atherosclerosis, and other cardiovascular diseases (<xref ref-type="bibr" rid="B43">Li M et al., 2022</xref>). Furthermore, <italic>A. mongholicus</italic> Bunge (Huangqi) could strengthen myocardial contractility, protect myocardial cells, improve cardiac function, and increase myocardial energy metabolism (<xref ref-type="bibr" rid="B53">Lv et al., 2021</xref>; <xref ref-type="bibr" rid="B6">Chen et al., 2015</xref>). <italic>Astragalus mongholicus</italic> Bunge (Huangqi) contains various biological active metabolites, such as astragaloside, isoflavones, saponins, polysaccharides, and flavonoids. The primary mechanisms were anti-inflammatory, anti-oxidative damage, anti-apoptotic, immunomodulatory, and antithrombotic (<xref ref-type="bibr" rid="B41">Li et al., 2018</xref>). Astragaloside &#x2163; was one of the primary active metabolites of <italic>A. mongholicus</italic> Bunge (Huangqi) (<xref ref-type="fig" rid="F13">Figure 13d</xref>). It has been found to target the miR-135a-TRPM7-TGF-&#x3b2;/Smads pathway, which may reduce cardiac fibrosis (<xref ref-type="bibr" rid="B85">Wei et al., 2020</xref>). Through the signaling pathways for ten-eleven translocation 2 and DNA methyltransferase 1, Astragaloside &#x2163; protects against vascular remodeling brought on by hypertension. This activity is crucial for controlling the function of vascular smooth muscle cells (<xref ref-type="bibr" rid="B43">Li M et al., 2022</xref>). In addition, Astragalus polysaccharides (ASP), which have therapeutic benefits on cardiovascular disorders such as cardiac hypertrophy and vascular endothelial dysfunction, were thought to be another significant metabolite of <italic>A. mongholicus</italic> Bunge (Huangqi). By blocking calcium-mediated calcineurin/NFATc3 and CaMKII signaling, ASP reduces cardiac hypertrophy in isoproterenol-induced hypertrophic myocardium (<xref ref-type="bibr" rid="B5">Chen et al., 2007</xref>). According to other animal and cell experiments, ASP has shown protective effectiveness in MVRI/ISO-treated cardiomyocytes by preventing apoptosis (<xref ref-type="bibr" rid="B49">Liu et al., 2018</xref>). ASP improved the pathological state of myocardial damage and chronic myocardial fibrosis by reducing the expression of inflammatory markers in the heart, including Interleukin-1&#x3b2;, interleukin-6, Tumor necrosis factor-&#x3b1;, monocyte chemoattractant protein-1, and interferon-&#x3b3; (<xref ref-type="bibr" rid="B50">Liu et al., 2019</xref>). In TCM, Astragali Radix was often combined with other botanical drugs in various complex prescription formulas.</p>
<p>
<italic>Typha angustifolia</italic> L. (Puhuang), the dried pollen of typha, was originally recorded in Shen Nong&#x2019;s Materia Medica (Shen Nong Ben Cao Jing). The National Health Commission of the People&#x2019;s Republic of China recognized it as a functional food in 2002, and the 2015 edition of the Pharmacopoeia of the People&#x2019;s Republic of China included it (<xref ref-type="bibr" rid="B21">Gao et al., 2021</xref>). It was frequently used as TCM to treat angina pectoris, dysmenorrhea, hematuria, stranguria, stroke, metrorrhagia, and injuries from falls (<xref ref-type="bibr" rid="B13">Ding et al., 2018</xref>; <xref ref-type="bibr" rid="B64">Qin and Sun, 2005</xref>). <italic>Typha angustifolia</italic> L. (Puhuang) is mostly composed of flavonoids, sterols, amino acids, organic acids, long-chain hydrocarbons, and other chemicals (<xref ref-type="bibr" rid="B13">Ding et al., 2018</xref>). As is shown in pharmacological and clinical research, <italic>Typha angustifolia</italic> L. (Puhuang) is effective in improving microcirculation, raising cAMP levels, anti-inflammatory, antiplatelet aggregation, anti-atherosclerosis, anti-oxidant, preventing and treating hyperlipidemia, and coronary heart diseases (<xref ref-type="bibr" rid="B64">Qin and Sun, 2005</xref>; <xref ref-type="bibr" rid="B33">Hung and Wu, 2016</xref>; <xref ref-type="bibr" rid="B7">Chen et al., 2021</xref>; <xref ref-type="bibr" rid="B13">Ding et al., 2018</xref>). In cardiovascular effects, (2S)-naringenin (<xref ref-type="fig" rid="F13">Figure 13e</xref>), as one of the active metabolites from <italic>Typha angustifolia</italic> L. (Puhuang), could suppress vascular smooth muscle cell proliferation induced platelet-derived growth factor receptor &#x3b2; through a G<sub>0</sub>/G<sub>1</sub> arrest. This might be useful in managing vascular restenosis and atherosclerosis (<xref ref-type="bibr" rid="B38">Lee et al., 2012</xref>). And <italic>Typha angustifolia</italic> L. (Puhuang) also consisted mainly of the Korean herbal medicine Silsosangami. It reduced the expression of inducible nitric oxide synthase and cyclooxygenase-2, inhibited neutrophil activities, and produced prostaglandin E2 and nitric oxide. It also possessed anti-inflammatory properties (<xref ref-type="bibr" rid="B62">Park et al., 2004</xref>). Besides, another study demonstrated that <italic>Typha angustifolia</italic> L. (Puhuang) could upregulate the expression of kdr, flt1, and VEGFA to display the pro-angiogenic effect (<xref ref-type="bibr" rid="B21">Gao et al., 2021</xref>).</p>
<p>However, it should be acknowledged that the current attempt to clarify the pharmacological links between traditional therapeutic concepts and the findings has inherent limitations, which require systematic elaboration. This study primarily focuses on the concept of replenishing qi and activating blood circulation, and explores its potential association with specific pharmacological mechanisms, such as the regulation of energy metabolism pathways and the enhancement of immune function. To some extent, it reflects a reductionist tendency, which simplifies the complex, holistic traditional concept into measurable biological indicators, leading to an incomplete understanding of its connotations. Therefore, the findings of this study should be interpreted with caution. They only reflect a preliminary association between a certain pharmacological mechanism and one aspect of replenishing qi and activating blood circulation, rather than a comprehensive explanation. Future research needs to integrate multi-omics approaches, establish more systematic experimental models, and combine clinical syndrome differentiation data to further explore the complex links between traditional therapeutic concepts and modern pharmacology, thereby avoiding the narrow interpretation caused by over-reliance on reductionist methods. In the present study, replenishing qi and activating blood circulation emerge as a potential therapeutic approach for mitigating the progression of hypertensive heart disease. However, its efficacy, underlying mechanisms, and optimal clinical application scenarios warrant further in-depth investigation in future research to validate its therapeutic value and clarify its role within a broader context of treatment strategies.</p>
</sec>
<sec id="s4-4">
<title>4.4 Comparison to previous systematic review evidence</title>
<p>The differences from other systematic reviews (<xref ref-type="bibr" rid="B57">Mohammed et al., 2023</xref>; <xref ref-type="bibr" rid="B65">Ren et al., 2020</xref>; <xref ref-type="bibr" rid="B89">Xiong et al., 2019</xref>; <xref ref-type="bibr" rid="B98">Zhang et al., 2022</xref>) were given in the following three points. Firstly, in addition to BP, other necessary objective outcome measures, including NYHA classification, LVEF, CO, E/A ratio, LVEDD, LVESD, LVMI, IVSTD, BNP, and adverse events, were used to assess the effect of TCM on HHD. That&#x2019;s the biggest difference compared to the previous research of TCM, which just focuses on hypertension. This meta-analysis focused on the impact of long-term hypertension on cardiac structure, function, and prognosis, with a particular emphasis on the progression from hypertension to HHD and HF, which had not been addressed in previous meta-analyses. Unfortunately, due to inadequate data in the included RCTs, long-term outcome endpoints such as cardiovascular death, HF incidence, hospitalization, and all-cause mortality were not investigated in this analysis. Secondly, the included studies did not place limitations on the TCM formula. Oral dose forms were the only available for TCM, including decoctions, pills, granules, and capsules. In contrast to conventional medicine, TCM has a long tradition of using food as medication. The third and fourth most often used Chinese botanical drugs in this meta-analysis, <italic>P. montana</italic> var. <italic>lobata</italic> (Willd.) Maesen &#x26; S.M.Almeida ex Sanjappa &#x26; Predeep (Gegen) and <italic>A. mongholicus</italic> Bunge (Huangqi), were found in the National Health Commission of the People&#x2019;s Republic of China&#x2019;s list of items that were &#x2018;both food and medicine&#x2019; (also known as &#x2018;medicine and food come from the same source&#x2019; or &#x2018;medicine food homology,&#x2019; or MFH) (<xref ref-type="bibr" rid="B59">National Health Commission of the People&#x2019;s Republic of China, 2023</xref>; <xref ref-type="bibr" rid="B58">National Health Commission of the People&#x2019;s Republic of China, 2022</xref>). The other four Chinese botanical drugs were found in the National Health Commission of the People&#x2019;s Republic of China&#x2019;s list of Chinese medicines that could be used as health food. The efficacy of oral TCM for HHD was comprehensively evaluated, and its edible safety was well-guaranteed. Thirdly, other strengths, such as adherence to the guidelines of PRISMA and the previously registered protocol in PROSPERO, were also worth mentioning. The GRADE system was used to assess the quality of supporting evidence, and the Cochrane Risk of Bias Tool was utilized to evaluate the risk of bias in the included studies to facilitate the creation of recommendations.</p>
</sec>
<sec id="s4-5">
<title>4.5 Limitations</title>
<p>First, despite our thorough search, every included RCT was only done in China, which limited the generalizability. Future randomized, double-blind, placebo-controlled RCTs with a longer-term duration are required. Second, this meta-analysis was subjected to methodological weaknesses of the original studies. Only one study reported allocation concealment that could result in selection bias, and one study described blinding of participants and personnel that could cause performance bias. Blinding of outcome assessment was not mentioned in any of the studies, which could result in detection bias. The majority of the included studies&#x2019; low quality had an impact on the accuracy of the results. Subsequent research endeavors ought to incorporate methods that mitigate the possibility of bias in reporting, like blinding result assessors, randomization, and allocation concealment. However, because TCM consists of many metabolites, conducting adequate blinding for TCM investigations may prove challenging. Moreover, many ancient forms, such as decoctions, pills, and powders, had special tastes and scents, which made it difficult to confirm that placebos were identical. More information is needed on the reported side effects, interactions, and general safety aspects of this preparation. Third, the onset and progression of HHD are complicated processes. To date, there are no guidelines or expert consensus providing recommendations on the stage of HHD. It is still difficult to recognize patients with hypertension at risk of developing HF in the long run promptly, even with the availability of targeted antihypertensive medications. Finally, because the included studies only provided a limited number of outcome indicators, this article was unable to assess the impact of TCM on HHD in its entirety. Thus, it is necessary to extend the follow-up time and conduct an RCT to identify the efficacy of TCM on HHD and observe the occurrence of long-term cardiovascular adverse events.</p>
</sec>
<sec id="s4-6">
<title>4.6 Future perspectives</title>
<p>The analysis we had done to reflect the changes in heart structure and function following HHD, but it was still not enough to show how this intricate shift in the development of HHD and HF occurs after hypertension. Further research should observe blood indicators for endothelial dysfunction, inflammation, and cardiac fibrosis, which could be analyzed to describe, track, and identify phenotypes that are at risk of developing HHD and HFpEF (<xref ref-type="bibr" rid="B18">Ekstr&#xf6;m et al., 2020</xref>). Additionally, TCM has been demonstrated to be an alternate and complementary strategy for both primary and secondary cardiovascular disease prevention (<xref ref-type="bibr" rid="B26">Hao et al., 2017</xref>). Typically, two or more botanical drugs are combined in a TCM recipe to create a synergistic effect. Botanical drug or botanical drug-pair interactions should be closely monitored from a clinical standpoint, particularly when several botanical drugs are utilized at once (<xref ref-type="bibr" rid="B101">Zuo et al., 2020</xref>). Our goal is to find new hypertension treatment strategies to prevent HF. More RCTs are required to evaluate how therapy of replenishing qi and activating blood circulation affects patients with HHD&#x2019;s long-term challenging endpoints. The results are expected to guide healthcare providers in hospitals to offer personalized treatment (<xref ref-type="bibr" rid="B18">Ekstr&#xf6;m et al., 2020</xref>).</p>
</sec>
</sec>
<sec sec-type="conclusion" id="s5">
<title>5 Conclusion</title>
<p>In general, the results of this meta-analysis suggested that the use of TCM and WM together may be more effective than using WM alone in the treatment of HHD. This combination might also reduce unfavorable LV remodeling and enhance cardiac systolic and diastolic function, which might slow the disease&#x2019;s progression. In addition to being a new approach to treating hypertension to avoid HF, therapy of replenishing qi and activating blood circulation offers a reference as an auxiliary treatment for secondary prevention following HHD. However, it was important to interpret these results cautiously, considering the limitations of the original trials. To support this clinical evidence, more rigorous trials for herbal therapy are advised.</p>
</sec>
<sec id="s6">
<title>6 Chemical metabolites studied in this article</title>
<p>Salvianolic acid A (PubChem CID: 5281793); 2,3,5,6-Tetramethylpyrazine (PubChem CID: 14296); Puerarin (PubChem CID: 5281807); Astragaloside IV (PubChem CID: 13943297); (2S)-naringenin (PubChem CID: 439246).</p>
</sec>
</body>
<back>
<sec sec-type="data-availability" id="s7">
<title>Data availability statement</title>
<p>The original contributions presented in the study are included in the article/<xref ref-type="sec" rid="s13">Supplementary Material</xref>, further inquiries can be directed to the corresponding authors.</p>
</sec>
<sec sec-type="author-contributions" id="s8">
<title>Author contributions</title>
<p>JH: Conceptualization, Data curation, Software, Visualization, Writing &#x2013; original draft. YW: Conceptualization, Formal Analysis, Investigation, Methodology, Writing &#x2013; original draft. FX: Formal Analysis, Funding acquisition, Resources, Supervision, Validation, Visualization, Writing &#x2013; review &#x26; editing. JZ: Funding acquisition, Methodology, Resources, Supervision, Validation, Visualization, Writing &#x2013; review &#x26; editing.</p>
</sec>
<sec sec-type="funding-information" id="s9">
<title>Funding</title>
<p>The author(s) declare that financial support was received for the research and/or publication of this article. This work was supported by the Department of Medical Administration of the National Administration of Traditional Chinese Medicine: Preventive intervention program for chronic diseases (ZYZB-2020-196), National Natural Science Foundation of China (No. 81904195), and the Qihuang Project for Inheritance and Innovation of Traditional Chinese Medicine. The funder had no role in the study design, data analysis, or decision to publish.</p>
</sec>
<sec sec-type="COI-statement" id="s10">
<title>Conflict of interest</title>
<p>The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.</p>
</sec>
<sec sec-type="ai-statement" id="s11">
<title>Generative AI statement</title>
<p>The author(s) declare that no Generative AI was used in the creation of this manuscript.</p>
<p>Any alternative text (alt text) provided alongside figures in this article has been generated by Frontiers with the support of artificial intelligence and reasonable efforts have been made to ensure accuracy, including review by the authors wherever possible. If you identify any issues, please contact us.</p>
</sec>
<sec sec-type="disclaimer" id="s12">
<title>Publisher&#x2019;s note</title>
<p>All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.</p>
</sec>
<sec sec-type="supplementary-material" id="s13">
<title>Supplementary material</title>
<p>The Supplementary Material for this article can be found online at: <ext-link ext-link-type="uri" xlink:href="https://www.frontiersin.org/articles/10.3389/fphar.2025.1506234/full#supplementary-material">https://www.frontiersin.org/articles/10.3389/fphar.2025.1506234/full&#x23;supplementary-material</ext-link>
</p>
<supplementary-material xlink:href="Table1.docx" id="SM1" mimetype="application/docx" xmlns:xlink="http://www.w3.org/1999/xlink"/>
<supplementary-material xlink:href="Table2.docx" id="SM2" mimetype="application/docx" xmlns:xlink="http://www.w3.org/1999/xlink"/>
</sec>
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<surname>Fan</surname>
<given-names>M.</given-names>
</name>
<name>
<surname>Fan</surname>
<given-names>R.</given-names>
</name>
<name>
<surname>Yao</surname>
<given-names>W.</given-names>
</name>
<name>
<surname>Deng</surname>
<given-names>Z.</given-names>
</name>
<name>
<surname>Tian</surname>
<given-names>Z.</given-names>
</name>
<etal/>
</person-group> (<year>2019</year>). <article-title>Effect of Yifengyangtongluo prescription on the improvement of traditional Chinese medicine syndrome and heart function of hypertensive heart disease with Yang deficiency and collateral-blocking type</article-title>. <source>Chin. J. Tradit. Med. Sci. Technol.</source> <volume>26</volume> (<issue>01</issue>), <fpage>54</fpage>&#x2013;<lpage>55</lpage>.</citation>
</ref>
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<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Zuo</surname>
<given-names>H. L.</given-names>
</name>
<name>
<surname>Linghu</surname>
<given-names>K. G.</given-names>
</name>
<name>
<surname>Wang</surname>
<given-names>Y. L.</given-names>
</name>
<name>
<surname>Liu</surname>
<given-names>K. M.</given-names>
</name>
<name>
<surname>Gao</surname>
<given-names>Y.</given-names>
</name>
<name>
<surname>Yu</surname>
<given-names>H.</given-names>
</name>
<etal/>
</person-group> (<year>2020</year>). <article-title>Interactions of antithrombotic herbal medicines with Western cardiovascular drugs</article-title>. <source>Pharmacol. Res.</source> <volume>159</volume>, <fpage>104963</fpage>. <pub-id pub-id-type="doi">10.1016/j.phrs.2020.104963</pub-id>
<pub-id pub-id-type="pmid">32497719</pub-id>
</citation>
</ref>
</ref-list>
<sec id="s14">
<title>Glossary</title>
<def-list>
<def-item>
<term id="G1-fphar.2025.1506234">
<bold>ACE2</bold>
</term>
<def>
<p>angiotensin-converting enzyme 2</p>
</def>
</def-item>
<def-item>
<term id="G2-fphar.2025.1506234">
<bold>ASP</bold>
</term>
<def>
<p>Astragalus polysaccharides</p>
</def>
</def-item>
<def-item>
<term id="G3-fphar.2025.1506234">
<bold>AT1</bold>
</term>
<def>
<p>angiotensin &#x2161; type 1 receptor</p>
</def>
</def-item>
<def-item>
<term id="G4-fphar.2025.1506234">
<bold>BNP</bold>
</term>
<def>
<p>B-type natriuretic peptide</p>
</def>
</def-item>
<def-item>
<term id="G5-fphar.2025.1506234">
<bold>BP</bold>
</term>
<def>
<p>blood pressure</p>
</def>
</def-item>
<def-item>
<term id="G6-fphar.2025.1506234">
<bold>C</bold>
</term>
<def>
<p>the control group</p>
</def>
</def-item>
<def-item>
<term id="G7-fphar.2025.1506234">
<bold>CI</bold>
</term>
<def>
<p>confidence interval</p>
</def>
</def-item>
<def-item>
<term id="G8-fphar.2025.1506234">
<bold>CNKI</bold>
</term>
<def>
<p>China National Knowledge Infrastructure</p>
</def>
</def-item>
<def-item>
<term id="G9-fphar.2025.1506234">
<bold>CO</bold>
</term>
<def>
<p>cardiac output</p>
</def>
</def-item>
<def-item>
<term id="G10-fphar.2025.1506234">
<bold>DBP</bold>
</term>
<def>
<p>diastolic blood pressure</p>
</def>
</def-item>
<def-item>
<term id="G11-fphar.2025.1506234">
<bold>E/A</bold>
</term>
<def>
<p>transmitral peak early diastolic velocity (E)/peak late diastolic velocity (A)</p>
</def>
</def-item>
<def-item>
<term id="G12-fphar.2025.1506234">
<bold>GDT</bold>
</term>
<def>
<p>Guideline Development Tool</p>
</def>
</def-item>
<def-item>
<term id="G13-fphar.2025.1506234">
<bold>GRADE</bold>
</term>
<def>
<p>Grading of Recommendations Assessment Development and Evaluation</p>
</def>
</def-item>
<def-item>
<term id="G14-fphar.2025.1506234">
<bold>HF</bold>
</term>
<def>
<p>heart failure</p>
</def>
</def-item>
<def-item>
<term id="G15-fphar.2025.1506234">
<bold>HFpEF</bold>
</term>
<def>
<p>heart failure with preserved ejection fraction</p>
</def>
</def-item>
<def-item>
<term id="G16-fphar.2025.1506234">
<bold>HHD</bold>
</term>
<def>
<p>hypertensive heart disease</p>
</def>
</def-item>
<def-item>
<term id="G17-fphar.2025.1506234">
<bold>HM</bold>
</term>
<def>
<p>herbal medicine</p>
</def>
</def-item>
<def-item>
<term id="G18-fphar.2025.1506234">
<bold>IVSTD</bold>
</term>
<def>
<p>interventricular septum thickness in diastole</p>
</def>
</def-item>
<def-item>
<term id="G19-fphar.2025.1506234">
<bold>LV</bold>
</term>
<def>
<p>left ventricular</p>
</def>
</def-item>
<def-item>
<term id="G20-fphar.2025.1506234">
<bold>LVEDD</bold>
</term>
<def>
<p>left ventricular end-diastolic diameter</p>
</def>
</def-item>
<def-item>
<term id="G21-fphar.2025.1506234">
<bold>LVEF</bold>
</term>
<def>
<p>left ventricular ejection fraction</p>
</def>
</def-item>
<def-item>
<term id="G22-fphar.2025.1506234">
<bold>LVESD</bold>
</term>
<def>
<p>left ventricular end-systolic diameter</p>
</def>
</def-item>
<def-item>
<term id="G23-fphar.2025.1506234">
<bold>LVH</bold>
</term>
<def>
<p>left ventricular hypertrophy</p>
</def>
</def-item>
<def-item>
<term id="G24-fphar.2025.1506234">
<bold>LVMI</bold>
</term>
<def>
<p>left ventricular mass index</p>
</def>
</def-item>
<def-item>
<term id="G25-fphar.2025.1506234">
<bold>MD</bold>
</term>
<def>
<p>mean difference</p>
</def>
</def-item>
<def-item>
<term id="G26-fphar.2025.1506234">
<bold>NR</bold>
</term>
<def>
<p>not reported</p>
</def>
</def-item>
<def-item>
<term id="G27-fphar.2025.1506234">
<bold>NYHA</bold>
</term>
<def>
<p>New York Heart Association</p>
</def>
</def-item>
<def-item>
<term id="G28-fphar.2025.1506234">
<bold>PRISMA</bold>
</term>
<def>
<p>Preferred Reporting Items for Systematic Reviews and Meta-Analyses</p>
</def>
</def-item>
<def-item>
<term id="G29-fphar.2025.1506234">
<bold>RAAS</bold>
</term>
<def>
<p>renin-angiotensin-aldosterone system</p>
</def>
</def-item>
<def-item>
<term id="G30-fphar.2025.1506234">
<bold>RCTs</bold>
</term>
<def>
<p>randomized controlled trials</p>
</def>
</def-item>
<def-item>
<term id="G31-fphar.2025.1506234">
<bold>RR</bold>
</term>
<def>
<p>risk ratio</p>
</def>
</def-item>
<def-item>
<term id="G32-fphar.2025.1506234">
<bold>SBP</bold>
</term>
<def>
<p>systolic blood pressure</p>
</def>
</def-item>
<def-item>
<term id="G33-fphar.2025.1506234">
<bold>SinoMed</bold>
</term>
<def>
<p>Chinese Biomedical Database</p>
</def>
</def-item>
<def-item>
<term id="G34-fphar.2025.1506234">
<bold>SMD</bold>
</term>
<def>
<p>standardized mean difference</p>
</def>
</def-item>
<def-item>
<term id="G35-fphar.2025.1506234">
<bold>T</bold>
</term>
<def>
<p>the TCM group</p>
</def>
</def-item>
<def-item>
<term id="G36-fphar.2025.1506234">
<bold>TCM</bold>
</term>
<def>
<p>traditional Chinese medicine</p>
</def>
</def-item>
<def-item>
<term id="G37-fphar.2025.1506234">
<bold>VIP</bold>
</term>
<def>
<p>Chinese Scientific Journal Database (Chinese VIP Information)</p>
</def>
</def-item>
<def-item>
<term id="G38-fphar.2025.1506234">
<bold>WHO</bold>
</term>
<def>
<p>World Health Organization</p>
</def>
</def-item>
<def-item>
<term id="G39-fphar.2025.1506234">
<bold>WM</bold>
</term>
<def>
<p>Western medicine</p>
</def>
</def-item>
</def-list>
</sec>
</back>
</article>