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<front>
<journal-meta>
<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>
<publisher>
<publisher-name>Frontiers Media S.A.</publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="publisher-id">741094</article-id>
<article-id pub-id-type="doi">10.3389/fphar.2021.741094</article-id>
<article-categories>
<subj-group subj-group-type="heading">
<subject>Pharmacology</subject>
<subj-group>
<subject>Original Research</subject>
</subj-group>
</subj-group>
</article-categories>
<title-group>
<article-title>Long-Term Use of Statins Lowering the Risk of Rehospitalization Caused by Ischemic Stroke Among Middle-Aged Hyperlipidemic Patients: A Population-Based Study</article-title>
<alt-title alt-title-type="left-running-head">Yin et&#x20;al.</alt-title>
<alt-title alt-title-type="right-running-head">Rosuvastatin Decreased Ischemic Stroke</alt-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname>Yin</surname>
<given-names>Jiu-Haw</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
<xref ref-type="fn" rid="fn1">
<sup>&#x2020;</sup>
</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Peng</surname>
<given-names>Giia-Sheun</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
<xref ref-type="fn" rid="fn1">
<sup>&#x2020;</sup>
</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Chen</surname>
<given-names>Kang-Hua</given-names>
</name>
<xref ref-type="aff" rid="aff3">
<sup>3</sup>
</xref>
<xref ref-type="aff" rid="aff4">
<sup>4</sup>
</xref>
<xref ref-type="fn" rid="fn1">
<sup>&#x2020;</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/1509655/overview"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Chu</surname>
<given-names>Chi-Ming</given-names>
</name>
<xref ref-type="aff" rid="aff5">
<sup>5</sup>
</xref>
<xref ref-type="aff" rid="aff6">
<sup>6</sup>
</xref>
<xref ref-type="aff" rid="aff7">
<sup>7</sup>
</xref>
<xref ref-type="aff" rid="aff8">
<sup>8</sup>
</xref>
<xref ref-type="aff" rid="aff9">
<sup>9</sup>
</xref>
<xref ref-type="fn" rid="fn1">
<sup>&#x2020;</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/1446575/overview"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Chien</surname>
<given-names>Wu-Chien</given-names>
</name>
<xref ref-type="aff" rid="aff10">
<sup>10</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/416035/overview"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Kao</surname>
<given-names>Li-Ting</given-names>
</name>
<xref ref-type="aff" rid="aff5">
<sup>5</sup>
</xref>
<xref ref-type="aff" rid="aff11">
<sup>11</sup>
</xref>
<xref ref-type="aff" rid="aff12">
<sup>12</sup>
</xref>
<xref ref-type="aff" rid="aff13">
<sup>13</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/708262/overview"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Wu</surname>
<given-names>Chia-Chao</given-names>
</name>
<xref ref-type="aff" rid="aff14">
<sup>14</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/879786/overview"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Yang</surname>
<given-names>Chih-Wei</given-names>
</name>
<xref ref-type="aff" rid="aff15">
<sup>15</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/1422742/overview"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Tsai</surname>
<given-names>Wen-Chiuan</given-names>
</name>
<xref ref-type="aff" rid="aff16">
<sup>16</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/877932/overview"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Lin</surname>
<given-names>Wei-Zhi</given-names>
</name>
<xref ref-type="aff" rid="aff13">
<sup>13</sup>
</xref>
<xref ref-type="aff" rid="aff17">
<sup>17</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/1461892/overview"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Wu</surname>
<given-names>Yi-Syuan</given-names>
</name>
<xref ref-type="aff" rid="aff13">
<sup>13</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/1509550/overview"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Lin</surname>
<given-names>Hung-Che</given-names>
</name>
<xref ref-type="aff" rid="aff18">
<sup>18</sup>
</xref>
<xref ref-type="aff" rid="aff19">
<sup>19</sup>
</xref>
<xref ref-type="aff" rid="aff20">
<sup>20</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/660309/overview"/>
</contrib>
<contrib contrib-type="author" corresp="yes">
<name>
<surname>Chang</surname>
<given-names>Yu-Tien</given-names>
</name>
<xref ref-type="aff" rid="aff5">
<sup>5</sup>
</xref>
<xref ref-type="corresp" rid="c001">&#x2a;</xref>
<uri xlink:href="https://loop.frontiersin.org/people/1406540/overview"/>
</contrib>
</contrib-group>
<aff id="aff1">
<label>
<sup>1</sup>
</label>Department of Neurology, Tri-Service General Hospital, National Defense Medical Center, <addr-line>Taipei</addr-line>, <country>Taiwan</country>
</aff>
<aff id="aff2">
<label>
<sup>2</sup>
</label>Division of Neurology, Department of Internal Medicine, Taipei Veterans General Hospital, Hsinchu Branch, Hsinchu County, <addr-line>Taipei</addr-line>, <country>Taiwan</country>
</aff>
<aff id="aff3">
<label>
<sup>3</sup>
</label>Associate Professor, School of Nursing, College of Medicine, Chang Gung University, <addr-line>Taoyuan</addr-line>, <country>Taiwan</country>
</aff>
<aff id="aff4">
<label>
<sup>4</sup>
</label>Associate Research Fellow, Department of Nursing, Chang Gung Memorial Hospital, Tao-Yuan Branch, <addr-line>Taoyuan</addr-line>, <country>Taiwan</country>
</aff>
<aff id="aff5">
<label>
<sup>5</sup>
</label>School of Public Health, National Defense Medical Center, <addr-line>Taipei</addr-line>, <country>Taiwan</country>
</aff>
<aff id="aff6">
<label>
<sup>6</sup>
</label>Department of Surgery, Songshan Branch of Tri-Service General Hospital, National Defense Medical Center, <addr-line>Taipei</addr-line>, <country>Taiwan</country>
</aff>
<aff id="aff7">
<label>
<sup>7</sup>
</label>Division of Biostatistics and Informatics, Department of Epidemiology, School of Public Health, National Defense Medical Center, <addr-line>Taipei</addr-line>, <country>Taiwan</country>
</aff>
<aff id="aff8">
<label>
<sup>8</sup>
</label>Department of Public Health, China Medical University, <addr-line>Taichung</addr-line>, <country>Taiwan</country>
</aff>
<aff id="aff9">
<label>
<sup>9</sup>
</label>Department of Healthcare Administration and Medical Informatics College of Health Sciences, Kaohsiung Medical University, <addr-line>Kaohsiung</addr-line>, <country>Taiwan</country>
</aff>
<aff id="aff10">
<label>
<sup>10</sup>
</label>Department of Medical Research, Tri-Service General Hospital, National Defense Medical Center, <addr-line>Taipei</addr-line>, <country>Taiwan</country>
</aff>
<aff id="aff11">
<label>
<sup>11</sup>
</label>Department of Pharmacy Practice, Tri-Service General Hospital, <addr-line>Taipei</addr-line>, <country>Taiwan</country>
</aff>
<aff id="aff12">
<label>
<sup>12</sup>
</label>School of Pharmacy, National Defense Medical Center, <addr-line>Taipei</addr-line>, <country>Taiwan</country>
</aff>
<aff id="aff13">
<label>
<sup>13</sup>
</label>Graduate Institute of Life Sciences, National Defense Medical Center, <addr-line>Taipei</addr-line>, <country>Taiwan</country>
</aff>
<aff id="aff14">
<label>
<sup>14</sup>
</label>Division of Nephrology, Department of Medicine, Tri-Service General Hospital, National Defense Medical Center, <addr-line>Taipei</addr-line>, <country>Taiwan</country>
</aff>
<aff id="aff15">
<label>
<sup>15</sup>
</label>Division of Gastroenterology, Department of Internal Medicine, Tri-Service General Hospital, National Defense Medical Center, <addr-line>Taipei</addr-line>, <country>Taiwan</country>
</aff>
<aff id="aff16">
<label>
<sup>16</sup>
</label>Department of Pathology, Tri-Service General Hospital, National Defense Medical Center, <addr-line>Taipei</addr-line>, <country>Taiwan</country>
</aff>
<aff id="aff17">
<label>
<sup>17</sup>
</label>School of Medicine, National Defense Medical Center, <addr-line>Taipei</addr-line>, <country>Taiwan</country>
</aff>
<aff id="aff18">
<label>
<sup>18</sup>
</label>Graduate Institute of Medical Sciences, National Defense Medical Center, <addr-line>Taipei</addr-line>, <country>Taiwan</country>
</aff>
<aff id="aff19">
<label>
<sup>19</sup>
</label>Department of Otolaryngology-Head and Neck Surgery, Tri-Service General Hospital, National Defense Medical Center, <addr-line>Taipei</addr-line>, <country>Taiwan</country>
</aff>
<aff id="aff20">
<label>
<sup>20</sup>
</label>Hualien Armed Forces General Hospital, <addr-line>Hualien</addr-line>, <country>Taiwan</country>
</aff>
<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/1126979/overview">Paul Scuffham</ext-link>, Griffith University, Australia</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/716449/overview">Jun-Jun Yeh</ext-link>, Ditmanson Medical Foundation Chia-Yi Christian Hospital, Taiwan</p>
<p>
<ext-link ext-link-type="uri" xlink:href="https://loop.frontiersin.org/people/483892/overview">Marc Henri De Longueville</ext-link>, UCB Pharma, Belgium</p>
</fn>
<corresp id="c001">&#x2a;Correspondence: Yu-Tien Chang, <email>greengarden720925@gmail.com</email>
</corresp>
<fn fn-type="equal" id="fn1">
<label>
<sup>&#x2020;</sup>
</label>
<p>These authors have contributed equally to this&#x20;work</p>
</fn>
<fn fn-type="other">
<p>This article was submitted to Drugs Outcomes Research and Policies, a section of the journal Frontiers in Pharmacology</p>
</fn>
</author-notes>
<pub-date pub-type="epub">
<day>18</day>
<month>10</month>
<year>2021</year>
</pub-date>
<pub-date pub-type="collection">
<year>2021</year>
</pub-date>
<volume>12</volume>
<elocation-id>741094</elocation-id>
<history>
<date date-type="received">
<day>14</day>
<month>07</month>
<year>2021</year>
</date>
<date date-type="accepted">
<day>14</day>
<month>09</month>
<year>2021</year>
</date>
</history>
<permissions>
<copyright-statement>Copyright &#xa9; 2021 Yin, Peng, Chen, Chu, Chien, Kao, Wu, Yang, Tsai, Lin, Wu, Lin and Chang.</copyright-statement>
<copyright-year>2021</copyright-year>
<copyright-holder>Yin, Peng, Chen, Chu, Chien, Kao, Wu, Yang, Tsai, Lin, Wu, Lin and Chang</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&#x20;terms.</p>
</license>
</permissions>
<abstract>
<p>
<bold>Background:</bold> The long-term effects of statin use on rehospitalization due to ischemic stroke (reHospIS) in hyperlipidemic patients are still unknown. Therefore, we aimed to assess the long-term risks of reHospIS for hyperlipidemic patients who were taking statins and nonstatin lipid-lowering medicines on a regular&#x20;basis.</p>
<p>
<bold>Methods and Materials:</bold> The National Health Insurance Research Database in Taiwan was used to conduct a 6-year cohort study of patients &#x3e;45&#xa0;years old (<italic>n</italic>&#x20;&#x3d; 9,098) who were newly diagnosed with hyperlipidemia and hospitalized for the first or second time due to ischemic stroke (IS). The risk of reHospIS was assessed using Cox proportional hazards regression&#x20;model.</p>
<p>
<bold>Results:</bold> Nonstatin lipid-lowering medicines regular users were associated with a higher risk of reHospIS compared to stains users (hazard ratio, HR &#x3d; 1.29&#x2013;1.39, <italic>p</italic>&#x20;&#x3c; 0.05). Rosuvastatin was the most preferred lipid-lowering medicine with lower HRs of reHospIS in hyperlipidemic patients whether they developed diabetes or not. Bezafibrate regular users of hyperlipidemic patients developing diabetes (HR &#x3d; 2.15, <italic>p</italic>&#x20;&#x3c; 0.01) had nearly 50% lower reHospIS risks than those without diabetes (HR &#x3d; 4.27, <italic>p</italic>&#x20;&#x3c; 0.05). Age, gender, drug dosage, comorbidities of diabetes and heart failure (HF), and characteristics of the first hospitalization due to IS were all adjusted in models. Moreover, increasing trends of HRs of reHospIS were observed from Rosuvastatin, nonstatin lipid-lowering medicines, Lovastatin, and Gemfibrozil to Bezafibrate&#x20;users.</p>
<p>
<bold>Conclusion:</bold> Statins were associated with long-term secondary prevention of reHospIS for hyperlipidemic patients. Rosuvastatin seemed to have the best protective effects. On the other hand, Bezafibrate appears to be beneficial for hyperlipidemic patients developing diabetes. Further research into the combination treatment of statin and nonstatin lipid-lowering medicines in hyperlipidemic patients developing diabetes is warranted.</p>
</abstract>
<kwd-group>
<kwd>statins</kwd>
<kwd>lipid-lowering medicines</kwd>
<kwd>rehospitalization</kwd>
<kwd>hyperlipidemia</kwd>
<kwd>ischemic stroke</kwd>
<kwd>secondary prevention</kwd>
<kwd>diabetes mellitus</kwd>
</kwd-group>
</article-meta>
</front>
<body>
<sec id="s1">
<title>Introduction</title>
<p>Hyperlipidemia is one of the most prevalent risk factors for atherosclerosis and cardioembolic stroke (<xref ref-type="bibr" rid="B3">Ayata et&#x20;al., 2013</xref>), particularly in patients with high LDL cholesterol (<xref ref-type="bibr" rid="B8">Farnier and Davignon, 1998</xref>; <xref ref-type="bibr" rid="B19">MF, 2021</xref>). Ischemic stroke (IS) is a major cause of morbidity and mortality. Elevated LDL levels appear to increase the risk of IS (<xref ref-type="bibr" rid="B29">Tziomalos et&#x20;al., 2009</xref>). Treatment of hyperlipidemia is helpful in both primary and secondary prevention of coronary heart disease and stroke (<xref ref-type="bibr" rid="B2">Arshad, 2014</xref>).</p>
<p>Statins (3-hydroxy-3-methylglutaryl coenzyme A reductase inhibitors) are the most commonly prescribed lipid-lowering medicines (<xref ref-type="bibr" rid="B4">Bonetti et&#x20;al., 2003</xref>). They have been shown to reduce the risk of IS in patients with a history of IS (<xref ref-type="bibr" rid="B29">Tziomalos et&#x20;al., 2009</xref>) via the lipid-lowering effect (<xref ref-type="bibr" rid="B8">Farnier and Davignon, 1998</xref>) and the reduction of platelet activation and reactivity (<xref ref-type="bibr" rid="B25">Pawelczyk et&#x20;al., 2015</xref>). Statin-based lipid lowering is effective for both primary and secondary prevention of IS (<xref ref-type="bibr" rid="B20">Milionis et&#x20;al., 2020</xref>; <xref ref-type="bibr" rid="B36">Zhu et&#x20;al., 2020</xref>). In addition, statin pretreatment or use in the acute phase of IS improved outcomes for recurrence, cardiovascular events (<xref ref-type="bibr" rid="B8">Farnier and Davignon, 1998</xref>; <xref ref-type="bibr" rid="B10">Flint et&#x20;al., 2012a</xref>; <xref ref-type="bibr" rid="B15">Kim et&#x20;al., 2014</xref>; <xref ref-type="bibr" rid="B23">O&#x2019;Brien et&#x20;al., 2015</xref>; <xref ref-type="bibr" rid="B13">Guo et&#x20;al., 2015</xref>; <xref ref-type="bibr" rid="B27">Scheitz et&#x20;al., 2015</xref>; <xref ref-type="bibr" rid="B33">Yeramaneni et&#x20;al., 2017</xref>; <xref ref-type="bibr" rid="B6">Cui et&#x20;al., 2020</xref>; <xref ref-type="bibr" rid="B12">Furlan et&#x20;al., 2020</xref>; <xref ref-type="bibr" rid="B30">Wang et&#x20;al., 2020</xref>), neurological disability, and all-cause and cardiovascular mortality (<xref ref-type="bibr" rid="B24">Orkaby et&#x20;al., 2020</xref>). Statins are the first-line LDL-lowering therapy in diabetic patients. Studies indicated that adding nonstatin lipid-lowering medicines to statins could improve the lipid profile (<xref ref-type="bibr" rid="B28">Scicali et&#x20;al., 2018</xref>) and reduce adverse cardiovascular events (<xref ref-type="bibr" rid="B21">NAEEM et&#x20;al., 2018</xref>) in diabetic individuals.</p>
<p>However, most previous studies (<xref ref-type="bibr" rid="B9">Flint et&#x20;al., 2012b</xref>; <xref ref-type="bibr" rid="B16">Koton et&#x20;al., 2012</xref>) compared the short-term protective effects of statin users, inpatient statin users, or pre-IS stroke statin users to statin-na&#xef;ve users. To the best of our knowledge, no long-term follow-up studies have been conducted to evaluate the risk of rehospitalization due to ischemic stroke (reHospIS) in hyperlipidemic patients with or without diabetes who were regularly taking statins or other nonstatin lipid-lowering medicines.</p>
</sec>
<sec sec-type="materials|methods" id="s2">
<title>Methods and Materials</title>
<sec id="s2-1">
<title>Study Population and Study Design</title>
<p>The coverage rate of National Health Insurance is nearly 100% in Taiwan. The analysis data is from the National Health Insurance Research Database (NHIRD) and capable of representing the whole nation. This is a cohort study and we included the medical claims from 2005 to 2010 in the ICD-9-CM system. During the study period in Taiwan, the clinical description guideline of lipid-lowering medicines was consistent. The eligible criteria of the study population were 1) the new patients with newly diagnosed disorders of lipid metabolism (ICD-9-CM code: 272), 2) the first hospitalization due to IS (ICD-9-CM code: 434 and 437 of inpatient medical records) from 2005 to 2009, 3) taking monolipid-lowering medicine over 90&#xa0;days and at least three times outpatient visits for hyperlipidemia after the first hospitalization due to IS, 4) age larger than 45&#xa0;years at which IS likely to occur (<xref ref-type="bibr" rid="B34">Yousufuddin and Young, 2019</xref>), 5) the period of time between first and second hospitalization larger than 1&#xa0;year, and 6) the defined daily dose (DDD) over zero. We excluded the inpatients 1) whose hospitalization cause was car incidents or suicide and 2) who were discharged from the hospitals for the reasons of suicide, death, or about to die. In the end, 9,098 patients are eligible (<xref ref-type="fig" rid="F1">Figure&#x20;1</xref>). To diminish the impact of baseline difference of putative confounders, we designed a 1-year washout period prior to the start of the study. Patients who were diagnosed with disorders of lipid metabolism (ICD-9-CM code: 272), ischemic diseases (ICD-9-CM code: 410&#x2013;414), or cerebrovascular diseases (ICD-9-CM code: 430&#x2013;438) or who were hospitalized due to IS in 2004 were excluded. Since 2001, the ICD-9-CM system had not been updated (<xref ref-type="bibr" rid="B1">Administration, 2014</xref>). Throughout the study period, the diagnosis classification system remained the same. This study was exempted from full review following consultation with the Tri-Service General Hospital Institutional Review Board (TSGH IRB No. B&#x2013;110&#x2013;22).</p>
<fig id="F1" position="float">
<label>FIGURE 1</label>
<caption>
<p>Study workflow.</p>
</caption>
<graphic xlink:href="fphar-12-741094-g001.tif"/>
</fig>
</sec>
<sec id="s2-2">
<title>Blood Lipid-Lowering Medicines</title>
<p>Nine blood lipid-lowering medicines were included (Atorvastatin, Rosuvastatin, Simvastatin, Lovastatin, Pravastatin, Fluvastatin, Bezafibrate, Gemfibrozil, and Fenofibrate). In order to understand the effects of various types of lipid-lowering medicines on the risks of reHospIS, all hyperlipidemic patients were divided into four subgroups according to the type of monolipid-lowering medicine they used on a regular basis: (A) nonstatin lipid-lowering medicines and statins regular users; (B) high-density statins (Atorvastatin, Rosuvastatin, and Simvastatin), nonstatin lipid-lowering medicines (Bezafibrate, Gemfibrozil, and Fenofibrate), and statins regular users; (C) Rosuvastatin, Simvastatin, Lovastatin, Pravastatin, Fluvastatin, Bezafibrate, Gemfibrozil, Fenofibrate, and Atorvastatin regular users; (D) five individual statins (Rosuvastatin, Simvastatin, Lovastatin, Pravastatin, and Fluvastatin) and nonstatin lipid-lowering medicine regular&#x20;users.</p>
</sec>
<sec id="s2-3">
<title>The Definition of Monolipid-Lowering Medicine Regular Users</title>
<p>Patients who had been prescribed a single type of lipid-lowering medicine for more than 90&#xa0;days and had at least three times records of outpatient visits from the first hospitalization due to IS to the end of follow-up were classified as monolipid-lowering medicine regular users. In order to clarify the effect of every single type of medication on rehospitalization, patients who used different types of blood lipid-lowering medicines in combination were excluded.</p>
</sec>
<sec id="s2-4">
<title>The Definition of DDD, Compliance Rate, and Comorbidity Diseases</title>
<p>The definition of DDD from WHO is the assumed average maintenance dose per day for a drug used for its main indication in adults. The DDD is a unit of measurement and does not necessarily reflect the recommended or prescribed daily dose (<xref ref-type="bibr" rid="B32">WHO, 2020</xref>). The values ranged from 0 to 1. The DDD was calculated between the first hospitalization date due to IS and the end of follow-up.</p>
<p>Compliance rates of lipid-lowering medicines were calculated as the number of days with lipid-lowering medicines supply divided by the total number of days from the first hospitalization date due to IS to the end of follow-up (<xref ref-type="bibr" rid="B31">Wei et&#x20;al., 2002</xref>).</p>
<p>In NHIRD, there is a risk of misclassification bias due to unverified diagnosis coding (<xref ref-type="bibr" rid="B14">Hsieh et&#x20;al., 2019</xref>). As a result, we defined diabetes mellitus (DM) hyperlipidemic patients as those who received medications of comorbidity diseases for over 90&#xa0;days after the first hospitalization due to IS were defined as having such comorbidity disease. We included the already known comorbidity diseases to IS, i.e.,&#x20;high blood pressure, angina, DM, HF, peripheral arterial occlusion disease, and arrhythmics. Type II diabetes accounted for 99 percent of all diabetes cases in Taiwan. As a result, diabetes was not divided into type I and type II diabetes (<xref ref-type="bibr" rid="B22">National Institutes of He, 2019</xref>).</p>
</sec>
<sec id="s2-5">
<title>Statistical Analysis</title>
<p>We used a univariable Cox proportional hazards regression model to explore the association of all indicators, including lipid-blood lowering medicines, characteristics of hospitals, cost of hospitalization, demographic characteristics, and comorbidity diseases with reHospIS. Multiple prediction models of lipid-blood lowering medicines on reHospIS were constructed under the adjustment of significant covariates or confounders by using multivariable Cox proportional hazard model regression. The level of statistical significance was set to be a two-sided <italic>p</italic> value less than 0.05. In the sensitivity analysis, all the hyperlipidemic patients were categorized into four patient subgroups of 1) all hyperlipidemic patients, 2) hyperlipidemic patients with diabetes, 3) nondiabetes hyperlipidemic patients, and 4) nondiabetes and non-HF hyperlipidemic patients. The case number of hyperlipidemic patients with HF was limited (<italic>n</italic>&#x20;&#x3d; 99) for further subgrouping and meaningful multivariable statistical analysis (<xref ref-type="table" rid="T1">Table&#x20;1</xref>). Therefore, we did not group study patients by HF. However, we wanted to know the lipid-lowering effects for hyperlipidemic patients without these two comorbidity diseases, and we presented the subgroup of nondiabetes and non-HF hyperlipidemic patients.</p>
<table-wrap id="T1" position="float">
<label>TABLE 1</label>
<caption>
<p>Descriptive statistics of study population.</p>
</caption>
<table>
<thead valign="top">
<tr>
<th rowspan="3" align="left"/>
<th colspan="6" align="center">Rehospitalization due to ischemic stroke (<italic>n</italic>&#x20;&#x3d; 9,098)</th>
</tr>
<tr>
<th colspan="2" align="center">No (<italic>n</italic>&#x20;&#x3d; 8,530)</th>
<th colspan="2" align="center">Yes (<italic>n</italic>&#x20;&#x3d; 568)</th>
<th rowspan="2" align="center">Hazard ratio</th>
<th rowspan="2" align="center">
<italic>p</italic> values</th>
</tr>
<tr>
<th align="center">
<italic>N</italic>
</th>
<th align="center">%</th>
<th align="center">
<italic>n</italic>
</th>
<th align="center">%</th>
</tr>
</thead>
<tbody valign="top">
<tr>
<td align="left">Follow-up time (days, mean, and SD)</td>
<td align="char" char=".">1,241</td>
<td align="char" char=".">504</td>
<td align="char" char=".">935</td>
<td align="char" char=".">405</td>
<td align="left"/>
<td align="left"/>
</tr>
<tr>
<td colspan="7" align="left">Year of first-time hospitalization<sup>%</sup>
</td>
</tr>
<tr>
<td align="left">&#x2003;2005</td>
<td align="char" char=".">1,353</td>
<td align="char" char=".">0.16</td>
<td align="char" char=".">173</td>
<td align="char" char=".">0.30</td>
<td align="center">ref</td>
<td align="left"/>
</tr>
<tr>
<td align="left">&#x2003;2006</td>
<td align="char" char=".">1756</td>
<td align="char" char=".">0.21</td>
<td align="char" char=".">178</td>
<td align="char" char=".">0.31</td>
<td align="center">0.97</td>
<td align="char" char=".">0.80</td>
</tr>
<tr>
<td align="left">&#x2003;2007</td>
<td align="char" char=".">1836</td>
<td align="char" char=".">0.22</td>
<td align="char" char=".">137</td>
<td align="char" char=".">0.24</td>
<td align="center">1.02</td>
<td align="char" char=".">0.87</td>
</tr>
<tr>
<td align="left">&#x2003;2008</td>
<td align="char" char=".">1886</td>
<td align="char" char=".">0.22</td>
<td align="char" char=".">63</td>
<td align="char" char=".">0.11</td>
<td align="center">0.77</td>
<td align="char" char=".">0.09</td>
</tr>
<tr>
<td align="left">&#x2003;2009</td>
<td align="char" char=".">1,699</td>
<td align="char" char=".">0.20</td>
<td align="char" char=".">17</td>
<td align="char" char=".">0.03</td>
<td align="center">0.65</td>
<td align="char" char=".">0.11</td>
</tr>
<tr>
<td colspan="7" align="left">Demographic characteristics</td>
</tr>
<tr>
<td align="left">&#x2003;Age (year, mean, and SD)</td>
<td align="char" char=".">64</td>
<td align="char" char=".">11</td>
<td align="char" char=".">65</td>
<td align="char" char=".">10.00</td>
<td align="center">1.01</td>
<td align="center">&#x2a;</td>
</tr>
<tr>
<td align="left">&#x2003;Gender</td>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
</tr>
<tr>
<td align="left">&#x2003;&#x2003;Male</td>
<td align="char" char=".">4,963</td>
<td align="char" char=".">0.58</td>
<td align="char" char=".">350</td>
<td align="char" char=".">0.62</td>
<td align="center">ref</td>
<td align="left"/>
</tr>
<tr>
<td align="left">&#x2003;&#x2003;Female</td>
<td align="char" char=".">3,567</td>
<td align="char" char=".">0.42</td>
<td align="char" char=".">218</td>
<td align="char" char=".">0.38</td>
<td align="center">0.85</td>
<td align="char" char=".">0.06</td>
</tr>
<tr>
<td colspan="7" align="left">The total cost of first-time hospitalization due to ischemic stroke (United&#x20;States dollars)<sup>&#x26;</sup>
</td>
</tr>
<tr>
<td align="left">&#x2003;&#x3c;667</td>
<td align="char" char=".">2,348</td>
<td align="char" char=".">0.27</td>
<td align="char" char=".">144</td>
<td align="char" char=".">0.25</td>
<td align="center">ref</td>
<td align="left"/>
</tr>
<tr>
<td align="left">&#x2003;667&#x2013;1,000</td>
<td align="char" char=".">2,314</td>
<td align="char" char=".">0.27</td>
<td align="char" char=".">153</td>
<td align="char" char=".">0.27</td>
<td align="center">1.12</td>
<td align="char" char=".">0.34</td>
</tr>
<tr>
<td align="left">&#x2003;1,000&#x2013;1,333</td>
<td align="char" char=".">1,461</td>
<td align="char" char=".">0.17</td>
<td align="char" char=".">95</td>
<td align="char" char=".">0.17</td>
<td align="center">1.12</td>
<td align="char" char=".">0.38</td>
</tr>
<tr>
<td align="left">&#x2003;&#x2265;1,333</td>
<td align="char" char=".">2,407</td>
<td align="char" char=".">0.28</td>
<td align="char" char=".">176</td>
<td align="char" char=".">0.31</td>
<td align="center">1.27</td>
<td align="center">&#x2a;</td>
</tr>
<tr>
<td colspan="7" align="left">The total days of first-time hospitalization due to ischemic stroke</td>
</tr>
<tr>
<td align="left">&#x2003;&#x3c;4</td>
<td align="char" char=".">1,216</td>
<td align="char" char=".">0.14</td>
<td align="char" char=".">73</td>
<td align="char" char=".">0.13</td>
<td align="center">ref</td>
<td align="left"/>
</tr>
<tr>
<td align="left">&#x2003;4&#x2013;7</td>
<td align="char" char=".">2,963</td>
<td align="char" char=".">0.35</td>
<td align="char" char=".">176</td>
<td align="char" char=".">0.31</td>
<td align="center">1.00</td>
<td align="char" char=".">0.99</td>
</tr>
<tr>
<td align="left">&#x2003;7&#x2013;10</td>
<td align="char" char=".">1918</td>
<td align="char" char=".">0.22</td>
<td align="char" char=".">123</td>
<td align="char" char=".">0.22</td>
<td align="center">1.07</td>
<td align="char" char=".">0.63</td>
</tr>
<tr>
<td align="left">&#x2003;&#x2265;10</td>
<td align="char" char=".">2,433</td>
<td align="char" char=".">0.29</td>
<td align="char" char=".">196</td>
<td align="char" char=".">0.35</td>
<td align="center">1.33</td>
<td align="center">&#x2a;</td>
</tr>
<tr>
<td colspan="7" align="left">Hospital type</td>
</tr>
<tr>
<td align="left">&#x2003;Public</td>
<td align="char" char=".">1855</td>
<td align="char" char=".">0.22</td>
<td align="char" char=".">137</td>
<td align="char" char=".">0.24</td>
<td align="center">ref</td>
<td align="left"/>
</tr>
<tr>
<td align="left">&#x2003;Private</td>
<td align="char" char=".">1838</td>
<td align="char" char=".">0.22</td>
<td align="char" char=".">127</td>
<td align="char" char=".">0.22</td>
<td align="center">0.86</td>
<td align="char" char=".">0.23</td>
</tr>
<tr>
<td align="left">&#x2003;Nonprofit proprietary</td>
<td align="char" char=".">4,837</td>
<td align="char" char=".">0.57</td>
<td align="char" char=".">304</td>
<td align="char" char=".">0.54</td>
<td align="center">0.91</td>
<td align="char" char=".">0.36</td>
</tr>
<tr>
<td colspan="7" align="left">Hospital class</td>
</tr>
<tr>
<td align="left">&#x2003;Medical center</td>
<td align="char" char=".">3,546</td>
<td align="char" char=".">0.42</td>
<td align="char" char=".">205</td>
<td align="char" char=".">0.36</td>
<td align="center">ref</td>
<td align="left"/>
</tr>
<tr>
<td align="left">&#x2003;Regional hospital</td>
<td align="char" char=".">3,973</td>
<td align="char" char=".">0.47</td>
<td align="char" char=".">279</td>
<td align="char" char=".">0.49</td>
<td align="center">1.21</td>
<td align="center">&#x2a;</td>
</tr>
<tr>
<td align="left">&#x2003;District hospital</td>
<td align="char" char=".">1,011</td>
<td align="char" char=".">0.12</td>
<td align="char" char=".">84</td>
<td align="char" char=".">0.15</td>
<td align="center">1.34</td>
<td align="center">&#x2a;</td>
</tr>
<tr>
<td colspan="7" align="left">Location of hospitals</td>
</tr>
<tr>
<td align="left">&#x2003;Taipei capital</td>
<td align="char" char=".">2,356</td>
<td align="char" char=".">0.28</td>
<td align="char" char=".">144</td>
<td align="char" char=".">0.25</td>
<td align="center">ref</td>
<td align="left"/>
</tr>
<tr>
<td align="left">&#x2003;Northern</td>
<td align="char" char=".">1,144</td>
<td align="char" char=".">0.13</td>
<td align="char" char=".">85</td>
<td align="char" char=".">0.15</td>
<td align="center">1.20</td>
<td align="char" char=".">0.18</td>
</tr>
<tr>
<td align="left">&#x2003;Central</td>
<td align="char" char=".">1,347</td>
<td align="char" char=".">0.16</td>
<td align="char" char=".">98</td>
<td align="char" char=".">0.17</td>
<td align="center">1.19</td>
<td align="char" char=".">0.18</td>
</tr>
<tr>
<td align="left">&#x2003;Southern</td>
<td align="char" char=".">1,467</td>
<td align="char" char=".">0.17</td>
<td align="char" char=".">99</td>
<td align="char" char=".">0.17</td>
<td align="center">1.12</td>
<td align="char" char=".">0.38</td>
</tr>
<tr>
<td align="left">&#x2003;Southern remote</td>
<td align="char" char=".">1877</td>
<td align="char" char=".">0.22</td>
<td align="char" char=".">121</td>
<td align="char" char=".">0.21</td>
<td align="center">1.01</td>
<td align="char" char=".">0.95</td>
</tr>
<tr>
<td align="left">&#x2003;Eastern</td>
<td align="char" char=".">339</td>
<td align="char" char=".">0.04</td>
<td align="char" char=".">21</td>
<td align="char" char=".">0.04</td>
<td align="center">1.03</td>
<td align="char" char=".">0.90</td>
</tr>
<tr>
<td colspan="7" align="left">Compliance</td>
</tr>
<tr>
<td colspan="7" align="left">&#x2003;DDD</td>
</tr>
<tr>
<td align="left">&#x2003;&#x2003;&#x2264;0.1</td>
<td align="char" char=".">3,473</td>
<td align="char" char=".">0.41</td>
<td align="char" char=".">178</td>
<td align="char" char=".">0.31</td>
<td align="center">ref</td>
<td align="left"/>
</tr>
<tr>
<td align="left">&#x2003;&#x2003;0.1&#x2013;0.2</td>
<td align="char" char=".">2,523</td>
<td align="char" char=".">0.30</td>
<td align="char" char=".">182</td>
<td align="char" char=".">0.32</td>
<td align="center">1.94</td>
<td align="center">&#x2a;&#x2a;&#x2a;</td>
</tr>
<tr>
<td align="left">&#x2003;&#x2003;0.2&#x2013;0.3</td>
<td align="char" char=".">1248</td>
<td align="char" char=".">0.15</td>
<td align="char" char=".">84</td>
<td align="char" char=".">0.15</td>
<td align="center">2.06</td>
<td align="center">&#x2a;&#x2a;&#x2a;</td>
</tr>
<tr>
<td align="left">&#x2003;&#x2003;0.3&#x2013;0.4</td>
<td align="char" char=".">568</td>
<td align="char" char=".">0.07</td>
<td align="char" char=".">51</td>
<td align="char" char=".">0.09</td>
<td align="center">2.82</td>
<td align="center">&#x2a;&#x2a;&#x2a;</td>
</tr>
<tr>
<td align="left">&#x2003;&#x2003;0.4&#x2013;0.5</td>
<td align="char" char=".">320</td>
<td align="char" char=".">0.04</td>
<td align="char" char=".">18</td>
<td align="char" char=".">0.03</td>
<td align="center">1.95</td>
<td align="center">&#x2a;&#x2a;</td>
</tr>
<tr>
<td align="left">&#x2003;&#x2003;&#x3e;0.5</td>
<td align="char" char=".">398</td>
<td align="char" char=".">0.05</td>
<td align="char" char=".">55</td>
<td align="char" char=".">0.10</td>
<td align="center">4.79</td>
<td align="center">&#x2a;&#x2a;&#x2a;</td>
</tr>
<tr>
<td colspan="7" align="left">&#x2003;Compliance rate</td>
</tr>
<tr>
<td align="left">&#x2003;&#x2003;&#x2264;0.25</td>
<td align="char" char=".">5,220</td>
<td align="char" char=".">0.61</td>
<td align="char" char=".">318</td>
<td align="char" char=".">0.56</td>
<td align="center">ref</td>
<td align="left"/>
</tr>
<tr>
<td align="left">&#x2003;&#x2003;0.25&#x2013;0.5</td>
<td align="char" char=".">2,551</td>
<td align="char" char=".">0.30</td>
<td align="char" char=".">156</td>
<td align="char" char=".">0.27</td>
<td align="center">1.51</td>
<td align="center">&#x2a;&#x2a;&#x2a;</td>
</tr>
<tr>
<td align="left">&#x2003;&#x2003;&#x3e;0.5</td>
<td align="char" char=".">759</td>
<td align="char" char=".">.09</td>
<td align="char" char=".">94</td>
<td align="char" char=".">0.17</td>
<td align="center">3.16</td>
<td align="center">&#x2a;&#x2a;&#x2a;</td>
</tr>
<tr>
<td colspan="7" align="left">Comorbidities</td>
</tr>
<tr>
<td align="left">&#x2003;High blood pressure (HBP)</td>
<td align="char" char=".">6,066</td>
<td align="char" char=".">0.71</td>
<td align="char" char=".">412</td>
<td align="char" char=".">0.73</td>
<td align="center">0.90</td>
<td align="char" char=".">0.27</td>
</tr>
<tr>
<td align="left">&#x2003;Angina</td>
<td align="char" char=".">617</td>
<td align="char" char=".">0.07</td>
<td align="char" char=".">44</td>
<td align="char" char=".">0.08</td>
<td align="center">0.94</td>
<td align="char" char=".">0.71</td>
</tr>
<tr>
<td align="left">&#x2003;Diabetes mellitus (DM)</td>
<td align="char" char=".">2,840</td>
<td align="char" char=".">0.33</td>
<td align="char" char=".">240</td>
<td align="char" char=".">0.42</td>
<td align="center">1.31</td>
<td align="center">&#x2a;&#x2a;</td>
</tr>
<tr>
<td align="left">&#x2003;Heart failure (HF)</td>
<td align="char" char=".">87</td>
<td align="char" char=".">0.01</td>
<td align="char" char=".">12</td>
<td align="char" char=".">0.02</td>
<td align="center">1.85</td>
<td align="center">&#x2a;</td>
</tr>
<tr>
<td align="left">&#x2003;Peripheral arterial occlusion disease (PAOD)</td>
<td align="char" char=".">604</td>
<td align="char" char=".">0.07</td>
<td align="char" char=".">46</td>
<td align="char" char=".">0.08</td>
<td align="center">1.04</td>
<td align="char" char=".">0.80</td>
</tr>
<tr>
<td align="left">&#x2003;Arrhythmics</td>
<td align="char" char=".">78</td>
<td align="char" char=".">0.01</td>
<td align="char" char=".">8</td>
<td align="char" char=".">0.01</td>
<td align="center">1.52</td>
<td align="char" char=".">0.24</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn>
<p>&#x2a;&#x2a;&#x2a;<italic>p</italic> value &#x3c; 0.001, &#x2a;&#x2a;<italic>p</italic> value &#x3c; 0.01, &#x2a;<italic>p</italic> value &#x3c; 0.05. Statistical analysis was using univariable Cox proportional hazards regression. ref: reference group and The cost was converted from NT dollars to Unites States dollars at a 30 to one exchange rate. % The period between first hospitalization and second hospitalization due to ischemic stroke was set to be over 1&#xa0;year, thus no first hospitalization due to ischemic stroke was present in&#x20;2010.</p>
</fn>
</table-wrap-foot>
</table-wrap>
</sec>
</sec>
<sec sec-type="results" id="s3">
<title>Results</title>
<sec id="s3-1">
<title>The Risk Factors of reHospIS</title>
<p>Older age, male sex, higher total cost of first-time hospitalization, higher total days of first-time hospitalization, lower hospital class, developing diabetes and heart failure (HF), and higher DDD and compliance rate were the risk factors of reHospIS (<xref ref-type="table" rid="T1">Table&#x20;1</xref>). DDD and compliance rates tended to indicate the severity of IS in the dose-response effect. Perhaps this is why DDD and compliance rates are positively associated with reHospIS&#x20;risks.</p>
</sec>
<sec id="s3-2">
<title>The Risks of reHospIS for Hyperlipidemic Patients Taking Monolipid-Lowering Medicine</title>
<p>Hyperlipidemic patients were grouped into four subgroups by the type of monolipid-lowering medicine they took regularly. Four medicine categories were (A) nonstatin lipid-lowering medicines versus statins (served as the reference group in the model, abbreviated as ref), (B) high-density statins (Atorvastatin, Rosuvastatin, and Simvastatin) and nonstatin lipid-lowering medicines (Bezafibrate, Gemfibrozil, and Fenofibrate) versus statins (ref), (C) Rosuvastatin, Simvastatin, Lovastatin, Pravastatin, Fluvastatin, Bezafibrate, Gemfibrozil, and Fenofibrate versus Atorvastatin (ref), and (D) five individual statins of Rosuvastatin, Simvastatin, Lovastatin, Pravastatin, and Fluvastatin versus nonstatin lipid-lowering medicines (ref).</p>
<p>In the univariable Cox proportional hazards regression models of four medicine categories (<xref ref-type="fig" rid="F2">Figure&#x20;2</xref>), Rosuvastatin regular users had a significantly lower risk of reHospIS (HR &#x3d; 0.76, <italic>p</italic>&#x20;&#x3c; 0.05) than Atorvastatin in subgroups (C) and (D) (<xref ref-type="fig" rid="F2">Figure&#x20;2</xref>). Among subgroups (A) to (D), the other lipid-lowering medicines had no significant difference in the risks of reHospIS among each other (<xref ref-type="fig" rid="F2">Figure&#x20;2</xref>).</p>
<fig id="F2" position="float">
<label>FIGURE 2</label>
<caption>
<p>The hazard ratios of rehospitalization due to ischemic stroke (reHospIS) for hyperlipidemic patients grouped by categories of lipid-lowering medicines they took regularly using univariable Cox proportional hazards regression. <bold>(A)</bold> Nonstatin lipid-lowering medicines versus statins (reference group, ref); <bold>(B)</bold> high-density statins (Atorvastatin, Rosuvastatin, and Simvastatin) and nonstatin lipid-lowering medicines versus low-density statins (Bezafibrate, Gemfibrozil, and Fenofibrate) (ref); <bold>(C)</bold> Rosuvastatin, Simvastatin, Lovastatin, Pravastatin, Fluvastatin, Bezafibrate, Gemfibrozil, and Fenofibrate versus Atorvastatin (ref); <bold>(D)</bold> five individual statins of Rosuvastatin, Simvastatin, Lovastatin, Pravastatin, and Fluvastatin versus nonstatin lipid-lowering medicines (ref). The asterisk represents a statistically significant hazard ratio (<italic>p</italic>&#x20;&#x3c; 0.05).</p>
</caption>
<graphic xlink:href="fphar-12-741094-g002.tif"/>
</fig>
</sec>
<sec id="s3-3">
<title>Multivariable Cox Proportional Hazards Regression Model</title>
<p>We entered all significant factors from univariable Cox proportional hazards regression models (<xref ref-type="table" rid="T1">Table&#x20;1</xref>) and furtherly analyzed them using multivariable Cox proportional hazard regression models. In the sensitivity analysis of evaluating risks of reHospIS, all hyperlipidemic patients are categorized into four patient subgroups: 1) all hyperlipidemic patients, 2) hyperlipidemic patients with diabetes, 3) hyperlipidemic patients without diabetes, and 4) hyperlipidemic patients without diabetes and without&#x20;HF.</p>
<p>In the results of medicine subgroups (A) to (D), Rosuvastatin regular users had the lowest HRs of reHospIS ranging from 0.63 to 0.64 (<italic>p</italic>&#x20;&#x3c; 0.05) for all patients subgroups (<xref ref-type="fig" rid="F3">Figure&#x20;3</xref>). Statins regular users had significantly lower risks (HRs &#x3d; 1.2&#x2013;1.4) for all patient subgroups as compared with nonstatin lipid-lowering medicines (<xref ref-type="fig" rid="F3">Figure&#x20;3A</xref>). Diabetes patients who took nonstatin lipid-lowering medicines had higher risks of reHospIS as compared with those who took low-density statins. There was no statistically significant difference in the risk of reHospIS for all patient subgroups who took low- or high-density statins (<xref ref-type="fig" rid="F3">Figure&#x20;3B</xref>). Rosuvastatin regular users of all patient subgroups had the significantly lowest HRs of reHospIS ranging from 0.63 to 0.65 (<italic>p</italic>&#x20;&#x3c; 0.05) as compared with Atorvastatin regular users in subgroups (C) and (D) (<xref ref-type="fig" rid="F3">Figures 3C,D</xref>). Lovastatin is one type of statin. Except for the diabetes patient subgroup, the other patient subgroups who took Lovastatin (HR &#x3d; 1.56&#x2013;1.78&#x20;<italic>p</italic>&#x20;&#x3c; 0.05) rather than the other types of statins had the highest risk as compared with Atorvastatin regular users (<xref ref-type="fig" rid="F3">Figures 3C,D</xref>). Except for diabetes patient subgroups, Bezafibrate regular users had significantly higher risks of reHospIS (HR &#x3d; 2.39&#x2013;4.3, <italic>p</italic>&#x20;&#x3c; 0.05) (<xref ref-type="fig" rid="F3">Figure&#x20;3C</xref>). To rule out the possible confounding effect of IS severity, we excluded patients who were not likely to be severe IS patients by excluding low-density statin regular users (the case number of analysis 6,479) (<xref ref-type="sec" rid="s11">Supplementary Table S1</xref>). The abovementioned results remain consistent. <xref ref-type="fig" rid="F4">Figure&#x20;4</xref> depicted the increasing risk trends of reHospIS among regular users of Rosuvastatin, Atorvastatin, nonstatin lipid-lowering medicines, Lovastatin, Gemfibrozil, and Bezafibrate. Except for Bezafibrate, the HR of each blood lipid-lowering medicine in each patient subgroup was similar (<xref ref-type="fig" rid="F4">Figure&#x20;4</xref>).</p>
<fig id="F3" position="float">
<label>FIGURE 3</label>
<caption>
<p>The hazard ratios of reHospIS for hyperlipidemic patients grouped by comorbidities (diabetes mellitus, DM, and heart failure, HF) and categories of lipid-lowering medicines they took regularly using multivariable Cox proportional hazards regression. All the hyperlipidemic patients were categorized into four patient subgroups of 1) all hyperlipidemic patients, 2) hyperlipidemic patients with DM, 3) non-DM hyperlipidemic patients, and 4) non-DM and non-HF hyperlipidemic patients. Cox proportional hazards regression model of each medicine category was conducted for each patient subgroup. The medicine categories were described as follows: <bold>(A)</bold> nonstatin lipid-lowering medicines versus statins (reference group, ref); <bold>(B)</bold> high-density statins (Atorvastatin, Rosuvastatin, and Simvastatin) and nonstatin lipid-lowering medicines versus low-density statins (Bezafibrate, Gemfibrozil, and Fenofibrate) (ref); <bold>(C)</bold> Rosuvastatin, Simvastatin, Lovastatin, Pravastatin, Fluvastatin, Bezafibrate, Gemfibrozil, and Fenofibrate versus Atorvastatin (ref); <bold>(D)</bold> five individual statins of Rosuvastatin, Simvastatin, Lovastatin, Pravastatin, and Fluvastatin versus nonstatin lipid-lowering medicines (ref). The asterisk represents a statistically significant hazard ratio (<italic>p</italic>&#x20;&#x3c; 0.05). Significant variables in the univariable Cox proportional hazards regression models were selected and entered in the multiple Cox proportional hazards regression&#x20;model.</p>
</caption>
<graphic xlink:href="fphar-12-741094-g003.tif"/>
</fig>
<fig id="F4" position="float">
<label>FIGURE 4</label>
<caption>
<p>Multivariable Cox hazard ratio regression outcomes of lipid-lowering medicines on predicting the risk of reHospIS. Only significant lipid-lowering medicines are presented. Atorvastatin users were served as the reference group, the horizontal line of value one. There are four hyperlipidemic patient subgroups marked in different colored circles. The red circle is all hyperlipidemic patients (All). The green circle is hyperlipidemic patients with diabetes (DM). The light green circle is non-DM hyperlipidemic patients. The yellow circle is non-DM and none-HF hyperlipidemic patients.</p>
</caption>
<graphic xlink:href="fphar-12-741094-g004.tif"/>
</fig>
</sec>
<sec id="s3-4">
<title>Bezafibrate and Lovastatin Users With DM Have Lower Risk Than Those Without DM</title>
<p>Though Bezafibrate was linked to a higher risk of reHospIS when compared to Atorvastatin, it appeared to be beneficial to hyperlipidemic patients with diabetes (HR &#x3d; 2.15, <italic>p</italic>&#x20;&#x3c; 0.05) than none DM patients (HR &#x3d; 4.27, <italic>p</italic>&#x20;&#x3c; 0.05) by reducing nearly half the risk of reHospIS. There was no statistical difference of risks of reHospIS in the DM patient subgroup who took Lovastatin (HR &#x3d; 1.31&#x20;<italic>p</italic>&#x20;&#x3d; 0.40) or Atorvastatin, whereas Lovastatin was linked to a higher risk of reHospIS for nondiabetes hyperlipidemic patients (HR &#x3d; 1.8, <italic>p</italic>&#x20;&#x3c; 0.05) when compared to Atorvastatin (<xref ref-type="fig" rid="F3">Figure&#x20;3C</xref>).</p>
</sec>
<sec id="s3-5">
<title>Summary</title>
<p>Under the adjustments of confounders, statins have a lower risk of reHospIS than nonstatin lipid-lowering medicines users in all subgroups. Among these lipid-lowering medicines, regular Rosuvastatin users had the lowest HRs of reHospIS. Though Bezafibrate and Lovastatin were linked to higher risks of reHospIS, they may be beneficial to DM patients when compared to none DM patients.</p>
</sec>
</sec>
<sec sec-type="discussion" id="s4">
<title>Discussion</title>
<p>This is a 6-years long retrospective study of 9,098 hyperlipidemic patients. Long-term statin users of hyperlipidemic patients had lower reHospIS risks than nonstatin lipid-lowering medicines users. In comparison to Atorvastatin regular users, Rosuvastatin regular users had the lowest HRs of reHospIS among all patient subgroups. Except for hyperlipidemic patients with diabetes, regular Lovastatin users had the highest risks of reHospIS among statins regular users. The increasing trends of risks of reHospIS were observed from Rosuvastatin, nonstatin lipid-lowering medicines, Lovastatin, and Gemfibrozil to Bezafibrate regular&#x20;users.</p>
<p>The mechanism of statins primarily lowered the concentration of LDL rather than reducing TG or increasing HDL. Randomized trials have shown that lowering LDL cholesterol reduces the risk of stroke (<xref ref-type="bibr" rid="B5">Castilla-Guerra et&#x20;al., 2019</xref>). It may be the reason that statins are more protective against reHospIS than nonstatin lipid-lowering medicines users. The first-generation statins are Pravastatin, Lovastatin, and Fluvastatin; the second-generation statins are Simvastatin and Atorvastatin; and the third-generation statins are Rosuvastatin and Pitavastatin. Second- and third-generation statins were more effective at lowering LDL cholesterol than first-generation statins. In addition, Rosuvastatin outperformed Atorvastatin, Simvastatin, and Pravastatin in terms of LDL-lowering efficacy.</p>
<p>In a mouse experiment, both normal and high doses of Rosuvastatin were found to be effective in preventing rt-PA-associated hemorrhages with brain ischemia while having no effect on cerebral blood reflow or neural function (<xref ref-type="bibr" rid="B18">Lu et&#x20;al., 2018</xref>). In addition, Rosuvastatin slowed the progression of cardiovascular disease in diabetes patients by improving HDL functions and suppressing inflammation. The prevention of unfavorable outcomes of IS was associated not only with LDL-lowering effect but also with pleiotropic effects of endothelial function, modulating thrombogenesis, attenuating inflammatory and oxidative stress damage, and facilitating angiogenesis matters (<xref ref-type="bibr" rid="B35">Zhao et&#x20;al., 2014</xref>).</p>
<p>It was noted that nonstatin lipid-lowering medicines were linked to higher risks of reHospIS in none-diabetes hyperlipidemic patients. Statins are preferred as first-line therapy, and other lipid-lowering medicines should be avoided. However, it has been reported that the combination therapy of statin and nonstatin lipid-lowering medicines (e.g., ezetimibe, fibrates, bile acid sequestrants, PCSK9 inhibitors, and omega-3 fatty acids) (<xref ref-type="bibr" rid="B26">Rodriguez et&#x20;al., 2018</xref>) was recommended for releasing other syndromes. For instance, the combination of Simvastatin and Bezafibrate increased cholesterol efflux in parallel with HDL cholesterol and apoA&#x2010;I responses. When compared to statin treatment alone, Bezafibrate and statin combination therapy reduces the risk of 30-day major adverse cardiovascular events and 1-year mortality rates in diabetes patients.</p>
<p>In this study, Bezafibrate regular users with diabetes had nearly 50% lower reHospIS risks than those without diabetes. Bezafibrate is one of the most commonly used molecules in the treatment of hypertriglyceridemia, and statin therapy is often added to achieve lipid profile goals in mixed dyslipidemia (<xref ref-type="bibr" rid="B17">Le&#xf3;n-Mart&#xed;nez et&#x20;al., 2021</xref>). Bezafibrate ameliorates diabetes and may benefit patients with nonalcoholic fatty liver disease and impaired glucose metabolism by reducing steatosis, enhancing hepatic mitochondrial mass, improving metabolic flexibility, and increasing hepatic insulin sensitivity (<xref ref-type="bibr" rid="B11">Franko et&#x20;al., 2017</xref>).</p>
<p>Lovastatin was an unfavorable lipid-lowering medicine for nondiabetes hyperlipidemic patients due to its high risk of reHospIS, but it had no adverse effects on those with DM when compared to Atorvastatin. Moreover, Lovastatin was found to significantly reduce fatty streak lesion formation in the aortic arch of hyperlipidemic-diabetic hamsters (<xref ref-type="bibr" rid="B7">El-Swefy et&#x20;al., 2000</xref>). Its other functions of lowering plasma total triglycerides and total cholesterols, selectively decreasing non-HDL-C, and providing antioxidant protection may also contribute to its protective effects. The antioxidant effects of Lovastatin may be beneficial for hyperlipidemic patients with diabetes.</p>
<p>There were some limitations in the study. Not all the statins were included in the study (e.g., Pitavastatin) because some statins were not commercially available and proven by Taiwan Food and Drug Administration during the study period. Serum lipid-lowering herbal medicines, oral hypoglycemic agents, lifestyle, and dietary factors were not included. The use of lipid-lowering medicines, blood lipid levels (not available in the NHIRD), and diabetes status of study subjects prior to their first hospitalization due to IS were not included in the study. However, we designed 1-year washout period prior to the start of the study to reduce the impact of the aforementioned conditions.</p>
<p>We only discussed the risk of reHospIS for users of monolipid-lowering medicines. We are unable to assess the combined effects of statins and nonstatin lipid-lowering medicines. However, we discovered that nonstatin lipid-lowering medicines had a beneficial effect on hyperlipidemic patients with diabetes. It calls for further studies into the effects of combinational treatments on the long-term risks of reHospIS.</p>
</sec>
<sec sec-type="conclusion" id="s5">
<title>Conclusion</title>
<p>In comparison to nonstatin lipid-lowering medicines, statins had a longer-term beneficial effect of secondary prevention of reHospIS for hyperlipidemic patients. Rosuvastatin is the most effective treatment for all subgroups of hyperlipidemic patients. On the other hand, Bezafibrate appears to benefit hyperlipidemic patients with diabetes. The combined effects of statins and nonstatin lipid-lowering medicines on diabetes hyperlipidemic patients warrant further studies to understand the beneficial mechanism.</p>
</sec>
</body>
<back>
<sec id="s6">
<title>Data Availability Statement</title>
<p>The data analyzed in this study is subject to the following licenses/restrictions. The dataset can be applied from the National Health Insurance Research Database according to the application regulation. Requests to access these datasets should be directed to <ext-link ext-link-type="uri" xlink:href="https://nhird.nhri.org.tw/apply_00.%20html">https://nhird.nhri.org.tw/apply_00.&#x20;html</ext-link>.</p>
</sec>
<sec id="s7">
<title>Ethics Statement</title>
<p>The studies involving human participants were reviewed and approved by Tri-Service General Hospital Institutional Review Board, No. 325, Sec.2, Chenggong Rd., Neihu District, Taipei City 11490, Taiwan. Written informed consent for participation was not required for this study in accordance with the national legislation and the institutional requirements.</p>
</sec>
<sec id="s8">
<title>Author Contributions</title>
<p>Data curation, Y-TC; formal analysis, Y-TC; project administration, J-HY and G-SP; resources, J-HY, G-SP, K-HC, W-CC and C-WY; supervision, C-MC and C-WY; writing&#x2013;original draft, Y-TC; Writing&#x2013;review and editing, C-MC, K-HC, L-TK, C-CW, W-CT, W-ZL, Y-SW, H-CL, and C-WY.</p>
</sec>
<sec sec-type="COI-statement" id="s9">
<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="disclaimer" id="s10">
<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 id="s11">
<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.2021.741094/full#supplementary-material">https://www.frontiersin.org/articles/10.3389/fphar.2021.741094/full&#x23;supplementary-material</ext-link>
</p>
<supplementary-material xlink:href="DataSheet1.docx" id="SM1" mimetype="application/docx" xmlns:xlink="http://www.w3.org/1999/xlink"/>
</sec>
<sec id="s12">
<title>Abbreviations</title>
<p>IS, ischemic stroke; reHospIS, rehospitalization due to IS; HF, heart failure; HBP, high blood pressure; PAOD, peripheral arterial occlusion disease.</p>
</sec>
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