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<front>
<journal-meta>
<journal-id journal-id-type="publisher-id">Front. Med.</journal-id>
<journal-title>Frontiers in Medicine</journal-title>
<abbrev-journal-title abbrev-type="pubmed">Front. Med.</abbrev-journal-title>
<issn pub-type="epub">2296-858X</issn>
<publisher>
<publisher-name>Frontiers Media S.A.</publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="doi">10.3389/fmed.2025.1596037</article-id>
<article-categories>
<subj-group subj-group-type="heading">
<subject>Medicine</subject>
<subj-group>
<subject>Original Research</subject>
</subj-group>
</subj-group>
</article-categories>
<title-group>
<article-title>Effect of probiotics on the incidence of acute kidney injury in patients with severe pneumonia</article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name><surname>Zhang</surname> <given-names>Qiang</given-names></name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
<role content-type="https://credit.niso.org/contributor-roles/writing-original-draft/"/>
</contrib>
<contrib contrib-type="author" corresp="yes">
<name><surname>Song</surname> <given-names>Xuefeng</given-names></name>
<xref ref-type="aff" rid="aff2"><sup>2</sup></xref>
<xref ref-type="corresp" rid="c001"><sup>&#x002A;</sup></xref>
<uri xlink:href="https://loop.frontiersin.org/people/3008955/overview"/>
<role content-type="https://credit.niso.org/contributor-roles/writing-original-draft/"/>
<role content-type="https://credit.niso.org/contributor-roles/writing-review-editing/"/>
</contrib>
</contrib-group>
<aff id="aff1"><sup>1</sup><institution>Department of Critical Care Medicine, Peking University Third Hospital</institution>, <addr-line>Beijing</addr-line>, <country>China</country></aff>
<aff id="aff2"><sup>2</sup><institution>Department of Gastrointestinal Oncology, Shanxi Province Cancer Hospital/Shanxi Hospital Affiliated to Cancer Hospital, Chinese Academy of Medical Sciences/Cancer Hospital Affiliated to Shanxi Medical University</institution>, <addr-line>Taiyuan, Shanxi</addr-line>, <country>China</country></aff>
<author-notes>
<fn fn-type="edited-by" id="fn0001">
<p>Edited by: Pierluigi Marzuillo, University of Campania Luigi Vanvitelli, Italy</p></fn>
<fn fn-type="edited-by" id="fn0002">
<p>Reviewed by: Johid Malik, University of Nebraska Medical Center, United States</p>
<p>Evandro Neves Silva, Federal University of Alfenas, Brazil</p></fn>
<corresp id="c001">&#x002A;Correspondence: Xuefeng Song, <email>sxfzlyy@163.com</email></corresp>
</author-notes>
<pub-date pub-type="epub">
<day>21</day>
<month>05</month>
<year>2025</year>
</pub-date>
<pub-date pub-type="collection">
<year>2025</year>
</pub-date>
<volume>12</volume>
<elocation-id>1596037</elocation-id>
<history>
<date date-type="received">
<day>19</day>
<month>03</month>
<year>2025</year>
</date>
<date date-type="accepted">
<day>28</day>
<month>04</month>
<year>2025</year>
</date>
</history>
<permissions>
<copyright-statement>Copyright &#x00A9; 2025 Zhang and Song.</copyright-statement>
<copyright-year>2025</copyright-year>
<copyright-holder>Zhang and Song</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 id="sec1">
<title>Objective</title>
<p>This study employed a retrospective analysis to investigate whether probiotics were associated with a lower incidence of Acute Kidney Injury (AKI) in patients with severe pneumonia.</p>
</sec>
<sec id="sec2">
<title>Methods</title>
<p>We retrospectively analyzed patients with severe pneumonia who required mechanical ventilation and had no prior history of kidney disease.</p>
</sec>
<sec id="sec3">
<title>Results</title>
<p>Based on the inclusion and exclusion criteria, a total of 267 cases were included, comprising 190 patients who did not develop AKI and 77 patients who developed AKI. Statistically significant differences (<italic>p</italic>&#x202F;&#x003C;&#x202F;0.05) were observed between the AKI and non-AKI groups in terms of gender, CRP, PCT, PLT, SOFA score, ALB, Cr, and BUN. The proportion of probiotics use was lower in the AKI group, with a statistically significant difference between the two groups (<italic>p</italic>&#x202F;&#x003C;&#x202F;0.05). Using the occurrence of AKI as the dependent variable, a multivariate logistic regression analysis was performed including gender, CRP, PCT, PLT, SOFA score, ALB, Cr, and BUN. The analysis demonstrated that probiotics were associated with a lower incidence of AKI during ICU hospitalization in patients with severe pneumonia (<italic>p</italic>&#x202F;=&#x202F;0.031). The results of the ordered logistic regression further indicated that probiotics use reduced the incidence of AKI (Coefficient&#x202F;=&#x202F;&#x2212;0.7748, <italic>p</italic>&#x202F;=&#x202F;0.006). Subgroup analysis revealed that probiotics were associated with a lower incidence of stage 1 AKI (OR: 0.4023, 95% CI:&#x202F;0.1895&#x2013;0.8540, <italic>p</italic>&#x202F;=&#x202F;0.018) but not stage 2 (OR: 0.683, 95% CI:&#x202F;0.2083&#x2013;2.242, <italic>p</italic>&#x202F;=&#x202F;0.53) or stage 3 AKI (OR: 0.9007, 95% CI:&#x202F;0.2851&#x2013;2.845, <italic>p</italic>&#x202F;=&#x202F;0.859). Among the 146 patients in the probiotic group and 121 patients in the non-probiotic group, 44 patients developed stage 1 AKI, 15 developed stage 2 AKI, and 18 developed stage 3 AKI. Creatinine was selected for matching to balance the confounder. After propensity score matching, a total of 224 cases were matched (112 in each group). The incidence of stage 1 AKI (<italic>p</italic>&#x202F;=&#x202F;0.019) remained statistically significant, while no significant differences were observed in the incidence of stage 2 AKI (<italic>p</italic>&#x202F;=&#x202F;0.757) or stage 3 AKI (<italic>p</italic>&#x202F;=&#x202F;0.757) between the two groups.</p>
</sec>
<sec id="sec4">
<title>Conclusion</title>
<p>Probiotics were associated with a lower incidence of stage 1 AKI in patients with severe pneumonia. However, our research was a single-center retrospective study, and multi-center randomized controlled studies would be needed in the future for validation.</p>
</sec>
</abstract>
<kwd-group>
<kwd>severe pneumonia</kwd>
<kwd>probiotics</kwd>
<kwd>acute kidney injury</kwd>
<kwd>critical care</kwd>
<kwd>renal complications</kwd>
</kwd-group>
<counts>
<fig-count count="1"/>
<table-count count="5"/>
<equation-count count="0"/>
<ref-count count="32"/>
<page-count count="8"/>
<word-count count="5625"/>
</counts>
<custom-meta-wrap>
<custom-meta>
<meta-name>section-at-acceptance</meta-name>
<meta-value>Pulmonary Medicine</meta-value>
</custom-meta>
</custom-meta-wrap>
</article-meta>
</front>
<body>
<sec sec-type="intro" id="sec5">
<label>1</label>
<title>Introduction</title>
<p>Severe pneumonia is a life-threatening lower respiratory tract infection characterized by rapid clinical deterioration and high mortality. In addition to respiratory failure, severe pneumonia may result in multi-organ dysfunction, including acute kidney injury, which significantly worsens prognosis. During severe inflammation, the composition of the gut microbiota undergoes significant alterations, which can disrupt microbial balance. This dysbiosis is associated with exacerbated local and systemic inflammation, increased uremic toxin concentrations, elevated intestinal permeability, and the development of endotoxemia and immune deficiencies (<xref ref-type="bibr" rid="ref1">1</xref>). Probiotics have been shown to enhance intestinal barrier function, reduce the host pathogen load, competitively inhibit pathogenic bacteria, regulate host inflammatory responses (<xref ref-type="bibr" rid="ref2">2</xref>), and modulate the immune system (<xref ref-type="bibr" rid="ref3">3</xref>). Some studies suggest that probiotics may reduce the risk of sepsis and lower respiratory tract infections (<xref ref-type="bibr" rid="ref4">4</xref>). However, researchers conducted a randomized controlled trial and found that probiotic administration did not reduce the incidence of ventilator-associated pneumonia (VAP), duration of antibiotic use, or length of ICU stay in critically ill patients (<xref ref-type="bibr" rid="ref1">1</xref>). They believe that although critically ill patients exhibit a reduction in commensal microbiota, overgrowth of potential pathogens, and consequently, a highly perturbed microbial community (<xref ref-type="bibr" rid="ref5">5</xref>), probiotics may not improve clinically significant outcomes associated with dysbiosis in such circumstances. Similarly, recent research has demonstrated that, in mechanically ventilated patients with severe conditions, probiotics did not reduce the incidence of ventilator-associated pneumonia compared to a placebo (<xref ref-type="bibr" rid="ref1">1</xref>). Despite numerous studies exploring the effects of probiotics on various health outcomes, results remain conflicting. These discrepancies may arise from several factors, including differences in patient populations, probiotic strains used, and variations in study designs.</p>
<p>Currently, the management of acute kidney injury (AKI) caused by sepsis is primarily limited to treating the underlying cause (<xref ref-type="bibr" rid="ref6">6</xref>), and in severe cases, addressing its complications through kidney replacement therapy (KRT) (<xref ref-type="bibr" rid="ref7">7</xref>). Therefore, there is an urgent need to explore alternative therapeutic approaches for AKI. In 2023, researchers conducted a multicenter randomized controlled trial to investigate whether probiotics could promote renal function recovery during AKI in sepsis. The results demonstrated that administering probiotics for seven consecutive days was safe but did not increase the likelihood of renal function recovery among sepsis patients (<xref ref-type="bibr" rid="ref8">8</xref>).</p>
<p>As AKI is a syndrome that elicits a strong systemic inflammatory response (<xref ref-type="bibr" rid="ref9">9</xref>), it has been demonstrated that attenuating this response can improve renal function and mitigate parenchymal damage (<xref ref-type="bibr" rid="ref10">10</xref>). Animal experiments have revealed a bidirectional relationship between host AKI and gut microbiota. The gut microbiota can significantly influence the prognosis of AKI, while AKI can also induce alterations in the gut microbiota. This interaction is termed the &#x201C;gut-kidney axis.&#x201D; The bidirectional relationship between the gut and kidney underscores the critical interplay between these two organs, with significant clinical implications. This inter-organ communication suggests potential therapeutic avenues via microbiota modulation. Modulating the microbiota through probiotic administration to ameliorate gut dysbiosis during AKI appears to improve the prognosis of patients with these conditions (<xref ref-type="bibr" rid="ref11">11</xref>). Current research primarily focuses on whether probiotics can improve the prognosis of patients with severe pneumonia and whether they can promote the recovery of AKI after its onset. Despite growing interest in the gut&#x2013;kidney axis, there is limited evidence on whether probiotic administration can prevent AKI in patients with severe pneumonia who have no prior renal disease. This retrospective study investigates whether probiotics use is associated with a reduced incidence of AKI in this patient population.</p>
<sec id="sec6">
<label>1.1</label>
<title>Study population</title>
<p>A retrospective study was conducted on patients with severe pneumonia admitted to Peking University Third Hospital from February 2021 to September 2023 who required mechanical ventilation.</p>
</sec>
<sec id="sec7">
<label>1.2</label>
<title>Inclusion and exclusion criteria</title>
<p>Mechanically ventilated patients meeting the diagnostic criteria for severe pneumonia (<xref ref-type="bibr" rid="ref12">12</xref>, <xref ref-type="bibr" rid="ref13">13</xref>) were included. AKI is defined by the Kidney Disease: Improving Global Outcomes (KDIGO) organization as an increase in serum creatinine (sCr) levels by &#x2265;0.3&#x202F;mg/dL (&#x2265;26.5&#x202F;&#x03BC;moL/L) within 48&#x202F;h, or an increase in sCr to &#x2265;1.5 times baseline, or urine volume &#x003C;0.5&#x202F;mL/kg/h for 6&#x202F;h (<xref ref-type="bibr" rid="ref14">14</xref>). Use of probiotics was before the development of AKI. A total of 267 patients met the inclusion criteria and were included in the final analysis. Patients were divided into the probiotic group and the non-probiotic group based on whether they received probiotics during their ICU stay.</p>
</sec>
<sec id="sec8">
<label>1.3</label>
<title>Exclusion criteria</title>
<p>Patients were excluded if they (1) died within 24&#x202F;h of admission [(8) patients], (2) were under 18&#x202F;years of age [(6) patients], (3) had pre-existing renal insufficiency [(41) patients], or (4) had active malignancies [(44) patients].</p>
</sec>
<sec id="sec9">
<label>1.4</label>
<title>Ethics statement</title>
<p>This study was a retrospective study that complied with medical ethical standards and was approved by the Medical Ethics Committee of Peking University Third Hospital (Ethics approval number: M20250221). Given the retrospective design, the requirement for informed consent was waived by the ethics committee.</p>
</sec>
<sec id="sec10">
<label>1.5</label>
<title>Observation indicators</title>
<p>Clinical data within 24&#x202F;h of enrollment were collected, including age, gender, comorbidities (diabetes, hypertension, hepatic insufficiency), C-reactive protein (CRP), procalcitonin (PCT), D-dimer, white blood cell count (WBC), Sequential Organ Failure Assessment (SOFA) score, Oxygenation Index (OI), Albumin (ALB), Creatinine (Cr), and Blood Urea Nitrogen (BUN). Data on use of probiotics and the development of AKI were collected throughout the patients&#x2019; ICU stay.</p>
</sec>
<sec id="sec11">
<label>1.6</label>
<title>Statistical methods</title>
<p>Statistical analysis was performed using STATA 18 software (StataCorp, College Station, TX, USA). The Kolmogorov&#x2013;Smirnov method was used to test the normality of measurement data. Normality was defined as a Kolmogorov&#x2013;Smirnov test <italic>p</italic> &#x003E; 0.05. Visual inspections (Q-Q plots and histograms) further validated this assumption. Normally distributed measurement data are presented as mean &#x00B1; standard deviation (&#x00B1;s) and analyzed using the <italic>t</italic>-test. Non-normally distributed measurement data are presented as median (interquartile range) [M (QL, QU)] and analyzed using the Mann&#x2013;Whitney U nonparametric test. Count data are presented as <italic>n</italic> (%) and analyzed using the <italic>&#x03C7;</italic><sup>2</sup> test. We performed univariate analysis,statistically significant differences (<italic>p</italic> &#x003C;&#x202F;0.05) were found between the AKI and non-AKI groups in terms of gender, CRP, PCT, PLT, SOFA, ALB, Cr, and BUN. Then these variables were included the multivariate logistic regression model. Multivariate logistic regression was performed to identify the independent predictors of AKI and to evaluate the correlation between probiotic use and AKI incidence. This regression analysis allowed us to control for potential confounding variables and isolate the specific factors that significantly influence the occurrence of AKI. By including relevant covariates in the model, we aimed to obtain a more accurate understanding of the relationship between probiotics use and AKI incidence while accounting for other variables that may affect the outcome. Subgroup analysis was also performed based on AKI stages. Before propensity score matching (PSM), we compared baseline characteristics between the probiotic and non - probiotic groups. Only creatinine levels showed a statistically difference. Thus, we chose creatinine for matching to balance this confounder and enhance result accuracy. A 1:1 match was performed using the nearest neighbor matching method, with a caliper set at 0.05 times the standard deviation to ensure matching accuracy. This analysis was conducted to determine whether there were differences in the occurrence of AKI between the probiotic and non-probiotic groups. <italic>p</italic> &#x003C;&#x202F;0.05 was considered statistically significant.</p>
</sec>
</sec>
<sec sec-type="results" id="sec12">
<label>2</label>
<title>Results</title>
<p>Based on the inclusion and exclusion criteria, a total of 267 cases were included, with 190 patients (71.16%) not developing AKI and 77 patients (28.84%) developing AKI. The AKI group had lower male proportion (12.99% vs. 26.31%, <italic>p</italic> =&#x202F;0.018), higher CRP (120.1&#x202F;mg/L vs. 74.26&#x202F;mg/L, <italic>p</italic> =&#x202F;0.0076), higher PCT (1.22&#x202F;ng/mL vs. 0.51&#x202F;ng/mL, <italic>p</italic> =&#x202F;0.001), lower PLT (160 vs. 185, <italic>p</italic> =&#x202F;0.0089), higher SOFA score (10 vs. 7, <italic>p</italic> =&#x202F;0.001), lower ALB (29.8&#x202F;g/L vs. 32.9&#x202F;g/L, <italic>p</italic> =&#x202F;0.008), higher Cr (111 vs. 67, <italic>p</italic> =&#x202F;0.001), and higher BUN (11.21 vs. 7.845, <italic>p</italic> =&#x202F;0.001). No significant differences were found in age, D - dimer, WBC, OI, or the rates of hypertension, diabetes, and liver dysfunction between the two groups (<italic>p</italic> &#x003E;&#x202F;0.05) (<xref ref-type="table" rid="tab1">Table 1</xref>).</p>
<table-wrap position="float" id="tab1">
<label>Table 1</label>
<caption>
<p>Comparison of basic information between two groups.</p>
</caption>
<table frame="hsides" rules="groups">
<thead>
<tr>
<th>Factors</th>
<th align="center" valign="top">Non -AKI (<italic>n</italic>&#x202F;=&#x202F;190)</th>
<th align="center" valign="top">AKI (<italic>n</italic>&#x202F;=&#x202F;77)</th>
<th align="center" valign="top"><italic>&#x03C7;</italic><sup>2</sup>/Z/t</th>
<th align="center" valign="top"><italic>p</italic></th>
</tr>
</thead>
<tbody>
<tr>
<td align="left" valign="top">Age (year)</td>
<td align="center" valign="top">68 (56, 75)</td>
<td align="center" valign="top">67 (55, 76)</td>
<td align="center" valign="top">0.002</td>
<td align="center" valign="top">0.965</td>
</tr>
<tr>
<td align="left" valign="top">Gender (M)</td>
<td align="center" valign="top">50 (26.31%)</td>
<td align="center" valign="top">10 (12.99%)</td>
<td align="center" valign="top">5.5875</td>
<td align="center" valign="top">0.018</td>
</tr>
<tr>
<td align="left" valign="top">CRP (mg/L)</td>
<td align="center" valign="top">74.26 (24.9, 157.5)</td>
<td align="center" valign="top">120.1 (49.6, 242)</td>
<td align="center" valign="top">7.136</td>
<td align="center" valign="top">0.0076</td>
</tr>
<tr>
<td align="left" valign="top">PCT (ng/mL)</td>
<td align="center" valign="top">0.51 (0.156, 3.26)</td>
<td align="center" valign="top">1.22 (0.417, 19.91)</td>
<td align="center" valign="top">15.181</td>
<td align="center" valign="top">0.001</td>
</tr>
<tr>
<td align="left" valign="top">D-2 (&#x03BC;g/L)</td>
<td align="center" valign="top">2, 750 (1,340, 6, 490)</td>
<td align="center" valign="top">2, 756 (1,236, 6,662)</td>
<td align="center" valign="top">0.008</td>
<td align="center" valign="top">0.973</td>
</tr>
<tr>
<td align="left" valign="top">WBC (&#x00D7;10<sup>9</sup>/L)</td>
<td align="center" valign="top">11.25 (8, 15.33)</td>
<td align="center" valign="top">10.94 (7.04, 17.06)</td>
<td align="center" valign="top">0.070</td>
<td align="center" valign="top">0.792</td>
</tr>
<tr>
<td align="left" valign="top">PLT (&#x00D7;10<sup>9</sup>/L)</td>
<td align="center" valign="top">185 (118, 245)</td>
<td align="center" valign="top">160 (84, 208)</td>
<td align="center" valign="top">6.850</td>
<td align="center" valign="top">0.0089</td>
</tr>
<tr>
<td align="left" valign="top">OI (mmHg)</td>
<td align="center" valign="top">176.13 (119.83, 236.57)</td>
<td align="center" valign="top">160 (102.86, 205.7)</td>
<td align="center" valign="top">2.554</td>
<td align="center" valign="top">0.11</td>
</tr>
<tr>
<td align="left" valign="top">SOFA</td>
<td align="center" valign="top">7 (6, 10)</td>
<td align="center" valign="top">10 (7, 12)</td>
<td align="center" valign="top">17.87</td>
<td align="center" valign="top">0.001</td>
</tr>
<tr>
<td align="left" valign="top">ALB (g/L)</td>
<td align="center" valign="top">32.9 (29.6, 35.8)</td>
<td align="center" valign="top">29.8 (26.5, 34.3)</td>
<td align="center" valign="top">11.13</td>
<td align="center" valign="top">0.008</td>
</tr>
<tr>
<td align="left" valign="top">Cr (&#x03BC;mol/L)</td>
<td align="center" valign="top">67 (53.88)</td>
<td align="center" valign="top">111 (87, 167)</td>
<td align="center" valign="top">58.186</td>
<td align="center" valign="top">0.001</td>
</tr>
<tr>
<td align="left" valign="top">BUN (mmol/L)</td>
<td align="center" valign="top">7.845 (5.315, 11.87)</td>
<td align="center" valign="top">11.21 (8.51, 16.49)</td>
<td align="center" valign="top">19.814</td>
<td align="center" valign="top">0.001</td>
</tr>
<tr>
<td align="left" valign="top">Hypertension</td>
<td align="center" valign="top">95 (50%)</td>
<td align="center" valign="top">45 (58.44%)</td>
<td align="center" valign="top">1.5656</td>
<td align="center" valign="top">0.211</td>
</tr>
<tr>
<td align="left" valign="top">Diabetes</td>
<td align="center" valign="top">30 (15.79%)</td>
<td align="center" valign="top">20 (%)</td>
<td align="center" valign="top">3.7343</td>
<td align="center" valign="top">0.053</td>
</tr>
<tr>
<td align="left" valign="top">Liver dysfunction</td>
<td align="center" valign="top">66 (34.74%)</td>
<td align="center" valign="top">33 (25.97%)</td>
<td align="center" valign="top">1.5487</td>
<td align="center" valign="top">0.213</td>
</tr>
<tr>
<td align="left" valign="top">Probiotics</td>
<td align="center" valign="top">97 (51.05%)</td>
<td align="center" valign="top">24 (31.17%)</td>
<td align="center" valign="top">8.74</td>
<td align="center" valign="top">0.003</td>
</tr>
</tbody>
</table>
</table-wrap>
<p>Probiotics use was higher in the non - AKI group (51.05% vs. 31.17%, <italic>p</italic> =&#x202F;0.003).</p>
</sec>
<sec id="sec13">
<label>3</label>
<title>Multivariate logistic analysis</title>
<p>According to the statistical results, 121 patients received probiotics, among whom 24 patients (19.83%) developed AKI; 146 patients did not receive probiotics, among whom 53 patients (36.30%) developed AKI. The chi-square test results showed that the proportion of AKI occurrence was statistically significant between the two groups before adjustment (<italic>&#x03C7;</italic><sup>2</sup>&#x202F;=&#x202F;8.74, <italic>p</italic>&#x202F;=&#x202F;0.003). Using the occurrence of AKI as the dependent variable, multivariate logistic analysis was performed incorporating indicators (gender, CRP, PCT, PLT, SOFA, ALB, Cr, and BUN) with statistical differences between the two groups.</p>
<p>As shown in <xref ref-type="table" rid="tab2">Table 2</xref>, after adjusting for the aforementioned (gender, CRP, PCT, PLT, SOFA, ALB, Cr, and BUN) factors, gender, CRP, PCT, PLT, BUN and Sofa score showed no significant correlation with AKI occurrence (all <italic>p</italic> &#x003E;&#x202F;0.05).</p>
<table-wrap position="float" id="tab2">
<label>Table 2</label>
<caption>
<p>Results after multiple logistic regression.</p>
</caption>
<table frame="hsides" rules="groups">
<thead>
<tr>
<th align="left" valign="top">Factors</th>
<th align="center" valign="top">Odds ratio</th>
<th align="center" valign="top">Std. err.</th>
<th align="center" valign="top">|z|</th>
<th align="center" valign="top">P&#x202F;&#x003E;&#x202F;|z|</th>
<th align="center" valign="top">[95% conf. interval]</th>
</tr>
</thead>
<tbody>
<tr>
<td align="left" valign="top">Gender</td>
<td align="center" valign="top">0.610</td>
<td align="center" valign="top">0.274</td>
<td align="center" valign="top">&#x2212;1.10</td>
<td align="center" valign="top">0.272</td>
<td align="center" valign="top">0.253&#x2013;1.471</td>
</tr>
<tr>
<td align="left" valign="top">CRP (mg/L)</td>
<td align="center" valign="top">1.000</td>
<td align="center" valign="top">0.001</td>
<td align="center" valign="top">0.23</td>
<td align="center" valign="top">0.816</td>
<td align="center" valign="top">0.997&#x2013;1.004</td>
</tr>
<tr>
<td align="left" valign="top">PCT (ng/mL)</td>
<td align="center" valign="top">1.009</td>
<td align="center" valign="top">0.0081</td>
<td align="center" valign="top">1.22</td>
<td align="center" valign="top">0.223</td>
<td align="center" valign="top">0.994&#x2013;1.026</td>
</tr>
<tr>
<td align="left" valign="top">PLT (&#x00D7;10<sup>9</sup>/L)</td>
<td align="center" valign="top">0.9992</td>
<td align="center" valign="top">0.0018</td>
<td align="center" valign="top">&#x2212;0.41</td>
<td align="center" valign="top">0.683</td>
<td align="center" valign="top">0.9956&#x2013;1.003</td>
</tr>
<tr>
<td align="left" valign="top">BUN (mmol/L)</td>
<td align="center" valign="top">0.9868</td>
<td align="center" valign="top">0.0234</td>
<td align="center" valign="top">&#x2212;0.56</td>
<td align="center" valign="top">0.575</td>
<td align="center" valign="top">0.942&#x2013;1.034</td>
</tr>
<tr>
<td align="left" valign="top">Cr (&#x03BC;mol/L)</td>
<td align="center" valign="top">1.0201</td>
<td align="center" valign="top">0.0046</td>
<td align="center" valign="top">4.37</td>
<td align="center" valign="top">0.000</td>
<td align="center" valign="top">1.011&#x2013;1.029</td>
</tr>
<tr>
<td align="left" valign="top">ALB (g/L)</td>
<td align="center" valign="top">0.904</td>
<td align="center" valign="top">0.0327</td>
<td align="center" valign="top">&#x2212;2.78</td>
<td align="center" valign="top">0.005</td>
<td align="center" valign="top">0.842&#x2013;0.9707</td>
</tr>
<tr>
<td align="left" valign="top">Sofa</td>
<td align="center" valign="top">1.022</td>
<td align="center" valign="top">0.0612</td>
<td align="center" valign="top">0.36</td>
<td align="center" valign="top">0.716</td>
<td align="center" valign="top">0.9088&#x2013;1.149</td>
</tr>
<tr>
<td align="left" valign="top">Probiotics</td>
<td align="center" valign="top">0.483</td>
<td align="center" valign="top">0.163</td>
<td align="center" valign="top">&#x2212;2.16</td>
<td align="center" valign="top">0.031</td>
<td align="center" valign="top">0.2491&#x2013;0.9357</td>
</tr>
<tr>
<td align="left" valign="top">Cons.</td>
<td align="center" valign="top">3.581</td>
<td align="center" valign="top">5.041</td>
<td align="center" valign="top">0.91</td>
<td align="center" valign="top">0.365</td>
<td align="center" valign="top">0.227&#x2013;56.543</td>
</tr>
</tbody>
</table>
</table-wrap>
<p>Cr levels were positively correlated with AKI occurrence (OR&#x202F;=&#x202F;1.020, 95% CI&#x202F;=&#x202F;1.011&#x2013;1.029, <italic>p</italic> =&#x202F;0.000). ALB levels were inversely correlated with AKI occurrence (OR&#x202F;=&#x202F;0.904, 95% CI&#x202F;=&#x202F;0.842&#x2013;0.970, <italic>p</italic> =&#x202F;0.005).</p>
<p>Probiotics use was associated with reduced AKI occurrence (OR&#x202F;=&#x202F;0.483, 95% CI&#x202F;=&#x202F;0.249&#x2013;0.935, <italic>p</italic> =&#x202F;0.031). Patients using probiotics had about half the odds of developing AKI compared to non - users.</p>
</sec>
<sec id="sec14">
<label>4</label>
<title>Results of ordered logistic regression</title>
<p>According to the KDIGO criteria, AKI is classified into stages 1, 2, and 3. The results of the Ordered Logistic Regression (<xref ref-type="table" rid="tab3">Table 3</xref>) indicate that Probiotic use was negatively associated with AKI stage (Coefficient&#x202F;=&#x202F;&#x2212;0.775, Std. err.&#x202F;=&#x202F;0.282, z&#x202F;=&#x202F;&#x2212;2.74, <italic>p</italic> =&#x202F;0.006). The 95% CI was &#x2212;1.328 to &#x2212;0.221, indicating that probiotics use was significantly related to lower AKI stages.</p>
<table-wrap position="float" id="tab3">
<label>Table 3</label>
<caption>
<p>Results of ordered logistic regression.</p>
</caption>
<table frame="hsides" rules="groups">
<thead>
<tr>
<th align="left" valign="top">AKI-stage</th>
<th align="center" valign="top">Coefficient</th>
<th align="center" valign="top">Std. err.</th>
<th align="center" valign="top">z</th>
<th align="center" valign="top">P&#x202F;&#x003E;&#x202F;z</th>
<th align="center" valign="top">[95% conf. interval]</th>
</tr>
</thead>
<tbody>
<tr>
<td align="left" valign="top">Probiotics</td>
<td align="center" valign="top">&#x2212;0.7748613</td>
<td align="center" valign="top">0.2824</td>
<td align="center" valign="top">&#x2212;2.74</td>
<td align="center" valign="top">0.006</td>
<td align="center" valign="top">&#x2212;1.328376 to &#x2212;0.2213462</td>
</tr>
<tr>
<td align="left" valign="top">_cut1</td>
<td align="center" valign="top">0.5922356</td>
<td align="center" valign="top">0.1698625</td>
<td/>
<td/>
<td/>
</tr>
<tr>
<td align="left" valign="top">_cut2</td>
<td align="center" valign="top">1.671473</td>
<td align="center" valign="top">0.2080382</td>
<td/>
<td/>
<td/>
</tr>
<tr>
<td align="left" valign="top">_cut3</td>
<td align="center" valign="top">2.343554</td>
<td align="center" valign="top">0.2606744</td>
<td/>
<td/>
<td/>
</tr>
</tbody>
</table>
</table-wrap>
<p>The Brant test was conducted to assess the proportional odds assumption of the ordered logistic regression model (X<sup>2</sup> =&#x202F;2.18, <italic>p</italic> =&#x202F;0.3358), thus the ordered logistic regression model is appropriate for the data.</p>
<p>The log-likelihood of the intercept-only model is &#x2212;235.709, while the log-likelihood of the full model is &#x2212;231.770. The deviance (D) with 263 degrees of freedom is 463.539. The likelihood ratio test statistic (LR) with 1 degree of freedom is 7.879, with a <italic>p</italic>-value of 0.005, indicating the model is statistically significant compared to the intercept-only model.</p>
</sec>
<sec id="sec15">
<label>5</label>
<title>Subgroup analysis by AKI stage</title>
<p>Using the occurrence of AKI stages as the dependent variable, multivariate logistic analysis was performed incorporating statistically significant indicators from the two groups mentioned above. The results (<xref ref-type="table" rid="tab4">Table 4</xref>) showed that probiotics could reduce the incidence of stage 1 AKI (OR: 0.4023, 95% CI&#x202F;=&#x202F;0.1895&#x2013;0.8540, <italic>p</italic>&#x202F;=&#x202F;0.018) but not stage 2 (OR: 0.683, 95% CI&#x202F;=&#x202F;0.2083&#x2013;2.242, <italic>p</italic>&#x202F;=&#x202F;0.53) or stage 3 AKI (OR: 0.9007, 95% CI&#x202F;=&#x202F;0.2851&#x2013;2.845, <italic>p</italic>&#x202F;=&#x202F;0.859).</p>
<table-wrap position="float" id="tab4">
<label>Table 4</label>
<caption>
<p>Subgroup analysis of AKI.</p>
</caption>
<table frame="hsides" rules="groups">
<thead>
<tr>
<th>AKI-stage</th>
<th align="center" valign="top">Odds ratio</th>
<th align="center" valign="top">Std. err.</th>
<th align="center" valign="top">95%CI</th>
<th align="center" valign="top">Z</th>
<th align="center" valign="top"><italic>p</italic></th>
</tr>
</thead>
<tbody>
<tr>
<td align="left" valign="top">AKI-1stage</td>
<td align="center" valign="top">0.4023</td>
<td align="center" valign="top">0.1545</td>
<td align="center" valign="top">0.1895&#x2013;0.8540</td>
<td align="center" valign="top">&#x2212;2.37</td>
<td align="center" valign="top">0.018</td>
</tr>
<tr>
<td align="left" valign="top">AKI-2stage</td>
<td align="center" valign="top">0 0.683</td>
<td align="center" valign="top">0.414</td>
<td align="center" valign="top">0.2083&#x2013;2.242</td>
<td align="center" valign="top">&#x2212;0.63</td>
<td align="center" valign="top">0.53</td>
</tr>
<tr>
<td align="left" valign="top">AKI-3stage</td>
<td align="center" valign="top">0.9007</td>
<td align="center" valign="top">0.5285</td>
<td align="center" valign="top">0.2851&#x2013;2.845</td>
<td align="center" valign="top">&#x2212;0.18</td>
<td align="center" valign="top">0.859</td>
</tr>
</tbody>
</table>
</table-wrap>
</sec>
<sec id="sec16">
<label>6</label>
<title>Propensity score matching</title>
<p>Based on the highest AKI stage during the patient&#x2019;s ICU stay, there were 44 patients with stage 1 AKI, 15 with stage 2 AKI, and 18 with stage 3 AKI. Before matching, there was a statistically significant difference in the incidence of stage 1 AKI between the two groups (<italic>p</italic> =&#x202F;0.009); however, there were no statistically significant differences in the incidence of stage 2 AKI (<italic>p</italic> =&#x202F;0.337) or stage 3 AKI (<italic>p</italic> =&#x202F;0.570). We performed a univariate analysis of all potential covariates and found that only creatinine was significantly different between the probiotic and non-probiotic groups (<italic>p</italic> =&#x202F;0.024). After propensity score matching with creatinine as a covariate, a total of 224 cases were matched (112 in the probiotic group and 112 in the non-probiotic group). Graph of PSM was shown in <xref ref-type="fig" rid="fig1">Figure 1</xref>. After matching, the two groups achieved good balance in baseline characteristics (<xref ref-type="table" rid="tab5">Table 5</xref>). The occurrence of stage 1 AKI (<italic>p</italic> =&#x202F;0.019) remained statistically significant. There were no statistically significant differences between the two groups for stage 2 AKI (<italic>p</italic> =&#x202F;0.757) or stage 3 AKI (<italic>p</italic> =&#x202F;0.757).</p>
<fig position="float" id="fig1">
<label>Figure 1</label>
<caption>
<p>Graph of PSM.</p>
</caption>
<graphic xlink:href="fmed-12-1596037-g001.tif"/>
</fig>
<table-wrap position="float" id="tab5">
<label>Table 5</label>
<caption>
<p>Comparison of patient characteristics between probiotic group and non-probiotic group before and after PSM.</p>
</caption>
<table frame="hsides" rules="groups">
<thead>
<tr>
<th rowspan="2">Factors</th>
<th align="center" valign="top" colspan="3">Before PSM</th>
<th align="center" valign="top" colspan="3">After PSM</th>
</tr>
<tr>
<th align="left" valign="top">Non-Probiotics (<italic>n</italic>&#x202F;=&#x202F;146)</th>
<th align="left" valign="top">Probiotics (<italic>n</italic>&#x202F;=&#x202F;121)</th>
<th align="left" valign="top"><italic>p</italic></th>
<th align="left" valign="top">Non-Probiotics (<italic>n</italic>&#x202F;=&#x202F;112)</th>
<th align="left" valign="top">Probiotics (<italic>n</italic>&#x202F;=&#x202F;112)</th>
<th align="left" valign="top"><italic>p</italic></th>
</tr>
</thead>
<tbody>
<tr>
<td align="left" valign="top">Age (year)</td>
<td align="left" valign="top">67 (54, 75)</td>
<td align="left" valign="top">69 (56, 75)</td>
<td align="left" valign="top">0.521</td>
<td align="left" valign="top">67 (56, 75)</td>
<td align="left" valign="top">70 (56.5, 76)</td>
<td align="left" valign="top">0.3652</td>
</tr>
<tr>
<td align="left" valign="top">Gender (M)</td>
<td align="left" valign="top">35 (23.97%)</td>
<td align="left" valign="top">25 (20.66%)</td>
<td align="left" valign="top">0.519</td>
<td align="left" valign="top">28 (25.45%)</td>
<td align="left" valign="top">20 (18.18%)</td>
<td align="left" valign="top">0.193</td>
</tr>
<tr>
<td align="left" valign="top">SOFA</td>
<td align="left" valign="top">8 (6, 10)</td>
<td align="left" valign="top">7 (6, 10)</td>
<td align="left" valign="top">0.8227</td>
<td align="left" valign="top">7 (6, 10)</td>
<td align="left" valign="top">7 (6, 10)</td>
<td align="left" valign="top">0.4352</td>
</tr>
<tr>
<td align="left" valign="top">WBC (&#x00D7;10<sup>9</sup>/L)</td>
<td align="left" valign="top">12.06 (8.2, 16.48)</td>
<td align="left" valign="top">10.79 (7.4, 14.45)</td>
<td align="left" valign="top">0.0759</td>
<td align="left" valign="top">11.85 (8.38, 16.38)</td>
<td align="left" valign="top">10.86 (7.5, 14.89)</td>
<td align="left" valign="top">0.1922</td>
</tr>
<tr>
<td align="left" valign="top">CRP (mg/L)</td>
<td align="left" valign="top">92.95 (24.96, 182.6)</td>
<td align="left" valign="top">86.52 (30.75, 172.6)</td>
<td align="left" valign="top">0.756</td>
<td align="left" valign="top">92.95 (24.93, 155.89)</td>
<td align="left" valign="top">85.65 (30.23, 172.2)</td>
<td align="left" valign="top">0.9698</td>
</tr>
<tr>
<td align="left" valign="top">PCT (ng/mL)</td>
<td align="left" valign="top">0.735 (0.205, 5.06)</td>
<td align="left" valign="top">0.64 (0.17, 4.5)</td>
<td align="left" valign="top">0.7131</td>
<td align="left" valign="top">0.61 (0.167, 2.96)</td>
<td align="left" valign="top">0.65 (0.17, 5.1)</td>
<td align="left" valign="top">0.4658</td>
</tr>
<tr>
<td align="left" valign="top">D-2 (&#x03BC;g/L)</td>
<td align="left" valign="top">3,316 (1,470, 7,411)</td>
<td align="left" valign="top">2405 (1,130, 5,378)</td>
<td align="left" valign="top">0.1664</td>
<td align="left" valign="top">2,978.5 (1,315, 6,619.5)</td>
<td align="left" valign="top">2,380 (1,110, 5,378)</td>
<td align="left" valign="top">0.3822</td>
</tr>
<tr>
<td align="left" valign="top">PLT (&#x00D7;10<sup>9</sup>/L)</td>
<td align="left" valign="top">184.5 (111, 234)</td>
<td align="left" valign="top">172 (111, 231)</td>
<td align="left" valign="top">0.5489</td>
<td align="left" valign="top">191 (116, 244.5)</td>
<td align="left" valign="top">172.6 (102, 230)</td>
<td align="left" valign="top">0.2808</td>
</tr>
<tr>
<td align="left" valign="top">BUN (mmol/L)</td>
<td align="left" valign="top">8.52 (6.2, 13.87)</td>
<td align="left" valign="top">9.08 (5.73, 12.49)</td>
<td align="left" valign="top">0.6749</td>
<td align="left" valign="top">8.14 (5.59, 11.77)</td>
<td align="left" valign="top">9.38 (5.77, 12.68)</td>
<td align="left" valign="top">0.2537</td>
</tr>
<tr>
<td align="left" valign="top">Cr (&#x03BC;mol/L)</td>
<td align="left" valign="top">82 (59, 108)</td>
<td align="left" valign="top">71 (54.5, 106.5)</td>
<td align="left" valign="top">0.024</td>
<td align="left" valign="top">71.5 (55, 101)</td>
<td align="left" valign="top">73 (56.5, 107.05)</td>
<td align="left" valign="top">0.8069</td>
</tr>
<tr>
<td align="left" valign="top">ALB (g/L)</td>
<td align="left" valign="top">31.55 (28.06, 35.4)</td>
<td align="left" valign="top">32.85 (29.25, 35.65)</td>
<td align="left" valign="top">0.199</td>
<td align="left" valign="top">32.15 (28.13, 35.3)</td>
<td align="left" valign="top">33 (29.5, 35.8)</td>
<td align="left" valign="top">0.1892</td>
</tr>
<tr>
<td align="left" valign="top">OI (mmHg)</td>
<td align="left" valign="top">158.13 (104.29, 235)</td>
<td align="left" valign="top">179 (126, 222.5)</td>
<td align="left" valign="top">0.1396</td>
<td align="left" valign="top">168.99 (106.84, 237.08)</td>
<td align="left" valign="top">178.9 (124.58, 222.68)</td>
<td align="left" valign="top">0.5623</td>
</tr>
<tr>
<td align="left" valign="top">Hypertension</td>
<td align="left" valign="top">78 (53.42%)</td>
<td align="left" valign="top">62 (51.24%)</td>
<td align="left" valign="top">0.722</td>
<td align="left" valign="top">60 (54.545%)</td>
<td align="left" valign="top">58 (52.73%)</td>
<td align="left" valign="top">0.789</td>
</tr>
<tr>
<td align="left" valign="top">Diabetes</td>
<td align="left" valign="top">29 (19.86%)</td>
<td align="left" valign="top">21 (17.36%)</td>
<td align="left" valign="top">0.601</td>
<td align="left" valign="top">17 (15.45%)</td>
<td align="left" valign="top">19 (17.27%)</td>
<td align="left" valign="top">0.716</td>
</tr>
<tr>
<td align="left" valign="top">AKI-1</td>
<td align="left" valign="top">32 (%)</td>
<td align="left" valign="top">12 (9.92%)</td>
<td align="left" valign="top">0.009</td>
<td align="left" valign="top">25 (22.73%)</td>
<td align="left" valign="top">12 (10.91%)</td>
<td align="left" valign="top">0.019</td>
</tr>
<tr>
<td align="left" valign="top">AKI-2</td>
<td align="left" valign="top">10 (21.92%)</td>
<td align="left" valign="top">5 (4.13%)</td>
<td align="left" valign="top">0.337</td>
<td align="left" valign="top">6 (5.45%)</td>
<td align="left" valign="top">5 (4.545%)</td>
<td align="left" valign="top">0.757</td>
</tr>
<tr>
<td align="left" valign="top">AKI-3</td>
<td align="left" valign="top">11 (7.53%)</td>
<td align="left" valign="top">7 (5.785%)</td>
<td align="left" valign="top">0.570</td>
<td align="left" valign="top">5 (4.545%)</td>
<td align="left" valign="top">6 (5.45%)</td>
<td align="left" valign="top">0.757</td>
</tr>
</tbody>
</table>
</table-wrap>
<p>To demonstrate balance after PSM, we calculated the standardized mean difference (SMD) for creatinine levels between the matched groups. The SMD was found to be &#x2212;0.00286, this ensures that the matched groups are comparable, thereby strengthening the validity of our findings.</p>
</sec>
<sec sec-type="discussion" id="sec17">
<label>7</label>
<title>Discussion</title>
<p>Among mechanically ventilated patients with severe pneumonia, we found that probiotics can reduce the incidence of stage 1 AKI. Our findings add new evidence to the clinical application of probiotics. AKI presents significant challenges in pediatric care (<xref ref-type="bibr" rid="ref15">15</xref>). Thus future similar perspective studies could be also made in children.</p>
<p>Common causes of AKI in patients with severe pneumonia include drug-induced nephrotoxicity (<xref ref-type="bibr" rid="ref16">16</xref>), extra-renal tissue damage (<xref ref-type="bibr" rid="ref17">17</xref>), and ischemia&#x2013;reperfusion injury (IRI) (<xref ref-type="bibr" rid="ref18">18</xref>). Studies have shown that oxidative stress (<xref ref-type="bibr" rid="ref19">19</xref>), inflammation [unreferenced], mitochondrial damage (<xref ref-type="bibr" rid="ref20">20</xref>), and immune dysfunction (<xref ref-type="bibr" rid="ref21">21</xref>) are core mechanisms leading to the development and progression of AKI.</p>
<p>Recent studies have demonstrated that probiotics can mitigate the severity of gastrointestinal adverse reactions induced by antitumor treatment and restore disrupted gut microbiota (<xref ref-type="bibr" rid="ref22">22</xref>). In a definitive efficacy trial, probiotics were employed as an adjunctive therapy for patients with depression (<xref ref-type="bibr" rid="ref23">23</xref>). Uremic toxins derived from gut dysbiosis can exacerbate renal dysfunction and fibrosis. For instance, the gut-derived metabolite trimethylamine-N-oxide (TMAO) directly contributes to the progression of renal dysfunction and is associated with an increased risk of mortality (<xref ref-type="bibr" rid="ref24">24</xref>). Certain probiotics prevent AKI by reducing inflammation and lowering oxidative stress levels. <italic>Lactobacillus salivarius</italic> BP121 exerts renoprotective effects primarily by modulating tight junction protein assembly through AMPK and TLR4 pathways and inhibiting the production of uremic toxins such as indoxyl sulfate (IS) and p-cresyl sulfate (PCS) (<xref ref-type="bibr" rid="ref25">25</xref>). In mice with <italic>Escherichia coli</italic>-induced pyelonephritis, probiotic administration before and after sepsis significantly improved renal function, reduced inflammation, and attenuated renal fibrosis (<xref ref-type="bibr" rid="ref26">26</xref>). Probiotics competitively inhibit pathogenic bacteria, maintain gut microbiota balance, and reduce the translocation of toxins and inflammatory mediators into the bloodstream. Additionally, they enhance gut epithelial barrier function, decrease endotoxin and bacterial translocation, and attenuate systemic inflammatory responses.</p>
<p>After AKI onset, probiotics have demonstrated efficacy in improving renal function, potentially by lowering creatinine and urea levels and significantly reducing pro-inflammatory cytokines like IL-1&#x03B2;, IL-6, TNF-<italic>&#x03B1;</italic>, and MCP-1 (<xref ref-type="bibr" rid="ref27">27</xref>). They modulate immune cell activity, curb the release of pro-inflammatory cytokines (e.g., TNF-&#x03B1;, IL-6), and mitigate systemic inflammatory responses, while also boosting anti-inflammatory cytokines (e.g., IL-10) to alleviate inflammatory kidney damage. Probiotics enhance immune function and infection resistance by activating immune cells such as macrophages and T-cells. Gut dysbiosis can heighten uremic toxin production and foster AKI development (<xref ref-type="bibr" rid="ref27">27</xref>). In a mouse renal ischemia&#x2013;reperfusion injury (IRI) model (<xref ref-type="bibr" rid="ref28">28</xref>), the probiotic <italic>Bifidobacterium bifidum</italic> (BGN4) increased gut microbiome evenness and curbed the proliferation of AKI-linked bacteria like Enterobacteriaceae and Bacteroidaceae. BGN4 intervention notably reduced tubular damage scores, neutrophil and macrophage infiltration, and renal IL-6 mRNA expression in mice (<xref ref-type="bibr" rid="ref28">28</xref>). Additionally, BGN4 lowered plasma low-density lipoprotein, alanine aminotransferase, and aspartate aminotransferase levels, indicating its potential to alleviate renal IRI and AKI-related liver damage (<xref ref-type="bibr" rid="ref29">29</xref>).</p>
<p>Additionally, some probiotics, such as ATCC 4356, can activate the nuclear factor erythroid 2-related factor 2 (Nrf2)/heme oxygenase-1 (HO1) axis, a crucial pathway for antioxidant stress, reduce the expression of malondialdehyde (MDA), and promote the expression of superoxide dismutase (SOD) and Nrf2. ATCC 4356 also exerts anti-inflammatory effects by regulating the PI3K/Akt signaling pathway (<xref ref-type="bibr" rid="ref30">30</xref>).</p>
<p>Complement system is considered a key pathogenic mediator in the development of several renal diseases (<xref ref-type="bibr" rid="ref31">31</xref>). Kidney is particularly susceptible to complement-mediated injury mainly due to its ultrafiltration function, low expression of complement regulatory factors, and local complement production (<xref ref-type="bibr" rid="ref32">32</xref>). It can cause kidney injury and also cause AKI. Higher inflammation can lead to a hyperactive complement system, which can damage the kidney. Probiotics may influence the activation and regulation of complement components. This helps to reduce the release of factors that trigger complement activation.</p>
<p>Our study found that probiotics reduced the incidence of stage 1 acute kidney injury (AKI) but were ineffective for stage 2 and stage 3 AKI. This may be attributed to the fact that stage 1 AKI is milder, allowing probiotics to effectively intervene by modulating the gut microbiota and reducing inflammation. In contrast, stage 2 and stage 3 AKI are more severe and involve more complex pathological mechanisms, making single-intervention strategies such as probiotics insufficient. Probiotics primarily exert their effects by modulating the gut microbiota, reducing inflammation, and mitigating oxidative stress, which may be particularly effective in the early stages of AKI. In late-stage AKI, however, widespread systemic inflammation and multi-organ damage occur, and the effects of probiotics may be inadequate to reverse these complex pathological changes. Additionally, in stage 1 AKI, gut barrier function may remain relatively intact, enabling probiotics to exert their beneficial effects. In stage 2 and stage 3 AKI, severe damage to the gut barrier may hinder the ability of probiotics to function effectively. The immune response in stage 1 AKI is also milder, and probiotics may alleviate renal damage by modulating the immune system. In contrast, the immune response in late-stage AKI is more intense, and the regulatory effects of probiotics may be insufficient to control excessive immune activation. Moreover, the dosage and duration of probiotic administration may be adequate for stage 1 AKI but may require higher doses or extended treatment periods to address the severity of stage 2 and stage 3 AKI. Furthermore, patients with stage 2 and stage 3 AKI often present with additional complications or receive multiple concurrent treatments, which may interfere with the efficacy of probiotics.</p>
<p>Severe pneumonia and sepsis are closely related and interconnected. Pneumonia, especially severe pneumonia, is one of the most common causes of sepsis. The pathogenetic mechanisms of both diseases are similar in that they both involve the body&#x2019;s immune response to infection, which can result in tissue damage and organ dysfunction. Additionally, sepsis patients are also at an increased risk of developing pneumonia, due to their weakened immune systems and the use of invasive medical devices. In clinical practice, a significant percentage of pneumonia cases are misdiagnosed as septic shock, and severe sepsis is often identified as a critical complication of pneumonia. Therefore, given the close relationship between severe pneumonia and sepsis, we shift our focus from severe pneumonia to sepsis to further explore the relevant research questions.</p>
<sec id="sec18">
<label>7.1</label>
<title>Limitations</title>
<p>Firstly, the sample size of this study is relatively small, particularly for stage 2 and stage 3 AKI cases. A larger sample size is required to enhance statistical power. Secondly, our data were derived from a retrospective study, and a randomized controlled trial (RCT) is recommended to further validate the effects of probiotics. As our study adopts an observational design, despite multivariate and propensity score matching (PSM) adjustments, there may still be residual confounding factors influencing the results. Moreover, the absence of microbiota profiling data, cytokines and claudin weakens the support for our mechanistic claims about the potential renal - protective effects of probiotics. Thirdly, the dosage, type, and duration of probiotics administration need to be further clarified. In clinical practice, there are still many issues that need to be addressed such as how to determine the optimal timing of probiotic intervention (whether it is better to administer probiotics early in the onset of AKI to prevent or mitigate kidney damage or at a specific stage of AKI progression), how to optimize probiotic dosage selection (tailoring dosage schemes according to patients&#x2019; individual characteristics, disease severity, and dynamic changes in microbiota), and how to stratify patients according to AKI stages to better assess the efficacy and safety of probiotics in different patient groups. Fourth, while these animal experimental results provide biological plausibility for the potential role of probiotics in AKI, extrapolating these findings to ICU patients with severe pneumonia carries certain risks.</p>
</sec>
</sec>
<sec sec-type="conclusions" id="sec19">
<label>8</label>
<title>Conclusion</title>
<p>Probiotics were associated with a lower incidence of stage 1 AKI in patients with severe pneumonia. However, our research was a single-center retrospective study, and multi-center randomized controlled studies would be needed in the future for validation. Defining optimal probiotic strains, dosages, and treatment windows would enhance the translational impact of the conclusions in future studies.</p>
</sec>
</body>
<back>
<sec sec-type="data-availability" id="sec20">
<title>Data availability statement</title>
<p>The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.</p>
</sec>
<sec sec-type="ethics-statement" id="sec21">
<title>Ethics statement</title>
<p>The studies involving humans were approved by the Medical Ethics Committee of Peking University Third Hospital (Ethics approval number: M20250221). The studies were conducted in accordance with the local legislation and institutional requirements. Written informed consent to participate in this study was not required from the participants due to the retrospective nature of the study and in accordance with the national legislation and the institutional requirements.</p>
</sec>
<sec sec-type="author-contributions" id="sec22">
<title>Author contributions</title>
<p>QZ: Writing &#x2013; original draft. XFS: Writing &#x2013; original draft, Writing &#x2013; review &#x0026; editing.</p>
</sec>
<sec sec-type="funding-information" id="sec23">
<title>Funding</title>
<p>The author(s) declare that no financial support was received for the research and/or publication of this article.</p>
</sec>
<sec sec-type="COI-statement" id="sec24">
<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="sec25">
<title>Generative AI statement</title>
<p>The authors declare that no Gen AI was used in the creation of this manuscript.</p>
</sec>
<sec sec-type="disclaimer" id="sec26">
<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>
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