A Retrospective Cohort Study: Unveiling the Association between Pre - ICU Use of Angiotensin - converting Enzyme Inhibitors and Angiotensin II Receptor Blockers and Mortality in Septic Patients

A Retrospective Cohort Study: Unveiling the Association between Pre - ICU Use of Angiotensin - converting Enzyme Inhibitors and Angiotensin II Receptor Blockers and Mortality in Septic Patients | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article A Retrospective Cohort Study: Unveiling the Association between Pre - ICU Use of Angiotensin - converting Enzyme Inhibitors and Angiotensin II Receptor Blockers and Mortality in Septic Patients Zhihu Zhou, Zhe Li, Qihai Wan, Yi Yu This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8137597/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 8 You are reading this latest preprint version Abstract Background/Aims : Angiotensin-converting enzyme inhibitors (ACEIs) and angiotensin II receptor blockers (ARBs) possess anti-inflammatory properties. The purpose of this study was to find out what impact the use of ACEIs and ARBs before ICU admission has on the clinical conditions of patients with sepsis. Methods Patients diagnosed with sepsis were included in this study using data extracted from the Medical Information Mart for Intensive Care-IV (MIMIC-IV) database. The primary endpoints assessed were the 30- and 90-day mortality rates, along with the length of stay in the intensive care unit (ICU). Statistical analysis was conducted using multivariable Cox regression and linear regression models, while propensity score matching (PSM) was used to ensure the reliability and validity of the results. Results Among the 22,783 patients hospitalized for sepsis. Multivariable Cox regression analysis revealed that the utilization of ACEIs/ARBs was significantly associated with a notable reduction in 90 - day mortality (hazard ratio (HR) = 0.36, 95% confidence interval: 0.33–0.4, p < 0.001). Regarding safety considerations, the use of ACEIs/ARBs was associated with an increased risk of acute kidney injury (AKI) (Odds Ratio (OR) = 1.09, 95% CI: 1.01–1.17, p = 0.026) and a higher incidence of vasopressor drug use (OR = 1.11, 95% CI: 1.04–1.19, p = 0.002). However, ACEIs/ARBs were linked with a reduced need for continuous renal replacement therapy (OR = 0.77, 95% CI: 0.66–0.9, p = 0.001). Conclusions The pre - ICU administration of ACEIs/ARBs to patients with sepsis may be associated with lower mortality rates. Angiotensin converting enzyme inhibitor Angiotensin II Sepsis Mortality Intensive Care Unit Figures Figure 1 Figure 2 Figure 3 Introduction Sepsis emerges as a consequence of a dysregulated immune response subsequent to an infection and remains a significant challenge for public health( 1 , 2 ). Sepsis is a multifaceted condition instigated by various infectious agents and perpetuated by unregulated activation and dysfunction of diverse immune and inflammatory cells and mediators. In conjunction with endocrine dysregulation, sepsis can also affect the renin–angiotensin–aldosterone system (RAAS)( 3 , 4 ). Despite recent advances in medicine, the mortality rate associated with sepsis remains high. The principal effector of the RAAS, angiotensin II, is recognized as a significant inflammatory factor associated with organ failure and mortality( 5 – 7 ). Angiotensin II induces upregulation of tissue factor expression, a pivotal contributor to thrombosis and consequent microvascular ischemia in sepsis, concomitant with proinflammatory cytokines such as tumor necrosis factor-alpha and interleukin-1( 8 , 9 ). In animal models of sepsis, interventions aimed at modulating the RAAS have been associated with decreased levels of proinflammatory cytokines, improved cardiovascular function, and elevated survival rates( 10 , 11 ). Therefore, it has been hypothesized that RAAS antagonists could ameliorate organ failure and reduce mortality rates, particularly when promptly administered at the onset of sepsis( 12 , 13 ). The RAAS plays a pivotal role in maintaining normal systemic function. Previous studies have demonstrated noteworthy alterations in RAAS dynamics during sepsis( 14 , 15 ). Thus, given the pivotal role of the RAAS in the pathophysiology of sepsis, is the use of ACEIs or ARBs protective in patients with sepsis? While some studies have suggested that the administration of ACEIs/ARBs before illness is linked with reduced mortality in patients with sepsis( 16 – 23 ), many studies have shown the opposite( 24 – 27 ), so further investigation is required. Building upon existing data, we postulated that ACEIs/ARBs may aid in decreasing sepsis-related mortality. Consequently, we conducted a novel retrospective investigation using the Medical Information Mart for Intensive Care (MIMIC-IV) dataset, spanning from 2008 to 2019. The primary objective of this study was to explore the potential association between pre - ICU use of ACEI/ARB and mortality rates in patients with sepsis. Methods Patients diagnosed with sepsis, either with or without previous exposure to ACEIs/ARBs prior to ICU admission, were enrolled in the study using data from the Medical Information Mart for Intensive Care (MIMIC)-IV (version 2.2), a longitudinal database derived from a single center in the USA and comprising records from 2008 to 2019(28). Yi Yu (one of the authors) obtained authorization to access the database under certificate ID 6477678. This study adhered to the Guidelines for Strengthening the Reporting of Observational Studies in Epidemiology to ensure proper reporting standards(29). Ethics approval and consent to participate This study involving human participants and human data/material was conducted in strict compliance with the ethical standards of the 1964 Helsinki Declaration and its later amendments or comparable ethical standards. For studies involving human participants, these were reviewed and approved by the Institutional Review Boards (IRBs) of both the Massachusetts Institute of Technology and Beth Israel Deaconess Medical Center. Written informed consent was obtained from all participants or their legally authorized representatives. Study population and data extraction The study recruited patients diagnosed with sepsis based on their discharge summaries. The diagnosis of sepsis followed the Sepsis 3.0 criteria, which delineate sepsis as a severe condition marked by organ dysfunction stemming from an uncontrolled response to infection. Clinically, organ dysfunction was determined by an increase in the Sequential (Sepsis-related) Organ Failure Assessment (SOFA) score of ≥2 points(30, 31). The study exclusively included patients aged ≥18 years. In cases where a single patient had multiple ICU admissions, only the initial admission was considered for analysis. Patients who stayed in the ICU <24 h were excluded. Data on patient demographics, vital signs, laboratory findings, underlying conditions, clinical severity scores, and other admission details were collected for analysis. ACEI/ARB use The utilization of ACEIs/ARBs before ICU admission was ascertained based on the existence of prescriptions for these medications within the MIMIC - IV database. ACEIs included medications such as Benazepril, Captopril, Enalapril, Fosinopril, Lisinopril, Quinapril, and Moexipril, among others. ARBs included drugs such as Losartan, Valsartan, Irbesartan, Olmesartan, and Candesartan, among others. Covariates Risk factors for mortality associated with sepsis were documented(32-34). The covariates included in the analysis were age, sex, body mass index (BMI), respiratory rate, temperature, pulse oxygen saturation (SpO 2 ), white blood cell (WBC) count, hemoglobin level, hematocrit, platelet count, and glucose level. The study gathered data on various health indicators, including SOFA score, and comorbid conditions such as cardiovascular disease, kidney disease, liver disease, malignancy, neurological disease, and chronic pulmonary disease. Additionally, the researchers extracted demographic information related to race. Patient outcomes This study mainly aimed to examine the 30 - and 90 - day mortality rates of septic patients with or without pre - ICU ACEIs/ARBs treatment. Secondary endpoints included the duration of ICU admission, the occurrence of acute kidney injury (AKI) events, the need for renal replacement therapy (RRT) or mechanical ventilation (MV), and use of vasopressors. Statistical analysis Baseline characteristics of patients in different groups The baseline characteristics of patients were categorized into distinct groups. Categorical data are expressed as frequencies (percentages), while continuous data are reported as the mean ± standard deviation, or median (interquartile range), as appropriate. Statistical analyses, including analysis of variance or rank sum testing, were employed to evaluate differences in continuous variables. Chi-squared or Fisher’s exact tests were used to compare the characteristics of the study population across different outcome groups. Missing data were imputed using the median value, because 5% of vital signs and laboratory parameters were missing. Because of the low percentage of missing data (ranging from 0.5% to 8%) for BMI, no imputation method was employed. We evaluated survival outcomes by constructing survival curves using the Kaplan–Meier methodology and conducting log-rank analysis. The association between ACEI/ARB use and mortality was assessed through multivariate Cox regression analysis. The adjusted Cox model was used to control for various covariates in the analysis. A total of five models were used for the regression analysis. Additional analyses included subgroup analyses and assessments of interactions, adjusting for relevant covariates. Multicollinearity was analyzed by assessing the variance inflation factor (VIF) among involved variables. Multicollinearity was considered to exist if VIF >2. Linear regression analyses were used to investigate the association between ACEI/ARB use and the length of ICU stay, ventilation time, and vasopressor duration. To analyze secondary outcomes, two statistical models were employed: unadjusted and fully adjusted. To enhance the robustness of the analysis, propensity score matching (PSM) was conducted using a 1:1 nearest neighbor matching algorithm with a caliper width of 0.1. All statistical analyses were performed using STATA software (version 17.0) in conjunction with R packages (http://www.R-project.org, The R Foundation) and Free Statistics software version 1.8(35). Statistical significance was defined as p < 0.05 with a two-tailed test. Results Participants A total of 33,177 patients met the criteria for sepsis. After excluding repeated ICU admissions, patients under the age of 18, and those with an ICU stay of <24 h, the final cohort comprised 22,783 patients. The selection process for study participants is illustrated in Figure 1 . Baseline characteristics The study included 22,783 patients, with mean age 65.0 ± 16.1 years, of whom 58.1% were male. Table 1 shows the baseline characteristics of the patient cohort. A comparative analysis of the two datasets revealed several disparities: the cohort not using ACEIs/ARBs tended to be younger, included a higher proportion of females, exhibited higher SOFA scores, had a lower Charlson comorbidity index, experienced significantly elevated 30- and 90-day mortality rates, faced an increased risk of AKI and continuous renal replacement therapy (CRRT), and showed higher rates of ventilation use. The relationship between use of ACEIs/ARBs and mortality among patients with sepsis Survival analyses using the Kaplan–Meier method revealed a significant decrease in mortality at 90 days among patients who used ACEIs/ARBs compared with those who did not (log-rank test: p < 0.0001) ( Figure 2 ). In the univariate analysis of mortality risk, the use of ACEIs/ARBs was significantly associated with a lower mortality rate compared with non-use of ACEIs/ARBs, with a hazard ratio (HR) of 0.34 and a 95% confidence interval (CI) of 0.3–0.37 for 30-day mortality (p < 0.001), and a HR of 0.34 and a 95% CI of 0.31–0.38 for 90-day mortality (p < 0.001) ( Table 2 ). Subsequently, in the comprehensive multivariate Cox regression analysis ( Table 2 ), we consistently observed that the HRs for ACEI/ARB use remained significant across all models (with HRs ranging from 0.31 to 0.36, all with p-values < 0.001). After adjusting for all covariates listed in Table 2, a 65% reduction in the risk of 30-day mortality was evident among patients using ACEIs/ARBs (HR = 0.35, 95% CI: 0.31–0.38, p < 0.001, model 5). Similarly, a 64% decrease in the risk of 90-day mortality was observed in ACEI/ARB users (HR = 0.36, 95% CI: 0.33–0.40, p < 0.001, model 5). Relationship between ACEI/ARB use and other outcomes When considering all the covariates listed in Table 3 , it was determined that the use of ACEIs/ARBs did not significantly impact the length of ICU stay (β = 0.48, 95% CI = −3.6 to 4.32). However, the use of ACEIs/ARBs did show a significant effect on the odds of AKI on the 7 th day (OR = 1.09, 95% CI = 1.01–1.17) and on the risk of requiring vasoactive drugs (OR = 1.11, 95% CI = 1.04–1.19). In addition, it was associated with a decreased likelihood of requiring CRRT (OR = 0.77, 95% CI = 0.66–0.9) and a reduced need for ventilation (OR = 0.89, 95% CI = 0.83–0.96) ( Table S1 ). Furthermore, the use of ACEIs/ARBs was correlated with a shorter ventilation duration (β = −2.53, 95% CI = −4.12 to −0.93) ( Table S2 ) and linked to a shorter duration of vasoactive drug use (β = −3.2, 95% CI = −5.22 to −1.18) ( Table S1 ). PSM further enhanced the robustness of these results. Subgroup analysis and sensitivity analysis Following PSM, the two groups were comprised of 7,720 well-matched pairs, with no significant differences observed in key indicators between the groups. Notably, among the 7,720 pairs in the propensity-matched cohort, patients receiving ACEIs/ARBs exhibited a significantly lower 30-day mortality risk [1,140 (14.8%) vs. 425 (5.5%), p < 0.001], as well as a lower 90-day mortality risk [1,208 (15.6%) vs. 466 (6%), p < 0.001] ( Table S2 ). In the multivariate Cox regression model, accounting for all covariates, the HR for 30-day mortality was 0.35 (95% CI: 0.32–0.4, p < 0.001), and the HR for 90-day mortality was 0.36 (95% CI: 0.33–0.4, p < 0.001) ( Table 2 ). In particular, subgroup analyses indicated that the protective effect of ACEIs/ARBs was more pronounced among individuals aged <60 years, with a BMI ≥25, no renal disease, SOFA score ≥5, and lactate level ≥4, with no other significant interactions in the subgroups. Comparable trends were observed for 90-day mortality ( Figure 3 ) and 30-day mortality ( Figure S1 ). Discussion The pre - ICU administration of ACEIs/ARBs to patients suffering from sepsis might be correlated with reduced mortality rates. Studies have shown that ACEIs and ARBs can downregulate the systemic inflammatory response(36, 37). Several studies have highlighted potential benefits in terms of mortality and morbidity for patients with sepsis(20, 22, 27, 38, 39). In a recent large cohort study involving >50,000 hospitalized patients with sepsis, prior use of ACEIs was linked with reduced 30-day and 90-day mortality compared with non-users, irrespective of gender, age, underlying comorbidities, and sources of infection in a propensity-matched cohort(20). A 2019 study examining the effects of preadmission ACEI and ARB use found a reduction in overall hospital mortality from sepsis (OR 0.93, 95% CI 0.88–0.98, p = 0.0085; and OR 0.85, 95% CI 0.81–0.90, p < 0.0001), respectively(21). These conclusions align with our findings. There is conflicting evidence regarding the efficacy of ACEIs/ARBs administration in reduction of the risk of sepsis-related death and improvement of the prognosis. A nested case-control study involving hypertensive adults in the United Kingdom revealed that the use of ACEIs was linked with an elevated risk of sepsis and 30-day mortality(24). In 2017, a prospective observational study demonstrated no significant association between prior use of ACEIs/ARBs and 30-day mortality among patients with sepsis(25). Pre-exposure to RASS inhibition did not confer a significant improvement in the prognosis of patients with septic shock(26, 27). Further rigorous clinical investigations are essential to comprehensively assess the preventive and therapeutic effectiveness of ACEIs/ARBs in managing sepsis. The mechanism by which ACEIs/ARBs are linked with a reduced risk of mortality in patients with sepsis remains unclear. One suggested protective mechanism underlying this associated decreased mortality is the anti-inflammatory effect of increased levels of angiotensin-converting enzyme (ACE) 2(40), as demonstrated in a murine model of acute lung injury. ACE2-knockout mice exhibited more severe lesions following pulmonary insult compared with their wild-type littermates(41, 42). In addition to the pulmonary protective effects of ACEIs, the impact on systemic hemodynamics and renal function must also be considered. Further research is necessary to understand the underlying mechanisms that could elucidate our findings, particularly with human data. In ICU patients, there is a significant association between the severity of AKI and mortality rates, especially in individuals with septic shock(43). The impact of prior use of ACEIs/ARBs on the occurrence of AKI among this patient cohort is debatable. A similar study indicated a significant association between ACEIs/ARBs and a higher stage of sepsis-related kidney injury during hospitalization, coupled with an increased incidence of stage 3 AKI within the first week in the ICU(27). This observation can potentially be explained by the more pronounced reduction in intraglomerular pressure in patients with a history of chronic RASS inhibition compared with those without such inhibition. In sepsis, the decreased renal blood flow can lead to a decline in filtration fraction, resulting in elevated serum creatinine levels and decreased urine output. Our investigation supports these findings, revealing a 9% higher likelihood of AKI development and an 11% higher likelihood of vasopressor requirement among users of ACEIs/ARBs compared with non-users. However, the administration of ACEIs/ARBs was associated with a reduced need for CRRT and a shorter duration of vasoactive drug usage. A recent post-hoc analysis by Demiselle et al . indicated that patients with prior RASS inhibition demonstrated a reduced risk of AKI onset during their ICU admission and may benefit from improved mean arterial pressure(26). This pattern was primarily observed in individuals using ARBs. Angiotensin II triggers vasoconstriction in the efferent arteriole; therefore, by blocking type 1 angiotensin II receptors, ARBs increase ACE2 levels, which counteract the effects of angiotensin II. ACE2 has been demonstrated to have protective and anti-inflammatory effects on the kidneys by enhancing nitric oxide production, thereby inducing vasodilation and enhancing renal blood flow(40). As a result, the preadministration of ARBs may elevate ACE2 levels, inducing vasodilation in renal arteries and reducing the incidence of AKI in patients with sepsis or septic shock. A noteworthy observation is the lack of disparity in the need for CRRT between the two groups, which remains perplexing. Strengths and limitations Our study has four main strengths. First, we used a comprehensive and publicly available database, ensuring the reliability and completeness of our data. Second, while the impact of ACEIs/ARBs on sepsis has been explored extensively, conclusive findings for patients with sepsis remain elusive. Our results show that using ACEIs/ARBs is linked to a lower mortality risk in sepsis patients. Third, we performed multiple sensitivity analyses to validate our results. (1) Cox regression analyses were adjusted using multiple models to address confounding effects, which remained consistent even after full adjustments. (2) PSM analysis was also conducted, yielding consistent outcomes. This rigorous analytical approach enhances the credibility and internal validity of our findings. Lastly, given the extensive use of ACEIs/ARBs for cardiovascular conditions, our results have broader implications beyond the population with sepsis. The limitations of our study align with those commonly encountered in observational research. First, our analysis was impeded by a substantial amount of missing data, which prevented the generation of statistics regarding the effects of ACEI/ARB levels on mortality. Consequently, definitively establishing the association between RASS and sepsis was not possible, leaving the optimal RASS value in sepsis unresolved. Second, an inherent constraint stems from the retrospective nature of our investigation. Unaccounted for potential confounding variables may exist, and our dataset lacks additional markers of inflammation beyond WBC counts. Third, caution is warranted when generalizing the findings of our study, as it was confined to a single nation (the USA) and a specific ICU setting. However, our study benefited from a substantial and fairly representative sample size. Subsequent multicenter prospective studies should be conducted to validate our results. Fourth, a multitude of factors influence the mortality risk associated with sepsis, such as educational attainment, smoking history, baseline cardiac function, hormone therapy, and other medical histories, which were not included in the MIMIC-IV database. Furthermore, our retrospective clinical investigation did not clarify the specific impact of ACEIs/ARBs on RASS in individual patients because of the lack of details regarding the duration and dosage of ACEI/ARB administration. Additional data could not be provided because of the non-randomized design of the study. Conclusion The current evidence suggests that the pre - ICU administration of ACEIs/ARBs to patients with sepsis may be associated with lower mortality rates. However, additional randomized controlled trials are necessary to confirm the hypotheses posited in this article. Abbreviations ACEIs Angiotensin-converting enzyme inhibitors ARBs Angiotensin II receptor blockers MIMIC-IV Medical Information Mart for Intensive Care-IV ICU Intensive care unit HR Hazard ratio AKI Acute kidney injury OR Odds Ratio PSM Propensity score matching RAAS Renin–angiotensin–aldosterone system SOFA Sequential Organ Failure Assessment BMI Body mass index SpO 2 Pulse oxygen saturation WBC White blood cell RRT Renal replacement therapy MV Mechanical ventilation VIF Variance inflation factor PSM Propensity score matching CRRT Continuous renal replacement therapy Declarations Ethics approval and consent to participate For studies involving human participants, these were reviewed and approved by the Institutional Review Boards (IRBs) of both the Massachusetts Institute of Technology and Beth Israel Deaconess Medical Center. Written informed consent was obtained from all participants or their legally authorized representatives. Consent for publication All authors of the manuscript consent to its publication in BMC Cardiovascular Disorders. Availability of data and materials The data underlying this study will be shared by the authors upon reasonable request. Competing Interests The authors declare no conflicting financial interests relevant to this article. Funding This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors. Authors' contributions Zhihu Zhou conducted data analysis and wrote the manuscript. Zhe Li conducted data analysis and modified the manuscript. Qihai Wan conducted data collection. Yi Yu conducted data collection and data interpretation. Zhihu Zhou designed the study and reviewed the manuscript. All authors contributed to the article and approved the submitted version. Acknowledgements We thank the Free Statistics team for providing technical assistance and valuable tools for data analysis and visualization. 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Angiotensin-Converting Enzyme 2 Protects from Severe Acute Lung Failure. Nature. 2005;436(7047):112–6. 10.1038/nature03712 . Epub 2005/07/08. Vaara ST, Pettila V, Kaukonen KM, Bendel S, Korhonen AM, Bellomo R, et al. The Attributable Mortality of Acute Kidney Injury: A Sequentially Matched Analysis*. Crit Care Med. 2014;42(4):878–85. 10.1097/CCM.0000000000000045 . Epub 2013/11/10. Tables Table 1. Characteristics of participants at baseline Variable Total (n = 22,783) No use of ACEIs/ARBs (n = 13,374) ACEI/ARB use (n = 9,409) P Age, years 65.0 ± 16.1 62.8 ± 17.4 68.2 ± 13.4 < 0.001 Sex, male, n (%) 13,229 (58.1) 7,657 (57.3) 5,572 (59.2) 0.003 BMI, kg/m 2 28.6 ± 6.5 28.0 ± 6.2 29.4 ± 6.8 < 0.001 Race, n (%) < 0.001 White 15,421 (67.7) 8,900 (66.5) 6,521 (69.3) Black 1,914 ( 8.4) 857 (6.4) 1,057 (11.2) Other 5,448 (23.9) 3,617 (27) 1,831 (19.5) WBC (×10 9 ) 13.1 ± 9.1 13.4 ± 9.7 12.7 ± 8.1 < 0.001 HB (g/L) 10.6 ± 2.0 10.6 ± 2.0 10.5 ± 2.0 0.778 PLT (×10 9 ) 204.3 ± 111.5 199.5 ± 114.1 211.1 ± 107.4 < 0.001 Respiration rate (bpm) 19.6 ± 4.0 19.8 ± 4.2 19.4 ± 3.8 < 0.001 Temperature (°C) 36.9 ± 0.6 36.9 ± 0.6 36.8 ± 0.5 < 0.001 SpO 2 (%) 97.0 ± 2.2 96.9 ± 2.3 97.0 ± 2.0 0.009 Heart rate (bpm) 86.7 ± 16.0 88.2 ± 16.4 84.5 ± 15.1 < 0.001 MAP (mmHg) 76.8 ± 10.3 76.6 ± 10.1 77.1 ± 10.6 < 0.001 PT (s) 16.5 ± 8.3 16.5 ± 8.1 16.3 ± 8.5 0.049 APPT (s) 37.6 ± 17.6 37.3 ± 17.4 37.9 ± 18.0 0.015 PaO 2 (mmHg) 160.5 ± 85.6 157.3 ± 84.1 165.0 ± 87.5 < 0.001 Lactate (mmol/L) 1.9 (1.5, 2.5) 1.9 (1.5, 2.6) 1.9 (1.4, 2.4) < 0.001 BUN (mg/dL) 20.5 (14.0, 34.0) 19.0 (13.0, 32.5) 22.0 (15.5, 35.5) < 0.001 Cr (mg/dL) 1.0 (0.8, 1.6) 1.0 (0.7, 1.5) 1.1 (0.8, 1.6) < 0.001 Glucose (mmol/L) 145.2 ± 62.8 141.3 ± 58.5 150.6 ± 68.0 < 0.001 Charlson Comorbidity Index 5.7 ± 2.9 5.3 ± 3.0 6.2 ± 2.6 < 0.001 SOFA score 5.9 ± 3.3 6.1 ± 3.5 5.7 ± 3.0 < 0.001 Myocardial infarct, n (%) 3,573 (15.7) 1,562 (11.7) 2,011 (21.4) < 0.001 Congestive heart failure, n (%) 6,187 (27.2) 2,644 (19.8) 3,543 (37.7) < 0.001 Cerebrovascular disease, n (%) 3,105 (13.6) 1,637 (12.2) 1,468 (15.6) < 0.001 Severe liver disease, n (%) 1,274 ( 5.6) 1090 (8.2) 184 (2) < 0.001 Diabetes, n (%) < 0.001 No 15,911 (69.8) 10,478 (78.3) 5,433 (57.7) complications 5,366 (23.6) 2,315 (17.3) 3,051 (32.4) With complications 1,506 ( 6.6) 581 (4.3) 925 (9.8) ICU stay, days 3.0 (1.8, 6.0) 3.0 (1.8, 6.2) 3.0 (1.8, 5.8) 0.001 30-day mortality, n (%) 2,576 (11.3) 2,059 (15.4) 517 (5.5) < 0.001 90-day mortality, n (%) 2,756 (12.1) 2,192 (16.4) 564 (6) < 0.001 CRRT, n (%) 1,375 ( 6.0) 943 (7.1) 432 (4.6) < 0.001 Vasopressors, n (%) 11,297 (49.6) 6,581 (49.2) 4,716 (50.1) 0.174 Ventilation, n (%) 11,496 (50.5) 6,917 (51.7) 4,579 (48.7) < 0.001 AKI in 7 days, n (%) 16,905 (74.2) 9,633 (72) 7,272 (77.3) < 0.001 For each variable, mean ± standard deviation, median (interquartile range), or number (percentage) was reported (as appropriate). ACEIs, angiotensin-converting enzyme inhibitors; ARBs, angiotensin II receptor blockers; BMI, body mass index; WBC, white blood cells; HB, hemoglobin; PLT, platelets; SpO 2 , pulse oxygen saturation; MAP, mean arterial pressure; PT, prothrombin time; APTT, activated partial thromboplastin time; PaO 2 , arterial partial pressure of oxygen; BUN, blood urea nitrogen; Scr, serum creatinine; SOFA, Sequential Organ Failure Assessment; ICU, intensive care unit; CRRT, continuous renal replacement therapy; AKI, acute kidney injury. Table 2. Relationship between ACEI/ARB use and mortality 30-day mortality 90-day mortality HRs of ACEI/ARBs use 95%CI P HRs of ACEI/ARBs use 95%CI P Model 1 0.34 0.3–0.37 <0.001 0.34 0.31–0.38 <0.001 Model 2 0.31 0.28–0.34 <0.001 0.32 0.29–0.35 <0.001 Model 3 0.32 0.29–0.35 <0.001 0.33 0.3–0.36 <0.001 Model 4 0.35 0.32–0.39 <0.001 0.36 0.33–0.4 <0.001 Model 5 0.35 0.31–0.38 <0.001 0.36 0.33–0.4 <0.001 PSM 0.35 0.32–0.4 <0.001 0.36 0.33–0.41 <0.001 HR, hazard ratio; ACEIs, angiotensin-converting enzyme inhibitors; ARBs, angiotensin II receptor blockers; CI, confidence interval; PSM, propensity-score matching. Model 1: Not adjusted. Model 2: Age, sex, BMI. Model 3 : Model 2 and race, WBC, HB, PLT, BUN, Cr, glucose, PT, APPT, PO 2 , lactate. Model 4 : Model 3 and heart rate, MAP, respiration rate, temperature, SpO 2 . Model 5 : Model 4 and myocardial infarct, congestive heart failure, cerebrovascular disease, chronic pulmonary disease, renal disease, severe liver disease, diabetes, Charlson Comorbidity Index, SOFA, ICU stay, CRRT, vasopressors, mechanical ventilation. Table 3. ACEI/ARB use and stay in the ICU (days) Model 1 Model 2 PSM Variable n. total β (95% CI) P β (95% CI) P β (95% CI) P No ACEIs/ARBs 13,374 0 (Ref) 0(Ref) 0(Ref) ACEIs/ARBs 9,409 −6.96 (−11.04 to −2.64) 0.001 0.48 (−3.6 to 4.32) 0.859 0.05 (−0.14 to 0.23) 0.625 ACEIs, angiotensin-converting enzyme inhibitors; ARBs, angiotensin II receptor blockers; CI, confidence interval; PSM, propensity-score matching. Model 1: Not adjusted. Model 2: Age, sex, BMI, race, WBC, HB, PLT, BUN, Cr, glucose, PT, APPT, PO 2 , lactate, heart rate, MAP, respiration rate, temperature, SpO 2 , myocardial infarct, congestive heart failure, cerebrovascular disease, chronic pulmonary disease, renal disease, severe liver disease, diabetes, Charlson Comorbidity Index, SOFA, CRRT, vasopressors, mechanical ventilation. Additional Declarations No competing interests reported. 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2","display":"","copyAsset":false,"role":"figure","size":57805,"visible":true,"origin":"","legend":"\u003cp\u003eKaplan–Meier survival curves for sepsis patients at day 90 and categorized by use of angiotensin-converting enzyme inhibitors (ACEIs) and angiotensin II receptor blockers (ARBs).\u003c/p\u003e","description":"","filename":"floatimage2.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8137597/v1/93d88fe42d5dc400b100fda5.jpeg"},{"id":97895240,"identity":"9af2d698-c744-4d16-aef2-a1e999838f8f","added_by":"auto","created_at":"2025-12-10 15:33:51","extension":"jpeg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":76476,"visible":true,"origin":"","legend":"\u003cp\u003eAssociation between ACEIs/ARBs use and 90-day mortality according to baseline 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Sepsis is a multifaceted condition instigated by various infectious agents and perpetuated by unregulated activation and dysfunction of diverse immune and inflammatory cells and mediators. In conjunction with endocrine dysregulation, sepsis can also affect the renin\u0026ndash;angiotensin\u0026ndash;aldosterone system (RAAS)(\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). Despite recent advances in medicine, the mortality rate associated with sepsis remains high.\u003c/p\u003e\u003cp\u003eThe principal effector of the RAAS, angiotensin II, is recognized as a significant inflammatory factor associated with organ failure and mortality(\u003cspan additionalcitationids=\"CR6\" citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e). Angiotensin II induces upregulation of tissue factor expression, a pivotal contributor to thrombosis and consequent microvascular ischemia in sepsis, concomitant with proinflammatory cytokines such as tumor necrosis factor-alpha and interleukin-1(\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e). In animal models of sepsis, interventions aimed at modulating the RAAS have been associated with decreased levels of proinflammatory cytokines, improved cardiovascular function, and elevated survival rates(\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e). Therefore, it has been hypothesized that RAAS antagonists could ameliorate organ failure and reduce mortality rates, particularly when promptly administered at the onset of sepsis(\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e). The RAAS plays a pivotal role in maintaining normal systemic function. Previous studies have demonstrated noteworthy alterations in RAAS dynamics during sepsis(\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e). Thus, given the pivotal role of the RAAS in the pathophysiology of sepsis, is the use of ACEIs or ARBs protective in patients with sepsis?\u003c/p\u003e\u003cp\u003eWhile some studies have suggested that the administration of ACEIs/ARBs before illness is linked with reduced mortality in patients with sepsis(\u003cspan additionalcitationids=\"CR17 CR18 CR19 CR20 CR21 CR22\" citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e), many studies have shown the opposite(\u003cspan additionalcitationids=\"CR25 CR26\" citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e), so further investigation is required. Building upon existing data, we postulated that ACEIs/ARBs may aid in decreasing sepsis-related mortality. Consequently, we conducted a novel retrospective investigation using the Medical Information Mart for Intensive Care (MIMIC-IV) dataset, spanning from 2008 to 2019. The primary objective of this study was to explore the potential association between pre - ICU use of ACEI/ARB and mortality rates in patients with sepsis.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003ePatients diagnosed with sepsis, either with or without previous exposure to ACEIs/ARBs prior to ICU admission, were enrolled in the study using data from the Medical Information Mart for Intensive Care (MIMIC)-IV (version 2.2), a longitudinal database derived from a single center in the USA and comprising records from 2008 to 2019(28). Yi Yu (one of the authors) obtained authorization to access the database under certificate ID 6477678. This study adhered to the Guidelines for Strengthening the Reporting of Observational Studies in Epidemiology to ensure proper reporting standards(29).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study involving human participants and human data/material was conducted in strict compliance with the ethical standards of the 1964 Helsinki Declaration and its later amendments or comparable ethical standards. For studies involving human participants, these were reviewed and approved by the Institutional Review Boards (IRBs) of both the Massachusetts Institute of Technology and Beth Israel Deaconess Medical Center. Written informed consent was obtained from all participants or their legally\u0026nbsp;authorized representatives.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStudy population and data extraction\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study recruited patients diagnosed with sepsis based on their discharge summaries. The diagnosis of sepsis followed the Sepsis 3.0 criteria, which delineate sepsis as a severe condition marked by organ dysfunction stemming from an uncontrolled response to infection. Clinically, organ dysfunction was determined by an increase in the Sequential (Sepsis-related) Organ Failure Assessment (SOFA) score of ≥2 points(30, 31). The study exclusively included patients aged ≥18 years. In cases where a single patient had multiple ICU admissions, only the initial admission was considered for analysis. Patients who stayed in the ICU \u0026lt;24 h were excluded. Data on patient demographics, vital signs, laboratory findings, underlying conditions, clinical severity scores, and other admission details were collected for analysis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eACEI/ARB use\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe utilization of ACEIs/ARBs before ICU admission was ascertained based on the existence of prescriptions for these medications within the MIMIC - IV database. ACEIs included medications such as Benazepril, Captopril, Enalapril, Fosinopril, Lisinopril, Quinapril, and Moexipril, among others. ARBs included drugs such as Losartan, Valsartan, Irbesartan, Olmesartan, and Candesartan, among others. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCovariates\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eRisk factors for mortality associated with sepsis were documented(32-34). The covariates included in the analysis were age, sex, body mass index (BMI), respiratory rate, temperature, pulse oxygen saturation (SpO\u003csub\u003e2\u003c/sub\u003e), white blood cell (WBC) count, hemoglobin level, hematocrit, platelet count, and glucose level. The study gathered data on various health indicators, including SOFA score, and comorbid conditions such as cardiovascular disease, kidney disease, liver disease, malignancy, neurological disease, and chronic pulmonary disease. Additionally, the researchers extracted demographic information related to race.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePatient outcomes\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThis study mainly aimed to examine the 30 - and 90 - day mortality rates of septic patients with or without pre - ICU ACEIs/ARBs treatment. Secondary endpoints included the duration of ICU admission, the occurrence of acute kidney injury (AKI) events, the need for renal replacement therapy (RRT) or mechanical ventilation (MV), and use of vasopressors.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatistical analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eBaseline characteristics of patients in different groups\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe baseline characteristics of patients were categorized into distinct groups. Categorical data are expressed as frequencies (percentages), while continuous data are reported as the mean ± standard deviation, or median (interquartile range), as appropriate. Statistical analyses, including analysis of variance or rank sum testing, were employed to evaluate differences in continuous variables. Chi-squared or Fisher’s exact tests were used to compare the characteristics of the study population across different outcome groups.\u003c/p\u003e\n\u003cp\u003eMissing data were imputed using the median value, because 5% of vital signs and laboratory parameters were missing. Because of the low percentage of missing data (ranging from 0.5% to 8%) for BMI, no imputation method was employed. We evaluated survival outcomes by constructing survival curves using the Kaplan–Meier methodology and conducting log-rank analysis. The association between ACEI/ARB use and mortality was assessed through multivariate Cox regression analysis. The adjusted Cox model was used to control for various covariates in the analysis. A total of five models were used for the regression analysis. Additional analyses included subgroup analyses and assessments of interactions, adjusting for relevant covariates. Multicollinearity was analyzed by assessing the variance inflation factor (VIF) among involved variables. Multicollinearity was considered to exist if VIF \u0026gt;2. Linear regression analyses were used to investigate the\u0026nbsp;association between ACEI/ARB use and the length of ICU stay, ventilation time, and vasopressor duration.\u0026nbsp;To analyze secondary outcomes, two statistical models were employed: unadjusted and fully adjusted.\u0026nbsp;To enhance the robustness of the analysis, propensity score matching (PSM) was conducted using a 1:1 nearest neighbor matching algorithm with a caliper width of 0.1.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAll statistical analyses were performed using STATA software (version 17.0) in conjunction with R packages (http://www.R-project.org, The R Foundation) and Free Statistics software version 1.8(35). Statistical significance was defined as p \u0026lt; 0.05 with a two-tailed test.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003eParticipants\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA total of 33,177 patients met the criteria for sepsis. After excluding repeated ICU admissions, patients under the age of 18, and those with an ICU stay of \u0026lt;24 h, the final cohort comprised 22,783 patients. The selection process for study participants is illustrated in \u003cstrong\u003eFigure 1\u003c/strong\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eBaseline characteristics\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study included 22,783 patients, with mean age 65.0 ± 16.1 years, of whom 58.1% were male. \u003cstrong\u003eTable 1\u003c/strong\u003e shows the baseline characteristics of the patient cohort. A comparative analysis of the two datasets revealed several disparities: the cohort not using ACEIs/ARBs tended to be younger, included a higher proportion of females, exhibited higher SOFA scores, had a lower Charlson comorbidity index, experienced significantly elevated 30- and 90-day mortality rates, faced an increased risk of AKI and continuous renal replacement therapy (CRRT), and showed higher rates of ventilation use.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eThe relationship between use of ACEIs/ARBs and mortality among patients with sepsis\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSurvival analyses using the Kaplan–Meier method revealed a significant decrease in mortality at 90 days among patients who used ACEIs/ARBs compared with those who did not (log-rank test: p \u0026lt; 0.0001) (\u003cstrong\u003eFigure 2\u003c/strong\u003e). In the univariate analysis of mortality risk, the use of ACEIs/ARBs was significantly associated with a lower mortality rate compared with non-use of ACEIs/ARBs, with a hazard ratio (HR) of 0.34 and a 95% confidence interval (CI) of 0.3–0.37 for 30-day mortality (p \u0026lt; 0.001), and a HR of 0.34 and a 95% CI of 0.31–0.38 for 90-day mortality (p \u0026lt; 0.001) (\u003cstrong\u003eTable 2\u003c/strong\u003e).\u003c/p\u003e\n\u003cp\u003eSubsequently, in the comprehensive multivariate Cox regression analysis (\u003cstrong\u003eTable 2\u003c/strong\u003e), we consistently observed that the HRs for ACEI/ARB use remained significant across all models (with HRs ranging from 0.31 to 0.36, all with p-values \u0026lt; 0.001). After adjusting for all covariates listed in Table 2, a 65% reduction in the risk of 30-day mortality was evident among patients using ACEIs/ARBs (HR = 0.35, 95% CI: 0.31–0.38, p \u0026lt; 0.001, model 5). Similarly, a 64% decrease in the risk of 90-day mortality was observed in ACEI/ARB users (HR = 0.36, 95% CI: 0.33–0.40, p \u0026lt; 0.001, model 5).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRelationship between\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eACEI/ARB\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;use and other outcomes\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWhen considering all the covariates listed in \u003cstrong\u003eTable 3\u003c/strong\u003e, it was determined that the use of ACEIs/ARBs did not significantly impact the length of ICU stay (β = 0.48, 95% CI = −3.6 to 4.32). However, the use of ACEIs/ARBs did show a significant effect on the odds of AKI on the 7\u003csup\u003eth\u003c/sup\u003e day (OR = 1.09, 95% CI = 1.01–1.17) and on the risk of requiring vasoactive drugs (OR = 1.11, 95% CI = 1.04–1.19). In addition, it was associated with a decreased likelihood of requiring CRRT (OR = 0.77, 95% CI = 0.66–0.9) and a reduced need for ventilation (OR = 0.89, 95% CI = 0.83–0.96) (\u003cstrong\u003eTable S1\u003c/strong\u003e). Furthermore, the use of ACEIs/ARBs was correlated with a shorter ventilation duration (β = −2.53, 95% CI = −4.12 to −0.93) (\u003cstrong\u003eTable S2\u003c/strong\u003e) and linked to a shorter duration of vasoactive drug use (β = −3.2, 95% CI = −5.22 to −1.18) (\u003cstrong\u003eTable S1\u003c/strong\u003e). PSM further enhanced the robustness of these results.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSubgroup analysis and sensitivity analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFollowing PSM, the two groups were comprised of 7,720 well-matched pairs, with no significant differences observed in key indicators between the groups. Notably, among the 7,720 pairs in the propensity-matched cohort, patients receiving ACEIs/ARBs exhibited a significantly lower 30-day mortality risk [1,140 (14.8%) vs. 425 (5.5%), p \u0026lt; 0.001], as well as a lower 90-day mortality risk [1,208 (15.6%) vs. 466 (6%), p \u0026lt; 0.001] (\u003cstrong\u003eTable S2\u003c/strong\u003e). In the multivariate Cox regression model, accounting for all covariates, the HR for 30-day mortality was 0.35 (95% CI: 0.32–0.4, p \u0026lt; 0.001), and the HR for 90-day mortality was 0.36 (95% CI: 0.33–0.4, p \u0026lt; 0.001) (\u003cstrong\u003eTable 2\u003c/strong\u003e). In particular, subgroup analyses indicated that the protective effect of ACEIs/ARBs was more pronounced among individuals aged \u0026lt;60 years, with a BMI ≥25, no renal disease, SOFA score ≥5, and lactate level ≥4, with no other significant interactions in the subgroups. Comparable trends were observed for 90-day mortality (\u003cstrong\u003eFigure 3\u003c/strong\u003e) and 30-day mortality (\u003cstrong\u003eFigure S1\u003c/strong\u003e).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe pre - ICU administration of ACEIs/ARBs to patients suffering from sepsis might be correlated with reduced mortality rates. Studies have shown that ACEIs and ARBs can downregulate the systemic inflammatory response(36, 37). Several studies have highlighted potential benefits in terms of mortality and morbidity for patients with sepsis(20, 22, 27, 38, 39). In a recent large cohort study involving \u0026gt;50,000 hospitalized patients with sepsis, prior use of ACEIs was linked with reduced 30-day and 90-day mortality compared with non-users, irrespective of gender, age, underlying comorbidities, and sources of infection in a propensity-matched cohort(20). A 2019 study examining the effects of preadmission ACEI and ARB use found a reduction in overall hospital mortality from sepsis (OR 0.93, 95% CI 0.88–0.98, p = 0.0085; and OR 0.85, 95% CI 0.81–0.90, p \u0026lt; 0.0001), respectively(21). These conclusions align with our findings.\u003c/p\u003e\n\u003cp\u003eThere is conflicting evidence regarding the efficacy of ACEIs/ARBs administration in reduction of the risk of sepsis-related death and improvement of the prognosis. A nested case-control study involving hypertensive adults in the United Kingdom revealed that the use of ACEIs was linked with an elevated risk of sepsis and 30-day mortality(24). In 2017, a prospective observational study demonstrated no significant association between prior use of ACEIs/ARBs and 30-day mortality among patients with sepsis(25). Pre-exposure to RASS inhibition did not confer a significant improvement in the prognosis of patients with septic shock(26, 27). Further rigorous clinical investigations are essential to comprehensively assess the preventive and therapeutic effectiveness of ACEIs/ARBs in managing sepsis.\u003c/p\u003e\n\u003cp\u003eThe mechanism by which ACEIs/ARBs are linked with a reduced risk of mortality in patients with sepsis remains unclear. One suggested protective mechanism underlying this associated decreased mortality is the anti-inflammatory effect of increased levels of angiotensin-converting enzyme (ACE) 2(40), as demonstrated in a murine model of acute lung injury. ACE2-knockout mice exhibited more severe lesions following pulmonary insult compared with their wild-type littermates(41, 42). In addition to the pulmonary protective effects of ACEIs, the impact on systemic hemodynamics and renal function must also be considered. Further research is necessary to understand the underlying mechanisms that could elucidate our findings, particularly with human data.\u003c/p\u003e\n\u003cp\u003eIn ICU patients, there is a significant association between the severity of AKI and mortality rates, especially in individuals with septic shock(43). The impact of prior use of ACEIs/ARBs on the occurrence of AKI among this patient cohort is debatable. A similar study indicated a significant association between ACEIs/ARBs and a higher stage of sepsis-related kidney injury during hospitalization, coupled with an increased incidence of stage 3 AKI within the first week in the ICU(27). This observation can potentially be explained by the more pronounced reduction in intraglomerular pressure in patients with a history of chronic RASS inhibition compared with those without such inhibition. In sepsis, the decreased renal blood flow can lead to a decline in filtration fraction, resulting in elevated serum creatinine levels and decreased urine output. Our investigation supports these findings, revealing a 9% higher likelihood of AKI development and an 11% higher likelihood of vasopressor requirement among users of ACEIs/ARBs compared with non-users. However, the administration of ACEIs/ARBs was associated with a reduced need for CRRT and a shorter duration of vasoactive drug usage.\u003c/p\u003e\n\u003cp\u003eA recent\u0026nbsp;\u003cem\u003epost-hoc\u003c/em\u003e analysis by Demiselle \u003cem\u003eet al\u003c/em\u003e. indicated that patients with prior RASS inhibition demonstrated a reduced risk of AKI onset during their ICU admission and may benefit from improved mean arterial pressure(26). This pattern was primarily observed in individuals using ARBs. Angiotensin II triggers vasoconstriction in the efferent arteriole; therefore, by blocking type 1 angiotensin II receptors, ARBs increase ACE2 levels, which counteract the effects of angiotensin II. ACE2 has been demonstrated to have protective and anti-inflammatory effects on the kidneys by enhancing nitric oxide production, thereby inducing vasodilation and enhancing renal blood flow(40). As a result, the preadministration of ARBs may elevate ACE2 levels, inducing vasodilation in renal arteries and reducing the incidence of AKI in patients with sepsis or septic shock. A noteworthy observation is the lack of disparity in the need for CRRT between the two groups, which remains perplexing.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStrengths and limitations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOur study has four main strengths. First, we used a comprehensive and publicly available database, ensuring the reliability and completeness of our data. Second, while the impact of ACEIs/ARBs on sepsis has been explored extensively, conclusive findings for patients with sepsis remain elusive. Our results show that using ACEIs/ARBs is linked to a lower mortality risk in sepsis patients. Third, we performed multiple sensitivity analyses to validate our results. (1) Cox regression analyses were adjusted using multiple models to address confounding effects, which remained consistent even after full adjustments. (2) PSM analysis was also conducted, yielding consistent outcomes. This rigorous analytical approach enhances the credibility and internal validity of our findings. Lastly, given the extensive use of ACEIs/ARBs for cardiovascular conditions, our results have broader implications beyond the population with sepsis.\u003c/p\u003e\n\u003cp\u003eThe limitations of our study align with those commonly encountered in observational research. First, our analysis was impeded by a substantial amount of missing data, which prevented the generation of statistics regarding the effects of ACEI/ARB levels on mortality. Consequently, definitively establishing the association between RASS and sepsis was not possible, leaving the optimal RASS value in sepsis unresolved. Second, an inherent constraint stems from the retrospective nature of our investigation. Unaccounted for potential confounding variables may exist, and our dataset lacks additional markers of inflammation beyond WBC counts. Third, caution is warranted when generalizing the findings of our study, as it was confined to a single nation (the USA) and a specific ICU setting. However, our study benefited from a substantial and fairly representative sample size. Subsequent multicenter prospective studies should be conducted to validate our results. Fourth, a multitude of factors influence the mortality risk associated with sepsis, such as educational attainment, smoking history, baseline cardiac function, hormone therapy, and other medical histories, which were not included in the MIMIC-IV database. Furthermore, our retrospective clinical investigation did not clarify the specific impact of ACEIs/ARBs on RASS in individual patients because of the lack of details regarding the duration and dosage of ACEI/ARB administration. Additional data could not be provided because of the non-randomized design of the study.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThe current evidence suggests that the pre - ICU administration of ACEIs/ARBs to patients with sepsis may be associated with lower mortality rates. However, additional randomized controlled trials are necessary to confirm the hypotheses posited in this article.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eACEIs\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eAngiotensin-converting enzyme inhibitors\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eARBs\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eAngiotensin II receptor blockers\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eMIMIC-IV\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eMedical Information Mart for Intensive Care-IV\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eICU\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eIntensive care unit\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eHR\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eHazard ratio\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eAKI\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eAcute kidney injury\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eOR\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eOdds Ratio\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003ePSM\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003ePropensity score matching\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eRAAS Renin\u0026ndash;angiotensin\u0026ndash;aldosterone system\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eSOFA\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eSequential Organ Failure Assessment\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eBMI\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eBody mass index\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eSpO\u003csub\u003e2\u003c/sub\u003e\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003ePulse oxygen saturation\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eWBC\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eWhite blood cell\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eRRT\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eRenal replacement therapy\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eMV\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eMechanical ventilation\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eVIF\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eVariance inflation factor\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003ePSM\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003ePropensity score matching\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eCRRT\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eContinuous renal replacement therapy\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFor studies involving human participants, these were reviewed and approved by the Institutional Review Boards (IRBs) of both the Massachusetts Institute of Technology and Beth Israel Deaconess Medical Center. Written informed consent was obtained from all participants or their legally\u0026nbsp;authorized representatives.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors of the manuscript consent to its publication in BMC Cardiovascular Disorders.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data underlying this study\u0026nbsp;will be shared by the authors upon reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interests\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no conflicting financial interests relevant to this article.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors' contributions\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eZhihu Zhou conducted data analysis and wrote the manuscript. Zhe Li conducted data analysis and modified the manuscript. Qihai Wan conducted data collection. Yi Yu conducted data collection and data interpretation. Zhihu Zhou designed the study and reviewed the manuscript. All authors contributed to the article and approved the submitted version.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe thank the Free Statistics team for providing technical assistance and valuable tools for data analysis and visualization. We are also grateful to all members of the Clinical Scientists team for their support and encouragement.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAngus DC, van der Poll T. Severe Sepsis and Septic Shock. 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Epub 2013/11/10.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003e\u003cstrong\u003eTable 1.\u003c/strong\u003e Characteristics of participants at baseline\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"589\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 141px;\"\u003e\n \u003cp\u003eVariable\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003eTotal\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(n = 22,783)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 148px;\"\u003e\n \u003cp\u003eNo use of ACEIs/ARBs\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(n = 13,374)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 125px;\"\u003e\n \u003cp\u003eACEI/ARB use\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;(n = 9,409)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;P\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 141px;\"\u003e\n \u003cp\u003eAge, years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e65.0 \u0026plusmn; 16.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 148px;\"\u003e\n \u003cp\u003e62.8 \u0026plusmn; 17.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 125px;\"\u003e\n \u003cp\u003e68.2 \u0026plusmn; 13.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 141px;\"\u003e\n \u003cp\u003eSex, male, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e13,229 (58.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 148px;\"\u003e\n \u003cp\u003e7,657 (57.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 125px;\"\u003e\n \u003cp\u003e5,572 (59.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 141px;\"\u003e\n \u003cp\u003eBMI, kg/m\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e28.6 \u0026plusmn; 6.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 148px;\"\u003e\n \u003cp\u003e28.0 \u0026plusmn; 6.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 125px;\"\u003e\n \u003cp\u003e29.4 \u0026plusmn; 6.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 141px;\"\u003e\n \u003cp\u003eRace, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 148px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 125px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 141px;\"\u003e\n \u003cp\u003eWhite\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e15,421 (67.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 148px;\"\u003e\n \u003cp\u003e8,900 (66.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 125px;\"\u003e\n \u003cp\u003e6,521 (69.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 141px;\"\u003e\n \u003cp\u003eBlack\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e1,914 ( 8.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 148px;\"\u003e\n \u003cp\u003e857 (6.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 125px;\"\u003e\n \u003cp\u003e1,057 (11.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 141px;\"\u003e\n \u003cp\u003eOther\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e5,448 (23.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 148px;\"\u003e\n \u003cp\u003e3,617 (27)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 125px;\"\u003e\n \u003cp\u003e1,831 (19.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 141px;\"\u003e\n \u003cp\u003eWBC (\u0026times;10\u003csup\u003e9\u003c/sup\u003e )\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e13.1 \u0026plusmn; 9.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 148px;\"\u003e\n \u003cp\u003e13.4 \u0026plusmn; 9.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 125px;\"\u003e\n \u003cp\u003e12.7 \u0026plusmn; 8.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 141px;\"\u003e\n \u003cp\u003eHB (g/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e10.6 \u0026plusmn; 2.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 148px;\"\u003e\n \u003cp\u003e10.6 \u0026plusmn; 2.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 125px;\"\u003e\n \u003cp\u003e10.5 \u0026plusmn; 2.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e0.778\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 141px;\"\u003e\n \u003cp\u003ePLT (\u0026times;10\u003csup\u003e9\u003c/sup\u003e )\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e204.3 \u0026plusmn; 111.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 148px;\"\u003e\n \u003cp\u003e199.5 \u0026plusmn; 114.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 125px;\"\u003e\n \u003cp\u003e211.1 \u0026plusmn; 107.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 141px;\"\u003e\n \u003cp\u003eRespiration rate (bpm)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e19.6 \u0026plusmn; 4.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 148px;\"\u003e\n \u003cp\u003e19.8 \u0026plusmn; 4.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 125px;\"\u003e\n \u003cp\u003e19.4 \u0026plusmn; 3.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 141px;\"\u003e\n \u003cp\u003eTemperature (\u0026deg;C)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e36.9 \u0026plusmn; 0.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 148px;\"\u003e\n \u003cp\u003e36.9 \u0026plusmn; 0.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 125px;\"\u003e\n \u003cp\u003e36.8 \u0026plusmn; 0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 141px;\"\u003e\n \u003cp\u003eSpO\u003csub\u003e2\u003c/sub\u003e (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e97.0 \u0026plusmn; 2.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 148px;\"\u003e\n \u003cp\u003e96.9 \u0026plusmn; 2.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 125px;\"\u003e\n \u003cp\u003e97.0 \u0026plusmn; 2.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e0.009\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 141px;\"\u003e\n \u003cp\u003eHeart rate (bpm)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e86.7 \u0026plusmn; 16.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 148px;\"\u003e\n \u003cp\u003e88.2 \u0026plusmn; 16.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 125px;\"\u003e\n \u003cp\u003e84.5 \u0026plusmn; 15.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 141px;\"\u003e\n \u003cp\u003eMAP (mmHg)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e76.8 \u0026plusmn; 10.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 148px;\"\u003e\n \u003cp\u003e76.6 \u0026plusmn; 10.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 125px;\"\u003e\n \u003cp\u003e77.1 \u0026plusmn; 10.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 141px;\"\u003e\n \u003cp\u003ePT (s)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e16.5 \u0026plusmn; 8.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 148px;\"\u003e\n \u003cp\u003e16.5 \u0026plusmn; 8.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 125px;\"\u003e\n \u003cp\u003e16.3 \u0026plusmn; 8.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e0.049\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 141px;\"\u003e\n \u003cp\u003eAPPT (s)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e37.6 \u0026plusmn; 17.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 148px;\"\u003e\n \u003cp\u003e37.3 \u0026plusmn; 17.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 125px;\"\u003e\n \u003cp\u003e37.9 \u0026plusmn; 18.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e0.015\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 141px;\"\u003e\n \u003cp\u003ePaO\u003csub\u003e2\u003c/sub\u003e (mmHg)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e160.5 \u0026plusmn; 85.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 148px;\"\u003e\n \u003cp\u003e157.3 \u0026plusmn; 84.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 125px;\"\u003e\n \u003cp\u003e165.0 \u0026plusmn; 87.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 141px;\"\u003e\n \u003cp\u003eLactate (mmol/L)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e1.9 (1.5, 2.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 148px;\"\u003e\n \u003cp\u003e1.9 (1.5, 2.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 125px;\"\u003e\n \u003cp\u003e1.9 (1.4, 2.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 141px;\"\u003e\n \u003cp\u003eBUN (mg/dL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e20.5 (14.0, 34.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 148px;\"\u003e\n \u003cp\u003e19.0 (13.0, 32.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 125px;\"\u003e\n \u003cp\u003e22.0 (15.5, 35.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 141px;\"\u003e\n \u003cp\u003eCr (mg/dL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e1.0 (0.8, 1.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 148px;\"\u003e\n \u003cp\u003e1.0 (0.7, 1.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 125px;\"\u003e\n \u003cp\u003e1.1 (0.8, 1.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 141px;\"\u003e\n \u003cp\u003eGlucose (mmol/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e145.2 \u0026plusmn; 62.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 148px;\"\u003e\n \u003cp\u003e141.3 \u0026plusmn; 58.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 125px;\"\u003e\n \u003cp\u003e150.6 \u0026plusmn; 68.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 141px;\"\u003e\n \u003cp\u003eCharlson Comorbidity Index\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e5.7 \u0026plusmn; 2.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 148px;\"\u003e\n \u003cp\u003e5.3 \u0026plusmn; 3.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 125px;\"\u003e\n \u003cp\u003e6.2 \u0026plusmn; 2.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 141px;\"\u003e\n \u003cp\u003eSOFA score\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e5.9 \u0026plusmn; 3.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 148px;\"\u003e\n \u003cp\u003e6.1 \u0026plusmn; 3.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 125px;\"\u003e\n \u003cp\u003e5.7 \u0026plusmn; 3.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 141px;\"\u003e\n \u003cp\u003eMyocardial infarct, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e3,573 (15.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 148px;\"\u003e\n \u003cp\u003e1,562 (11.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 125px;\"\u003e\n \u003cp\u003e2,011 (21.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 141px;\"\u003e\n \u003cp\u003eCongestive heart failure, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e6,187 (27.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 148px;\"\u003e\n \u003cp\u003e2,644 (19.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 125px;\"\u003e\n \u003cp\u003e3,543 (37.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 141px;\"\u003e\n \u003cp\u003eCerebrovascular disease, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e3,105 (13.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 148px;\"\u003e\n \u003cp\u003e1,637 (12.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 125px;\"\u003e\n \u003cp\u003e1,468 (15.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 141px;\"\u003e\n \u003cp\u003eSevere liver disease, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e1,274 ( 5.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 148px;\"\u003e\n \u003cp\u003e1090 (8.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 125px;\"\u003e\n \u003cp\u003e184 (2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 141px;\"\u003e\n \u003cp\u003eDiabetes, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 148px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 125px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 141px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e15,911 (69.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 148px;\"\u003e\n \u003cp\u003e10,478 (78.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 125px;\"\u003e\n \u003cp\u003e5,433 (57.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 141px;\"\u003e\n \u003cp\u003ecomplications\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e5,366 (23.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 148px;\"\u003e\n \u003cp\u003e2,315 (17.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 125px;\"\u003e\n \u003cp\u003e3,051 (32.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 141px;\"\u003e\n \u003cp\u003eWith complications\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e1,506 ( 6.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 148px;\"\u003e\n \u003cp\u003e581 (4.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 125px;\"\u003e\n \u003cp\u003e925 (9.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 141px;\"\u003e\n \u003cp\u003eICU stay, days\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e3.0 (1.8, 6.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 148px;\"\u003e\n \u003cp\u003e3.0 (1.8, 6.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 125px;\"\u003e\n \u003cp\u003e3.0 (1.8, 5.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 141px;\"\u003e\n \u003cp\u003e30-day mortality, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e2,576 (11.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 148px;\"\u003e\n \u003cp\u003e2,059 (15.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 125px;\"\u003e\n \u003cp\u003e517 (5.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 141px;\"\u003e\n \u003cp\u003e90-day mortality, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e2,756 (12.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 148px;\"\u003e\n \u003cp\u003e2,192 (16.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 125px;\"\u003e\n \u003cp\u003e564 (6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 141px;\"\u003e\n \u003cp\u003eCRRT, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e1,375 ( 6.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 148px;\"\u003e\n \u003cp\u003e943 (7.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 125px;\"\u003e\n \u003cp\u003e432 (4.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 141px;\"\u003e\n \u003cp\u003eVasopressors, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e11,297 (49.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 148px;\"\u003e\n \u003cp\u003e6,581 (49.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 125px;\"\u003e\n \u003cp\u003e4,716 (50.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e0.174\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 141px;\"\u003e\n \u003cp\u003eVentilation, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e11,496 (50.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 148px;\"\u003e\n \u003cp\u003e6,917 (51.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 125px;\"\u003e\n \u003cp\u003e4,579 (48.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 141px;\"\u003e\n \u003cp\u003eAKI in 7 days, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e16,905 (74.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 148px;\"\u003e\n \u003cp\u003e9,633 (72)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 125px;\"\u003e\n \u003cp\u003e7,272 (77.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eFor each variable, mean \u0026plusmn; standard deviation, median (interquartile range), or number (percentage) was reported (as appropriate).\u003c/p\u003e\n\u003cp\u003eACEIs, angiotensin-converting enzyme inhibitors; ARBs, angiotensin II receptor blockers; BMI, body mass index; WBC, white blood cells; HB, hemoglobin; PLT, platelets; SpO\u003csub\u003e2\u003c/sub\u003e, pulse oxygen saturation; MAP, mean arterial pressure; PT, prothrombin time; APTT, activated partial thromboplastin time; PaO\u003csub\u003e2\u003c/sub\u003e, arterial partial pressure of oxygen; BUN, blood urea nitrogen; Scr, serum creatinine; SOFA, Sequential Organ Failure Assessment; ICU, intensive care unit; CRRT, continuous renal replacement therapy; AKI, acute kidney injury.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2.\u003c/strong\u003e Relationship between ACEI/ARB use and mortality\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"695\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 276px;\"\u003e\n \u003cp\u003e30-day mortality\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 332px;\"\u003e\n \u003cp\u003e90-day mortality\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 130px;\"\u003e\n \u003cp\u003eHRs of ACEI/ARBs use\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 83px;\"\u003e\n \u003cp\u003e95%CI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003eP\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003eHRs of ACEI/ARBs use\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 87px;\"\u003e\n \u003cp\u003e95%CI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003eP\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eModel\u0026nbsp;1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 130px;\"\u003e\n \u003cp\u003e0.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 83px;\"\u003e\n \u003cp\u003e0.3\u0026ndash;0.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 138px;\"\u003e\n \u003cp\u003e0.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e0.31\u0026ndash;0.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eModel\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 130px;\"\u003e\n \u003cp\u003e0.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 83px;\"\u003e\n \u003cp\u003e0.28\u0026ndash;0.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 138px;\"\u003e\n \u003cp\u003e0.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e0.29\u0026ndash;0.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eModel\u0026nbsp;3\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 130px;\"\u003e\n \u003cp\u003e0.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003e0.29\u0026ndash;0.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 138px;\"\u003e\n \u003cp\u003e0.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e0.3\u0026ndash;0.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eModel\u0026nbsp;4\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 130px;\"\u003e\n \u003cp\u003e0.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003e0.32\u0026ndash;0.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 138px;\"\u003e\n \u003cp\u003e0.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e0.33\u0026ndash;0.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eModel\u0026nbsp;5\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 130px;\"\u003e\n \u003cp\u003e0.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003e0.31\u0026ndash;0.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 138px;\"\u003e\n \u003cp\u003e0.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e0.33\u0026ndash;0.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePSM\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 130px;\"\u003e\n \u003cp\u003e0.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003e0.32\u0026ndash;0.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 138px;\"\u003e\n \u003cp\u003e0.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e0.33\u0026ndash;0.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eHR, hazard ratio; ACEIs, angiotensin-converting enzyme inhibitors; ARBs, angiotensin II receptor blockers; CI, confidence interval; PSM, propensity-score matching.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eModel 1:\u0026nbsp;\u003c/strong\u003eNot adjusted.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eModel 2:\u0026nbsp;\u003c/strong\u003eAge, sex, BMI.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eModel 3\u003c/strong\u003e: \u003cstrong\u003eModel 2\u003c/strong\u003e and race, WBC, HB, PLT, BUN, Cr, glucose, PT, APPT, PO\u003csub\u003e2\u003c/sub\u003e, lactate.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eModel 4\u003c/strong\u003e: \u003cstrong\u003eModel 3\u003c/strong\u003e and heart rate, MAP, respiration rate, temperature, SpO\u003csub\u003e2\u003c/sub\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eModel 5\u003c/strong\u003e: \u003cstrong\u003eModel 4\u003c/strong\u003e and myocardial infarct, congestive heart failure, cerebrovascular disease, chronic pulmonary disease, renal disease, severe liver disease, diabetes, Charlson Comorbidity Index, SOFA, ICU stay, CRRT, vasopressors, mechanical ventilation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3.\u003c/strong\u003e ACEI/ARB use and stay in the ICU (days)\u003c/p\u003e\n\u003cdiv\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"858\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 120px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 173px;\"\u003e\n \u003cp\u003eModel 1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 162px;\"\u003e\n \u003cp\u003eModel 2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 156px;\"\u003e\n \u003cp\u003ePSM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 120px;\"\u003e\n \u003cp\u003eVariable\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003en. total\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 173px;\"\u003e\n \u003cp\u003e\u0026beta; (95% CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003eP\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 162px;\"\u003e\n \u003cp\u003e\u0026beta; (95% CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003eP\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 156px;\"\u003e\n \u003cp\u003e\u0026beta; (95% CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56px;\"\u003e\n \u003cp\u003eP\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 120px;\"\u003e\n \u003cp\u003eNo ACEIs/ARBs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e13,374\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 173px;\"\u003e\n \u003cp\u003e0 (Ref)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 162px;\"\u003e\n \u003cp\u003e0(Ref)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 156px;\"\u003e\n \u003cp\u003e0(Ref)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 120px;\"\u003e\n \u003cp\u003eACEIs/ARBs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e9,409\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 173px;\"\u003e\n \u003cp\u003e\u0026minus;6.96 (\u0026minus;11.04 to\u0026nbsp;\u0026minus;2.64)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 162px;\"\u003e\n \u003cp\u003e0.48 (\u0026minus;3.6 to 4.32)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e0.859\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 156px;\"\u003e\n \u003cp\u003e0.05 (\u0026minus;0.14 to 0.23)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56px;\"\u003e\n \u003cp\u003e0.625\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eACEIs, angiotensin-converting enzyme inhibitors; ARBs, angiotensin II receptor blockers; CI, confidence interval; PSM, propensity-score matching.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eModel 1:\u0026nbsp;\u003c/strong\u003eNot adjusted.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eModel 2:\u0026nbsp;\u003c/strong\u003eAge, sex, BMI, race, WBC, HB, PLT, BUN, Cr, glucose, PT, APPT, PO\u003csub\u003e2\u003c/sub\u003e, lactate, heart rate, MAP, respiration rate, temperature, SpO\u003csub\u003e2\u003c/sub\u003e, myocardial infarct, congestive heart failure, cerebrovascular disease, chronic pulmonary disease, renal disease, severe liver disease, diabetes, Charlson Comorbidity Index, SOFA, CRRT, vasopressors, mechanical ventilation.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-cardiovascular-disorders","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bcar","sideBox":"Learn more about [BMC Cardiovascular Disorders](http://bmccardiovascdisord.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bcar/default.aspx","title":"BMC Cardiovascular Disorders","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Angiotensin converting enzyme inhibitor, Angiotensin II, Sepsis, Mortality, Intensive Care Unit","lastPublishedDoi":"10.21203/rs.3.rs-8137597/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8137597/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground/Aims\u003c/h2\u003e\u003cp\u003e: Angiotensin-converting enzyme inhibitors (ACEIs) and angiotensin II receptor blockers (ARBs) possess anti-inflammatory properties. The purpose of this study was to find out what impact the use of ACEIs and ARBs before ICU admission has on the clinical conditions of patients with sepsis.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003ePatients diagnosed with sepsis were included in this study using data extracted from the Medical Information Mart for Intensive Care-IV (MIMIC-IV) database. The primary endpoints assessed were the 30- and 90-day mortality rates, along with the length of stay in the intensive care unit (ICU). Statistical analysis was conducted using multivariable Cox regression and linear regression models, while propensity score matching (PSM) was used to ensure the reliability and validity of the results.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eAmong the 22,783 patients hospitalized for sepsis. Multivariable Cox regression analysis revealed that the utilization of ACEIs/ARBs was significantly associated with a notable reduction in 90 - day mortality (hazard ratio (HR)\u0026thinsp;=\u0026thinsp;0.36, 95% confidence interval: 0.33\u0026ndash;0.4, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Regarding safety considerations, the use of ACEIs/ARBs was associated with an increased risk of acute kidney injury (AKI) (Odds Ratio (OR)\u0026thinsp;=\u0026thinsp;1.09, 95% CI: 1.01\u0026ndash;1.17, p\u0026thinsp;=\u0026thinsp;0.026) and a higher incidence of vasopressor drug use (OR\u0026thinsp;=\u0026thinsp;1.11, 95% CI: 1.04\u0026ndash;1.19, p\u0026thinsp;=\u0026thinsp;0.002). However, ACEIs/ARBs were linked with a reduced need for continuous renal replacement therapy (OR\u0026thinsp;=\u0026thinsp;0.77, 95% CI: 0.66\u0026ndash;0.9, p\u0026thinsp;=\u0026thinsp;0.001).\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e\u003cp\u003eThe pre - ICU administration of ACEIs/ARBs to patients with sepsis may be associated with lower mortality rates.\u003c/p\u003e","manuscriptTitle":"A Retrospective Cohort Study: Unveiling the Association between Pre - ICU Use of Angiotensin - converting Enzyme Inhibitors and Angiotensin II Receptor Blockers and Mortality in Septic Patients","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-12-09 08:47:33","doi":"10.21203/rs.3.rs-8137597/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvitedReview","content":"","date":"2026-02-09T21:59:08+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"326437160181522489988233301186559646046","date":"2026-01-29T13:21:21+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"145164784737136254307835400280359609182","date":"2026-01-27T21:40:15+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-12-05T09:06:22+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-12-05T08:46:34+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-11-25T10:46:24+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-11-24T14:35:03+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Cardiovascular Disorders","date":"2025-11-24T14:04:54+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-cardiovascular-disorders","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bcar","sideBox":"Learn more about [BMC Cardiovascular Disorders](http://bmccardiovascdisord.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bcar/default.aspx","title":"BMC Cardiovascular Disorders","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"f78fb3ce-2762-44c0-9297-0975ceffbc8e","owner":[],"postedDate":"December 9th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2025-12-09T08:47:34+00:00","versionOfRecord":[],"versionCreatedAt":"2025-12-09 08:47:33","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8137597","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8137597","identity":"rs-8137597","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}