Impact of Aspirin on Clinical Outcomes in Sepsis Patients with Atrial Fibrillation: An Analysis of the MIMIC-IV and eICU-CRD Databases

Impact of Aspirin on Clinical Outcomes in Sepsis Patients with Atrial Fibrillation: An Analysis of the MIMIC-IV and eICU-CRD Databases | Authorea try { document.documentElement.classList.add('js'); } catch (e) { } var _gaq = _gaq || []; _gaq.push(['_setAccount', 'G-8VDV14Y67G']); _gaq.push(['_trackPageview']); (function() { var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true; ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js'; var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s); })(); Skip to main content Preprints Collections Wiley Open Research IET Open Research Ecological Society of Japan All Collections About About Authorea FAQs Contact Us Quick Search anywhere Search for preprint articles, keywords, etc. Search Search ADVANCED SEARCH SCROLL This is a preprint and has not been peer reviewed. Data may be preliminary. 30 January 2026 V1 Latest version Share on Impact of Aspirin on Clinical Outcomes in Sepsis Patients with Atrial Fibrillation: An Analysis of the MIMIC-IV and eICU-CRD Databases Authors : Fangchao Chen , Yufeng Zhong , Dianyang Wang , Qiuyin Wei , Rui Su , Hongfei Ge , WenCai Wei , and Wei Wang [email protected] Authors Info & Affiliations https://doi.org/10.22541/au.176975650.07852835/v1 157 views 54 downloads Contents Abstract Abstract Introduction Materials and Methods Results Conclusion Supplementary Material Information & Authors Metrics & Citations View Options References Figures Tables Media Share Abstract Background :Sepsis features dysregulated inflammation, endothelial dysfunction, platelet activation, and immunothrombosis; concomitant Atrial Fibrillation(AF) may further intensify prothrombotic and proinflammatory signaling, thereby increasing thrombotic risk and mortality. Aspirin may provide benefit through platelet inhibition and modulation of inflammatory and immune pathways. However, evidence for aspirin use in sepsis patients with comorbid AF is limited, and its clinical value and risk-benefit profile remain unclear. Objective : To evaluate the association between aspirin treatment and prognosis in sepsis patients with AF, including in-hospital gastrointestinal bleeding (GIB). Methods :In MIMIC-IV, propensity score matching balanced baseline characteristics. Kaplan–Meier analyses compared 28-day and 1-year all-cause mortality between aspirin and non-aspirin groups, and multivariable Cox proportional hazards models assessed independent associations. Multivariable logistic regression evaluated in-hospital GIB. External validation was performed in eICU-CRD. Time-dependent Cox regression assessed temporal associations, with subgroup and stratified analyses by anticoagulant use, AF patterns, comorbidities, aspirin dose, duration, and initiation timing. Results :Aspirin use was associated with lower 28-day mortality (16.06% vs. 23.70%) and 1-year mortality (21.03% vs. 29.22%) (both P<0.001), with consistent Kaplan–Meier differences (P<0.001). Aspirin was independently associated with improved 28-day survival and was not independently associated with in-hospital GIB. Findings were validated in eICU-CRD. Time-dependent Cox models confirmed reduced mortality. Effects were significant in subgroups with AF detected during hospitalization (both P<0.05). Initiation after sepsis diagnosis or ICU admission were associated with reduced mortality (both P<0.001). Conclusion :Aspirin treatment is significantly associated with reduced all-cause mortality in sepsis patients with AF. Impact of Aspirin on Clinical Outcomes in Sepsis Patients with Atrial Fibrillation: An Analysis of the MIMIC-IV and eICU-CRD Databases Running Title: Aspirin Improves Outcomes in Sepsis with AF Fangchao Chen * 1, 2, 3 , Yufeng Zhong * 2 , Dianyang Wang 2 ，Qiuyin Wei 2 ,Rui Su 4 , Hongfei Ge 5 ,WenCai Wei 6 ,Wei Wang ※ 1, 3 1. Department of Emergency, the First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China. 2. Department of Emergency, Liuzhou Workers’ Hospital, the Fourth Affiliated Hospital of Guangxi Medical University, Liuzhou, Guangxi, China. 3. Guangxi University Key Laboratory of Emergency Medicine, the First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China 4. Department of Respiratory and Critical Care Medicine, Liuzhou Workers’ Hospital, the Fourth Affiliated Hospital of Guangxi Medical University, Liuzhou, Guangxi, China. 5. Department of Critical Care Medicine, Liuzhou Workers’ Hospital, the Fourth Affiliated Hospital of Guangxi Medical University, Liuzhou, Guangxi, China. 6.Department of Cardiology,Liuzhou Workers’ Hospital, the Fourth Affiliated Hospital of Guangxi Medical University, Liuzhou, Guangxi, China. * These authors contributed equally to this work. ※Corresponding author: Prof. Wei Wang, Department Director, the Emergency Department, the First Affiliated Hospital of Guangxi Medical University, No.6 Shuangyong Road, Qingxiu District, Nanning, Guangxi Zhuang Autonomous Region, People’s Republic of China, E-mail: [email protected] ; Abstract Background :Sepsis features dysregulated inflammation, endothelial dysfunction, platelet activation, and immunothrombosis; concomitant Atrial Fibrillation(AF) may further intensify prothrombotic and proinflammatory signaling, thereby increasing thrombotic risk and mortality. Aspirin may provide benefit through platelet inhibition and modulation of inflammatory and immune pathways. However, evidence for aspirin use in sepsis patients with comorbid AF is limited, and its clinical value and risk-benefit profile remain unclear. Objective : To evaluate the association between aspirin treatment and prognosis in sepsis patients with AF, including in-hospital gastrointestinal bleeding (GIB). Methods :In MIMIC-IV, propensity score matching balanced baseline characteristics. Kaplan–Meier analyses compared 28-day and 1-year all-cause mortality between aspirin and non-aspirin groups, and multivariable Cox proportional hazards models assessed independent associations. Multivariable logistic regression evaluated in-hospital GIB. External validation was performed in eICU-CRD. Time-dependent Cox regression assessed temporal associations, with subgroup and stratified analyses by anticoagulant use, AF patterns, comorbidities, aspirin dose, duration, and initiation timing. Results :Aspirin use was associated with lower 28-day mortality (16.06% vs. 23.70%) and 1-year mortality (21.03% vs. 29.22%) (both P<0.001), with consistent Kaplan–Meier differences (P<0.001). Aspirin was independently associated with improved 28-day survival and was not independently associated with in-hospital GIB. Findings were validated in eICU-CRD. Time-dependent Cox models confirmed reduced mortality. Effects were significant in subgroups with AF detected during hospitalization (both P<0.05). Initiation after sepsis diagnosis or ICU admission were associated with reduced mortality (both P<0.001). Conclusion :Aspirin treatment is significantly associated with reduced all-cause mortality in sepsis patients with AF. Keywords : Aspirin; Sepsis; Atrial Fibrillation; Clinical Outcomes; MIMIC-IV Introduction Sepsis is defined as a dysregulated host response to infection that leads to life-threatening organ dysfunction. Its pathophysiology involves a systemic inflammatory cascade, immune dysregulation, diffuse endothelial injury, and abnormal activation of the coagulation system. Despite advances in medical care, sepsis remains a major global cause of death and disability and is a leading contributor to mortality in intensive care units (ICUs), largely due to the development of multiple organ dysfunction syndrome (MODS)[1]. Cardiovascular complications are particularly common in sepsis and are strongly associated with poor prognosis[2]. Atrial Fibrillation(AF), the most prevalent clinical arrhythmia, may be triggered by cytokine storms, autonomic dysfunction, underlying structural heart disease, endotoxemia, and myocardial depression. AF can further compromise hemodynamic stability by reducing cardiac output, inducing blood pressure fluctuations, and impairing tissue perfusion, thereby aggravating organ dysfunction[3, 4]. Clinical evidence indicates that sepsis and AF constitute a high-risk pathological state; their synergistic effects increase thromboembolism and multi-organ injury, accelerate disease progression, and ultimately lead to markedly higher mortality[5–7]. Aspirin, a classic cyclooxygenase (COX) inhibitor, has anti-inflammatory and antioxidant properties in addition to its antiplatelet effects[8, 9]. Mechanistically, aspirin reduces prostaglandin and thromboxane synthesis and inhibits the nuclear factor-κB (NF-κB) signaling pathway[10], thereby downregulating pro-inflammatory cytokines such as tumor necrosis factor-α (TNF-α) and interleukin-1 (IL-1)[11], which may attenuate the systemic inflammatory response in sepsis. These pleiotropic mechanisms have motivated investigations of aspirin as a potential strategy to improve sepsis outcomes. However, clinical benefits remain controversial. Some studies suggest that antiplatelet therapy, whether initiated before or after sepsis onset, reduces mortality by 22%–66%[12–14], whereas others report no clear benefit[15, 16]. Nonetheless, evidence supports potential organ-protective effects of aspirin in specific sepsis phenotypes, including acute respiratory distress syndrome (ARDS)[17, 18], acute kidney injury (AKI)[19], and myocardial injury[20]. In sepsis complicated by AF, aspirin use raises additional clinical challenges[21, 22]. AF management typically involves risk stratification using CHADS₂, CHA₂DS₂-VASc, and HAS-BLED scores and decisions regarding warfarin or NOACs[23, 24]. Consequently, balancing antiplatelet and anticoagulant strategies—particularly the trade-off between efficacy and bleeding risk—becomes complex[25]. This complexity, together with the heterogeneity of sepsis and concerns about aspirin-related adverse events, has contributed to a lack of high-quality direct evidence regarding whether aspirin improves outcomes in sepsis patients with AF, including new-onset AF. Moreover, comparative evidence on aspirin alone versus combination therapy with traditional anticoagulants remains limited. Against this background, this study aimed to systematically evaluate the association between aspirin use and all-cause mortality in sepsis patients with AF, using multicenter databases for external validation. Through detailed subgroup analyses, we sought to clarify the role and apparent efficacy of aspirin across clinically relevant populations, including patients receiving warfarin, novel antiplatelet agents, those with valvular disease, and those with persistent or new-onset AF. Ultimately, this study aimed to better define aspirin’s role in this complex pathological context and to provide an evidence-based foundation for optimizing combination therapeutic strategies to improve clinical prognosis. Materials and Methods Data Sources and Ethical Review Data were obtained from the publicly available MIMIC-IV database (version 3.1, PhysioNet)[26]. This database has been approved by the Institutional Review Boards (IRB) of Beth Israel Deaconess Medical Center (BIDMC) and the Massachusetts Institute of Technology (MIT)[27]. External validation data were derived from the eICU Collaborative Research Database (eICU-CRD) (version 2.0)[28], which contains de-identified records from more than 200,000 ICU admissions across over 200 hospitals in the United States (2014–2015). The principal investigator completed the Collaborative Institutional Training Initiative (CITI) program (Certification No. 72379798) and signed the data use agreement to access both databases. Because this study was a retrospective analysis of de-identified data, the requirement for informed consent was waived by the IRB. Study Population Adult patients with sepsis and AF were identified in the MIMIC-IV and eICU-CRD databases. Inclusion criteria were: (1) age ≥18 years; (2) ICU admission meeting Sepsis-3 criteria (suspected or confirmed infection with an acute increase in Sequential Organ Failure Assessment [SOFA] score ≥2); (3) concomitant AF, encompassing prior, new-onset,paroxysmal, persistent, or permanent AF. Based on AF occurrence patterns during the ICU stay, patients were further categorized into three rhythm groups:①no AF throughout the ICU stay;②AF present at ICU admission;③new-onset AF developing after ICU admission. (4) availability of key study variables, including vital signs and laboratory values. For patients with multiple ICU admissions, only the first admission was included. Patients were categorized into an aspirin treatment group and a non-aspirin treatment group. Exclusion criteria were: (1) ICU length of stay <24 hours; and (2) missing data exceeding 20% of the total dataset in MIMIC-IV or 30% in eICU-CRD. Data Collection Baseline data included: (1) aspirin prescription information (use status, duration, cumulative dose, and timing relative to sepsis); (2) demographics (age, gender, ethnicity, weight); (3) severity scores at admission (SOFA, APACHE II); (4) comorbidities :hypertension(HTN), Valvular Heart Disease(VHD), Cerebrovascular Disease(CVA), Type 2 Diabetes Mellitus(T2DM), Chronic Kidney Disease(CKD), Cancer, Myocardial Infarction(MI), Ischemic Heart Disease(IHD),Acute Kidney Injury(AKI),Coronary Artery Disease(CAD), Hyperlipidemia(HL), Chronic Obstructive Pulmonary Disease(COPD), Heart Failure(HF); (5) initial vital signs (HR, RR, SBP, DBP, Temp, SpO₂); (6) initial laboratory measurements (WBC, Hb, PLT, anion gap, glucose, potassium, sodium, total calcium, pH, PaO₂, lactate, INR, PT, creatinine, BUN); and (7) initial interventions :warfarin, beta-blockers, NOACs, proton pump inhibitors (PPIs),H₂-receptor antagonists (H₂RAs),RRT, MV. The primary outcomes were 28-day and 365-day mortality. Secondary outcomes were ICU length of stay (LOS) and total hospital LOS. Data were extracted using SQL with PostgreSQL 15.0 from MIMIC-IV (v3.1) and eICU-CRD (v2.0). All baseline variables were collected within 24 hours of ICU admission. Exposure and Outcomes The exposure of interest was aspirin use during hospitalization (no dose restriction), identified from prescription records. The primary outcomes were all-cause mortality at 28 days and 365 days after ICU admission. Secondary outcomes included ICU LOS, total hospital LOS, in-hospital mortality,and gastrointestinal bleeding (GIB). Propensity Score Matching Propensity score matching (PSM) was used to adjust for covariates[29] and enhance robustness via 1:1 nearest-neighbor matching with a caliper width of 0.25. Based on literature consensus[30], variables included in the PSM model were age, weight, sex, race,body temperature, HR, RR, SBP, DBP, SpO₂,VHD, HTN, AKI, CVA, CKD, cancer, T2DM, HL, HF, MI, IHD, COPD, SOFA score, GCS score, APACHE II score,WBC count, Hb, PLT count, anion gap, Glu, potassium, sodium, total calcium, pH,PaO₂,Lac,INR,PT,Cr,BUN,RRT,MV,beta-blockers,NOACs,warfarin. Standardized mean difference (SMD) was used to assess matching quality. Statistical Analysis Categorical variables are presented as counts and percentages and were compared using Pearson’s chi-square test. Continuous variables were assessed for normality using the Kolmogorov–Smirnov test; given non-normal distributions, they are reported as medians [interquartile range (IQR)]. Baseline characteristics were compared between groups. Kaplan–Meier survival curves and log-rank tests were used to compare mortality. Unadjusted and adjusted Cox regression models were fitted to estimate associations, reported with 95% confidence intervals (CIs). Variables with P<0.05 in univariate analysis and prognosis-related variables were included as confounders. Model 1 was unadjusted; Model 2 adjusted for warfarin and NOACs; and Model 3 further adjusted for demographics, vital signs, comorbidities, severity scores, laboratory values, and interventions. Time-dependent Cox regression was also performed. Sensitivity analyses examined aspirin dosage, duration, and timing. Subgroup analyses assessed heterogeneity by sex, age, valvular disease, anticoagulant/antiplatelet use, SOFA score, and comorbidities, with interaction testing. Reporting Guidelines This study followed the Reporting of Studies Conducted using Observational Routinely-collected Data (RECORD) statement[31]. Results Baseline Characteristics of Sepsis Patients with AF From the MIMIC-IV database, 9,109 eligible patients were identified; 38.3% (n=3,490) received aspirin during the ICU stay(Fig. 1). Compared with non-users, the aspirin group was younger, had higher body weight, included a higher proportion of males, and had slightly lower SOFA and APACHE II scores. Aspirin use was more frequent among patients with HTN, HL, CAD, and MI, whereas no significant difference was observed for CBD. The aspirin group had lower rates of RRT but higher rates of MV. Medication use differed between groups: beta-blockers and warfarin were used more frequently in the aspirin group, whereas NOACs were used less frequently(Table 1).After PSM, 3,586 patients (1,793 per group) were included, and most baseline imbalances were corrected (Table 1).In eICU-CRD, 2,226 patients met inclusion criteria, and 21.7% (n=482) received aspirin. Similar to MIMIC-IV, the aspirin group had lower severity scores and higher warfarin use(Supplementary Table 1). Baseline Characteristics Stratified by Mortality Status At 28-day follow-up, survivors and non-survivors differed significantly. Aspirin treatment rates were higher among survivors (28-day: 43.77% vs. 17.28%; 1-year: 44.52% vs. 19.60%)(Table 1), with a similar pattern in eICU-CRD(Supplementary Table 1). In MIMIC-IV, survivors had lower heart rate, respiratory rate,Lac，creatinine, and glucose, and higher PaO₂.Survivors also had lower CRRT use but higher use of warfarin, beta-blockers, and NOACs.But survivors had a lower rate of PPI/H₂RA use.Non-survivors had higher rates of VHD,AKI,CKD,MI,IHD,and COPD and lower prevalence of hypertension(Supplementary Tables 2 and 3). Clinical Outcomes Primary outcomes: In the unmatched MIMIC-IV cohort, 28-day and 1-year mortality were higher in the non-aspirin group than in the aspirin group (27.6% vs. 9.28%, P<0.001; 32.48% vs. 12.75%, P<0.001, respectively). After PSM, mortality remained lower in the aspirin group at 28 days (16.06% vs. 23.70%, P<0.001) and 1 year (21.03% vs. 29.22%, P<0.001)(Table 1). In eICU-CRD, mortality at 28 days was consistently lower in the aspirin group(Supplementary Table 4 ). Secondary outcomes: In the unmatched cohort, ICU and total hospital LOS were longer in the non-aspirin group (P<0.001)(Table 1). After PSM, differences in ICU LOS (P=0.738) and total hospital LOS (P=0.736) were not statistically significant(Table 1). No significant LOS differences were observed in eICU-CRD(Supplementary Table 1).In the unadjusted cohort, the aspirin group had a lower risk of in-hospital GIB than the non-aspirin group (Table 1). After propensity score matching, the incidence of in-hospital GIB was 5.74% (103/1,793) in the aspirin group and 7.14% (128/1,793) in the non-aspirin group (P = 0.089) (Table 1). In a multivariable logistic regression model adjusting for hospital length of stay, aspirin use was not significantly associated with in-hospital GIB (OR 0.792, 95% CI 0.604–1.034; P = 0.088)(Supplementary Fig.2). Similarly, no statistically significant difference between groups was observed in the eICU-CRD cohort (Supplementary Table 1) Survival Analysis and External Validation In the PSM-matched MIMIC-IV cohort, Kaplan–Meier analyses showed higher mortality in the non-aspirin group for both 28-day and 1-year outcomes (log-rank P<0.001)(Fig.2), with similar findings in eICU-CRD(Supplementary Fig.2). Multivariable Cox regression analyses across Models 1–3 consistently indicated that aspirin use was independently associated with improved 28-day, 1-year, and in-hospital survival.For 28-day mortality, the fully adjusted Model 3 yielded an adjusted estimate of 0.61 (95% CI: 0.52–0.70; P<0.001)(Table 2). These findings were externally validated in eICU-CRD across three models (Model 3: 0.79, 95% CI: 0.63–0.99; P=0.044)(Supplementary Table. 5). Time-Dependent Cox Regression Analysis Time-dependent Cox regression evaluated dynamic aspirin exposure and mortality. Aspirin exposure was significantly associated with reduced mortality at 28 days (HR=0.27, 95%CI: 0.21–0.35; P<0.001), 90 days (HR=0.29,95%CI: 0.23–0.38 P<0.001), and 365 days (HR=0.29, 95%CI: 0.23–0.38;P<0.001)(Supplementary Table. 6)(Supplementary Table 6). Associations of Exposure Characteristics with Outcomes Stratified analyses evaluated dosage, duration, and timing with respect to 28-day mortality. Cumulative aspirin dose was not significantly associated with mortality (HR=1.00;95% CI, 1.00–1.00). In contrast, the ratio of aspirin duration to total hospital LOS (HR=0.51;95%CI,0.35–0.73;P<0.001) and to ICU LOS (HR=0.43; 95% CI, 0.37–0.50; P<0.001) was inversely associated with mortality. Regarding timing, aspirin initiation after sepsis diagnosis (HR=0.32 95%CI,0.25–0.41; P<0.001 P<0.001) or after ICU admission (HR=0.33 95% CI, 0.25–0.43, P<0.001) was associated with reduced mortality(Figure.3). Subgroup Analysis In the matched cohort, aspirin was associated with a protective effect (HR<1, P0.05). A significant interaction was observed with beta-blocker use, with a more pronounced association in patients receiving beta-blockers. Significant associations were also observed in subgroups without GI bleeding, without CRRT, and those receiving mechanical ventilation. AF pattern demonstrated significant interaction (P<0.007): the association was limited in patients without AF occurrence after ICU admission, whereas clear associations were observed in patients with AF at admission or new-onset AF during hospitalization(Figure.4). Discussion Clinical management of sepsis is challenging, particularly when complicated by AF[13, 32], which is associated with poor prognosis. In this large, multicenter retrospective cohort study, we systematically evaluated the association between aspirin use and clinical outcomes in sepsis patients with AF. After rigorous adjustment for baseline imbalances using propensity score matching and multivariable Cox regression models, aspirin use was consistently associated with significantly reduced 28-day and 1-year all-cause mortality. These findings were robust across multiple analytical approaches, including time-dependent Cox models, and were externally validated in the eICU-CRD cohort. Importantly, aspirin use was not independently associated with an increased risk of in-hospital GIB after adjustment for length of stay, suggesting a favorable benefit–risk profile in this high-risk population. Collectively, these results indicate that aspirin exposure is associated with improved short- and long-term survival in sepsis patients complicated by AF. A growing body of evidence suggests that sepsis involves a tightly coupled dysregulation of inflammation and coagulation, leading to microvascular dysfunction, immunothrombosis, and organ injury; platelets play a central role in this process not only as mediators of hemostasis but also as active participants in immune regulation and inflammatory amplification during sepsis[13]. Accordingly, antiplatelet therapy—including aspirin—has been proposed as a strategy to modulate the immunothrombotic axis, yet observational studies have reported heterogeneous findings, and meta-analyses indicate a possible reduction in short-term mortality while remaining limited by substantial heterogeneity and residual confounding[33, 34]. In parallel, AF is among the most common ICU arrhythmias, and sepsis-associated new-onset AF has been linked to higher risks of stroke and mortality, with long-term data suggesting it may confer persistent vulnerability to recurrent AF and adverse outcomes[5]. Walkey et al. further showed that new-onset AF during sepsis is independently associated with increased short-term mortality and stroke risk, underscoring AF as both a marker of illness severity and a potential contributor to poor prognosis [6]. However, evidence guiding optimal antithrombotic strategies in septic patients with AF remains limited, as most prior sepsis–antiplatelet studies did not specifically address this phenotype characterized by inflammation-driven hypercoagulability. Therefore, evaluating aspirin specifically in septic patients with AF is clinically relevant. Sepsis is characterized by dysregulated inflammation, endothelial dysfunction, platelet activation, and immunothrombosis. AF may further exacerbate this prothrombotic and proinflammatory milieu through atrial mechanical dysfunction and systemic inflammatory amplification. The potential survival benefit of aspirin may involve antiplatelet, anti-inflammatory, and immunomodulatory pathways[35]. First, aspirin irreversibly inhibits platelet cyclooxygenase-1 (COX-1), thereby suppressing thromboxane A₂ (TXA₂) generation and reducing platelet aggregation and thrombosis propensity[36]. In sepsis, platelet activation and endothelial injury promote microthrombus formation and impair organ perfusion, and antiplatelet interventions may attenuate this immunothrombosis-related injury [33, 34]. This pathway may be particularly relevant in sepsis complicated by AF, where blood flow stasis and systemic inflammation can synergistically increase thromboembolic risk[5, 6]. Second, aspirin exerts anti-inflammatory and immunomodulatory effects, including attenuation of platelet–leukocyte interactions and modulation of endothelial activation, which are central to sepsis-induced organ dysfunction. Beyond inhibiting pro-inflammatory mediators, aspirin can trigger pro-resolving lipid mediators (e.g., aspirin-triggered lipoxins), potentially promoting resolution of inflammation and limiting tissue injury. Experimental data demonstrate that aspirin-triggered 15-epi-lipoxin A4 can regulate neutrophil–platelet aggregation and mitigate acute lung injury, supporting a biologically plausible anti-inflammatory and organ-protective effect[37]. Third, platelets interact with neutrophils to facilitate neutrophil extracellular trap (NET) formation, a process implicated in thrombosis and inflammatory injury. Thus, aspirin-mediated inhibition of platelet activation may indirectly modulate NET-associated immunothrombotic cascades[38]. Importantly, as this was a retrospective observational study, these mechanistic considerations are based on prior evidence and were not directly measured in our cohort, warranting confirmation in prospective studies. Several notable findings in this study merit further discussion. First, the absence of an increased risk of in-hospital GIB after adjustment for length of stay is clinically relevant, as bleeding concerns often limit aspirin use in critically ill patients. Regarding timing and dosage, prior findings have been inconsistent [39]. In this cohort of sepsis patients with AF, survival associations were observed when aspirin was initiated after sepsis diagnosis or after ICU admission. No significant association was observed with cumulative dose, suggesting a possible threshold effect for antiplatelet and/or anti-inflammatory activity. In contrast, stronger inverse associations were observed for longer aspirin exposure relative to hospitalization or ICU stay. Because sepsis involves dynamic and persistent activation of inflammation and coagulation[2],sustained inhibition of platelet activity and related endothelial effects may be relevant to prognosis. Subgroup analyses supported broad consistency across age, sex, severity, and most comorbidities. The lack of interaction in patients with prior cerebral or myocardial infarction suggests that aspirin’s association in sepsis may not be limited to secondary cardiovascular prevention and may relate to broader processes such as endothelial injury and microvascular barrier integrity[3, 20, 40]. The significant association observed in mechanically ventilated patients may also be consistent with a potential role in mitigating ARDS progression through anti-inflammatory and anti-thrombotic mechanisms[18, 41]. Given the central role of anticoagulation in AF management, potential interactions were examined. The association remained consistent among patients receiving warfarin or NOACs (interaction P > 0.05) and was significant among those not receiving warfarin, suggesting that aspirin’s association may be independent of or complementary to traditional anticoagulants. Whereas oral anticoagulants inhibit fibrin formation, aspirin targets platelet activation. In early sepsis, platelet–leukocyte interactions contribute to immunothrombosis[42, 43]. AF further exacerbates the procoagulant milieu, as inflammatory cells, platelets, and the coagulation system interact synergistically to drive microvascular thrombosis, ultimately leading to multiple organ dysfunction[44–46]. In this context, aspirin may reduce microvascular thrombosis and improve perfusion. A stronger association in patients receiving beta-blockers may indicate a clinically relevant intersection between sympathetic modulation and antithrombotic pathways[3, 35]. Stratification by AF pattern further localized the association, with clearer findings among patients with AF at admission or new-onset AF during hospitalization and more limited findings among those without detected AF. In the context of sepsis-induced hypercoagulability, AF-related loss of atrial mechanical function may amplify thromboembolic risk[6, 44, 47], potentially defining a subgroup in which aspirin is most relevant. For new-onset AF, its occurrence is itself regarded as a marker of increased sepsis severity and an amplified inflammatory response [40, 47]. Beyond its inhibitory effect on platelet aggregation, aspirin may also exert protective effects by activating the AMP-activated protein kinase (AMPK) pathway, thereby preventing pathological atrial remodeling and fibrosis[21], which may partially explain the survival advantage observed in AF-related subgroups. Although prior studies have reported heterogeneous results[4, 48], the present analysis supports the potential value of aspirin in the specific high-risk phenotype of sepsis with AF. Discrepancies in the literature may reflect cohort heterogeneity and differences in exposure definitions. Overall, these findings underscore aspirin’s potential relevance within the interplay of inflammation, immune dysregulation, and thrombosis in this population[3]. Limitations This study has several limitations. First, as a retrospective observational analysis, residual bias and unmeasured confounding (e.g., specific indications for discontinuing aspirin) may remain despite PSM and multivariable adjustment. Second, causality cannot be established. Third, the long study period may not fully reflect evolving sepsis management practices and guidelines. Fourth, clinical status changes dynamically, and single time-point assessments may be insufficient. Fifth, randomized controlled trials are required to confirm efficacy and safety given the lack of unified standards for aspirin initiation and discontinuation. Sixth, future studies should incorporate stratification by biomarkers and genetics to identify optimal candidate populations. Finally, the combined effects of aspirin with other agents warrant further investigation. Conclusion Among patients with sepsis and AF, aspirin administration is associated with reduced all-cause mortality. Prospective clinical trials are needed to provide high-level evidence regarding the populations most likely to benefit, the potential mechanisms involved, and the optimal dosing strategy and timing of initiation. Future research should focus on translating these findings into clinical practice to improve outcomes in sepsis patients with AF. Funding This study was funded by Guangxi University Key Laboratory of Emergency Medicine. Conflict of interest statement The authors declare that they have no competing interests Ethics declarations Given the public characteristics of the MIMIC-IV and eICU-CRD data, ethical approval was deemed unnecessary. Availability of data and materials The data supporting the findings of this study are available from the corresponding author on reasonable request. Author statements All authors have seen and approved the final version of the manuscript being submitted. They warrant that the article is the authors’ original work, hasn’t received prior publication and isn’t under consideration for publication elsewhere. Author contribution WW supervised and designed this research; FC and YZ was responsible for data analysis, designing tables and figures, and paper writing; DW, QW, RS,HG, andWCW were in charge of data analysis and the writing of the results section; and FC was responsible for the review and proofreading of the manuscript. Insert Figure/Table here Table 1. Baseline Characteristics of Sepsis Patients with AF in the MIMIC-IV Database Original cohort PSM cohort Variable Non-aspirin group Aspirin group SMD Non-aspirin group Aspirin group SMD N = 5,619 N = 3,490 N = 1,793 N = 1,793 Demographic Age, (yrs) 77.00 (68.00 - 85.00) 74.00 (66.00 - 81.00) 0.20 76.00 (67.00 - 84.00) 75.00 (67.00 - 84.00) 0.02 Weight,(kg) 77.30 (64.85 - 93.00) 86.00 (73.25 - 101.00) -0.32 81.00 (68.00 - 96.65) 81.40 (68.10 - 97.00) -0.03 Female, n (%) 2,389.00 (42.52%) 1,255.00 (35.96%) 710.00 (39.60%) 700.00 (39.04%) 0.01 Race, n (%) 0.22 0.03 WHITE 3,902.00 (69.44%) 2,635.00 (75.50%) 1,298.00 (72.39%) 1,295.00 (72.23%) ASIAN 152.00 (2.71%) 86.00 (2.46%) 52.00 (2.90%) 45.00 (2.51%) BLACK 473.00 (8.42%) 127.00 (3.64%) 96.00 (5.35%) 102.00 (5.69%) OTHER 346.00 (6.16%) 239.00 (6.85%) 118.00 (6.58%) 116.00 (6.47%) UNKNOWN 746.00 (13.28%) 403.00 (11.55%) 229.00 (12.77%) 235.00 (13.11%) Vital signs on admission Body temperature, (◦C) 36.80 (36.40 - 37.10) 36.70 (36.40 - 37.00) 0.12 36.70 (36.40 - 37.10) 36.70 (36.40 - 37.10) 0.01 HR, (bpm) 91.00 (77.00 - 108.00) 81.00 (75.00 - 92.00) 0.41 87.00 (74.00 - 103.00) 86.00 (75.00 - 101.00) 0.04 RR, (bpm) 20.00 (15.00 - 24.00) 17.00 (15.00 - 20.00) 0.40 19.00 (14.00 - 23.00) 18.00 (15.00 - 23.00) 0.04 SBP, (mmHg) 118.00 (102.00 - 136.00) 113.00 (100.00 - 127.00) 0.22 116.00 (100.00 - 134.00) 115.00 (101.00 - 133.00) 0.01 DBP, (mmHg) 67.00 (54.00 - 80.00) 59.00 (53.00 - 68.00) 0.40 64.00 (52.00 - 77.00) 62.00 (53.00 - 75.00) 0.03 SpO2, (%) 99.00 (95.00 - 100.00) 97.00 (95.00 - 99.00) 0.19 98.00 (94.00 - 100.00) 98.00 (95.00 - 100.00) 0.02 Comorbidity, n (%) HTN 1,936.00 (34.45%) 1,725.00 (49.43%) 0.31 682.00 (38.04%) 716.00 (39.93%) 0.04 AKI 3,156.00 (56.17%) 1,170.00 (33.52%) 0.47 868.00 (48.41%) 837.00 (46.68%) 0.03 CVA 665.00 (11.83%) 393.00 (11.26%) 0.02 236.00 (13.16%) 216.00 (12.05%) 0.03 CKD 1,765.00 (31.41%) 827.00 (23.70%) 0.17 544.00 (30.34%) 536.00 (29.89%) 0.01 Cancer 1,156.00 (20.57%) 630.00 (18.05%) 0.06 333.00 (18.57%) 318.00 (17.74%) 0.02 T2DM 1,956.00 (34.81%) 1,097.00 (31.43%) 0.07 613.00 (34.19%) 601.00 (33.52%) 0.01 HL 2,343.00 (41.70%) 1,914.00 (54.84%) 0.27 828.00 (46.18%) 828.00 (46.18%) 0.00 HF 2,861.00 (50.92%) 1,561.00 (44.73%) 0.12 968.00 (53.99%) 949.00 (52.93%) 0.02 MI 541.00 (9.63%) 384.00 (11.00%) 0.05 227.00 (12.66%) 245.00 (13.66%) 0.03 IHD 2,338.00 (41.61%) 2,270.00 (65.04%) 0.48 982.00 (54.77%) 1,009.00 (56.27%) 0.03 COPD 1,240.00 (22.07%) 551.00 (15.79%) 0.16 393.00 (21.92%) 368.00 (20.52%) 0.03 VHD 5,156.00 (91.76%) 3,317.00 (95.04%) 0.13 1,679.00 (93.64%) 1,678.00 (93.59%) 0.00 Critical assessment on admission SOFA score 5.00 (3.00 - 8.00) 6.00 (4.00 - 9.00) -0.34 6.00 (4.00 - 8.00) 6.00 (4.00 - 8.00) -0.02 GCS, score 14.00 (13.00 - 15.00) 15.00 (14.00 - 15.00) -0.34 15.00 (13.00 - 15.00) 15.00 (13.00 - 15.00) -0.01 APACHEII, score 19.00 (15.00 - 24.00) 22.00 (18.00 - 27.00) -0.35 20.00 (16.00 - 25.00) 20.00 (16.00 - 25.00) -0.02 Biochemistry WBC, count,(10³/μL) 11.70 (8.10 - 16.80) 12.00 (8.70 - 15.90) 0.07 11.60 (8.00 - 16.10) 11.70 (8.50 - 16.00) 0.01 Hb, (g/dL) 10.20 (8.70 - 11.80) 9.70 (8.50 - 11.20) 0.21 10.20 (8.80 - 11.70) 10.20 (8.80 - 11.70) 0.00 PLT, (103/μL) 188.00 (131.00 - 258.00) 157.00 (119.00 - 213.00) 0.27 185.00 (131.00 - 252.00) 180.00 (130.00 - 246.00) 0.02 Anion gap (mEq/L) 15.00 (12.00 - 18.00) 13.00 (10.00 - 15.00) 0.53 14.00 (12.00 - 17.00) 14.00 (12.00 - 17.00) 0.05 Glu, (mg/dl) 138.00 (108.00 - 179.00) 119.00 (105.00 - 141.00) 0.36 131.00 (104.00 - 166.00) 127.00 (105.00 - 160.00) 0.04 Potassium, (mEq/L) 4.20 (3.80 - 4.70) 4.20 (3.90 - 4.60) 0.05 4.20 (3.80 - 4.60) 4.20 (3.80 - 4.60) 0.00 Sodium, (mEq/L) 138.00 (135.00 - 142.00) 139.00 (137.00 - 141.00) -0.09 139.00 (135.00 - 141.00) 138.00 (136.00 - 141.00) 0.02 Total Calcium, (mg/dl) 8.30 (7.80 - 8.80) 8.30 (7.90 - 8.70) -0.01 8.30 (7.80 - 8.80) 8.30 (7.90 - 8.70) 0.01 pH, (units) 7.36 (7.29 - 7.42) 7.40 (7.34 - 7.44) -0.34 7.38 (7.31 - 7.44) 7.38 (7.31 - 7.43) 0.01 PaO2, (mm Hg) 77.00 (44.00 - 132.00) 270.00 (104.00 - 361.00) -1.2 111.00 (61.00 - 214.00) 108.00 (64.00 - 233.00) -0.04 Lac,(mmol/L) 1.70 (1.20 - 2.60) 1.95 (1.40 - 2.80) 0.00 1.70 (1.20 - 2.60) 1.80 (1.30 - 2.60) -0.01 INR 1.40 (1.20 - 2.00) 1.40 (1.20 - 1.60) 0.24 1.40 (1.20 - 1.90) 1.40 (1.20 - 1.70) 0.08 PT 15.80 (13.40 - 21.20) 15.50 (13.80 - 17.70) 0.24 15.70 (13.40 - 21.00) 15.20 (13.30 - 18.60) 0.09 Cr, (mg/dL) 1.30 (0.90 - 2.10) 1.00 (0.80 - 1.40) 0.32 1.20 (0.90 - 1.90) 1.20 (0.80 - 1.80) 0.02 BUN, (mg/dL) 30.00 (19.00 - 48.00) 20.00 (15.00 - 30.00) 0.49 27.00 (18.00 - 43.00) 24.00 (16.00 - 40.00) 0.07 Treatment, n (%) RRT 565.00 (10.06%) 260.00 (7.45%) 0.09 173.00 (9.65%) 175.00 (9.76%) 0.00 MV 4,908.00 (87.35%) 3,352.00 (96.05%) 0.32 1,640.00 (91.47%) 1,667.00 (92.97%) 0.06 Rhythem, n (p%) 0.49 0.08 1 2,043.00 (36.36%) 563.00 (16.13%) 536.00 (29.89%) 475.00 (26.49%) 2 2,382.00 (42.39%) 1,765.00 (50.57%) 818.00 (45.62%) 864.00 (48.19%) 3 1,194.00 (21.25%) 1,162.00 (33.30%) 439.00 (24.48%) 454.00 (25.32%) Medication, n (%) Beta-blockers 4,071.00 (72.45%) 3,165.00 (90.69%) 0.48 1,468.00 (81.87%) 1,515.00 (84.50%) 0.07 NOACs 914.00 (16.27%) 183.00 (5.24%) 0.36 156.00 (8.70%) 151.00 (8.42%) 0.01 Warfarin 1,493.00 (26.57%) 1,860.00 (53.30%) 0.57 723.00 (40.32%) 704.00 (39.26%) 0.02 PPIs/H₂RAs 3,491.00 (62.13%) 2,664.00 (76.33%) 0.31 1,206.00 (67.26%) 1,272.00 (70.94%) 0.08 Outcomes 28-day mortality, n (p%) 1,551.00 (27.60%) 324.00 (9.28%) 0.49 425.00 (23.70%) 288.00 (16.06%) 0.19 1-year mortality, N (%) 1,825.00 (32.48%) 445.00 (12.75%) 0.49 524.00 (29.22%) 377.00 (21.03%) 0.19 LOS of ICU, n (%) 3.97 (2.16 - 7.84) 3.18 (1.68 - 6.19) 0.11 4.43 (2.24 - 8.48) 3.91 (2.10 - 7.68) 0.03 LOS of Hospital, n (%) 10.37 (6.14 - 18.10) 8.95 (6.09 - 15.12) 0.10 10.06 (5.77 - 17.41) 9.38 (5.96 - 16.03) 0.04 In-hospital mortality, n (p%) 520.00 (9.25%) 132.00 (3.78%) 0.22 146.00 (8.14%) 106.00 (5.91%) 0.09 GIB 433.00 (7.71%) 124.00 (3.55%) 0.18 128.00 (7.14%) 103.00 (5.74%) 0.06 Abbreviations: PSM, propensity score matching; SMD, standardized mean difference; HR, heart rate; SBP, systolic blood pressure; DBP, diastolic blood pressure; RR, respiratory rate; SpO₂, peripheral oxygen saturation; WBC, white blood cell count; Hb, hemoglobin; PLT, platelet count; CR, serum creatinine; BUN, blood urea nitrogen; Lac, lactate; SOFA, Sequential Organ Failure Assessment; APACHE II, Acute Physiology and Chronic Health Evaluation II; GCS, Glasgow Coma Scale; MV, invasive mechanical ventilation; RRT, continuous renal replacement therapy. Rhythm: 1 = NO AF throughout ICU stay; 2 = AF present at ICU admission; 3 = New-onset AF after ICU admission. Table 2. Association Between Aspirin Exposure and All-Cause Mortality Model1 Model 2 Model 3 Primary outcomes HR (95%CI) p HR (95%CI) p HR (95%CI) p 28-day mortality Non-aspirin group Reference Reference Reference Aspirin group 0.65(0.56-0.76) <0.001 0.63(0.54-0.73) <0.001 0.61(0.52–0.70) <0.001 1-year mortality Non-aspirin group Reference Reference Reference Aspirin group 0.68(0.60-0.78) <0.001 0.66(0.58–0.76) <0.001 0.64(0.56–0.73) <0.001 Secondary outcome In-hospital mortality Non-aspirin group Reference <0.001 Reference <0.001 Reference <0.001 Aspirin group 0.76(0.66–0.88) 0.73 (0.63–0.84) 0.71(0.60–0.83) Non-aspirin group : patients who did not receive aspirin therapy; Aspirin group : patients who received aspirin therapy; HR: hazard ratio; 95% CI: 95% confidence interval; Model 1 : unadjusted model; Model 2 : adjusted for warfarin and NOACs; Model 3 :Adjusted for demographic characteristics (age, weight, sex, race); vital signs on admission (body temperature, HR, RR, SBP, DBP, SpO₂); comorbidities (VHD, HTN, AKI, CVA, CKD, cancer, T2DM, HL, HF, MI, IHD, COPD); critical assessment on admission (SOFA score, GCS score, APACHE II score); biochemical parameters (WBC count, Hb, PLT count, anion gap, Glu, potassium, sodium, total calcium, pH, PaO₂, Lac, INR, PT, Cr, BUN); treatment (RRT, MV); and medications (beta-blockers, NOACs, warfarin). Figure 1 Flow chart of this study. Figure 2 Kaplan–Meier analysis of aspirin exposure and 28-day/365-day mortality. A. Cumulative incidence of 28-day mortality with numbers at risk. B. Cumulative incidence of 1-year mortality with numbers at risk. Non-aspirin: patients without aspirin exposure; Aspirin: patients with aspirin exposure. Figure 3 Stratified analyses of the associations between aspirin use haracteristics and mortality . Aspirin Hospitalization Coverage Ratio (AHCR); Aspirin ICU Coverage Ratio (AICR) ; starttime1: initiation of aspirin at ICU admission; starttime2: initiation of aspirin after sepsis diagnosis; Total Drug Amount: total amount of aspirin administered during hospitalization. Figure 4 Subgroup analysis of 28-day all-cause mortality in sepsis patients with AF according to aspirin use. Supplementary materials Supplementary Table 1 Baseline Characteristics of Sepsis Patients with Atrial Fibrillation in the eICU-CRD Database Supplementary Table 2 Baseline characteristics of patients in MIMIC-IV grouped by 28-day all-cause mortality Supplementary Table 3 Baseline characteristics of patients in MIMIC-IV grouped by 365-day all-cause mortality Supplementary Table 4 Baseline Characteristics Stratified by 28-Day Mortality in the eICU-CRD Database Supplementary Table 5 Association Between Aspirin Exposure and All-Cause Mortality in the eICU-CRD Database Supplementary Table 6 Univariate time-varying Cox regression of aspirin and mortality in the MIMIC-IV Database. Supplementary Figure 1 Kaplan–Meier analysis of aspirin exposure and 28-day mortality. Supplementary Figure 2 Forest plot of multivariable logistic regression for aspirin use and in-hospital References 1. Singer M, Deutschman CS, Seymour CW, Shankar-Hari M, Annane D, Bauer M, et al. 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Authors Affiliations Fangchao Chen The First Affiliated Hospital of Guangxi Medical University View all articles by this author Yufeng Zhong Liuzhou Workers' Hospital View all articles by this author Dianyang Wang Liuzhou Workers' Hospital View all articles by this author Qiuyin Wei Liuzhou Workers' Hospital View all articles by this author Rui Su Liuzhou Workers' Hospital View all articles by this author Hongfei Ge Liuzhou Workers' Hospital View all articles by this author WenCai Wei Liuzhou Workers' Hospital View all articles by this author Wei Wang [email protected] The First Affiliated Hospital of Guangxi Medical University View all articles by this author Metrics & Citations Metrics Article Usage 157 views 54 downloads .FvxKWukQNSOunydq8rnd { width: 100px; } Citations Download citation Fangchao Chen, Yufeng Zhong, Dianyang Wang, et al. Impact of Aspirin on Clinical Outcomes in Sepsis Patients with Atrial Fibrillation: An Analysis of the MIMIC-IV and eICU-CRD Databases. 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