ArticlePloS one2026
Eosinophil count trajectories are associated with the prognosis of acute myocardial infarction patients: Insights from ICU data analysis.
Article in PloS one, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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Who cites it
1 citing paper in PubMed.
- Inflammatory Signatures from the Complete Blood Count and In-Hospital Mortality in Acute Myocardial Infarction.Journal of clinical medicine · 2026Article
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9 authors.
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Abstract
objectivePrevious clinical studies have demonstrated conflicting evidence regarding the relationship between eosinophil (EOS) count and adverse outcomes in acute myocardial infarction (AMI). This study aimed to evaluate the impact of EOS count trajectories during ICU admission on mortality and the incidence of acute kidney injury (AKI) in AMI patients.
methodsA total of 1,493 critically ill AMI patients from the MIMIC-IV database were enrolled. Primary outcomes included 28-day and 1-year mortality, and secondary outcomes encompassed severe AKI incidence and ICU mortality. Group-based trajectory modeling (GBTM) was applied to identify distinct EOS count trajectories. Survival differences were assessed by Kaplan-Meier curves and log-rank tests. Associations between the EOS trajectory and mortality were evaluated using multivariable logistic/Cox regression. Furthermore, mediation analysis was conducted to investigate the potential mediating effect of AKI on mortality.
resultsThree EOS trajectories were identified: Trajectory1 (stable-low), Trajectory2 (low-level steady rise), and Trajectory3 (medium-level rapid rise). Compared to Trajectory1, both the Trajectory2 (HR = 0.68, 95% CI: 0.47-0.99) and Trajectory3 (HR = 0.63, 95% CI: 0.50-0.79) showed significant reductions in 28-day mortality risk. The Trajectory3 also exhibited a 34% lower 1-year mortality risk compared to Trajectory1 (HR = 0.72, 95% CI: 0.60-0.86). Mediation analysis revealed that AKI partially mediated the association between EOS trajectories and 28-day mortality.
conclusionEOS count trajectory independently predicts both short- and long-term mortality in critically ill AMI patients, establishing its role as a reliable marker for risk stratification and prognostic evaluation.
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