Organism type of infection is associated with prognosis in sepsis: an analysis from the MIMIC-IV database
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Updated: Jul 25, 2025
A Data-Driven Approach to Quantifying Immune States in Sepsis
Published on: February 7, 2025
Qiuping Guo1, Peng Qu1,2, Wanfu Cui1
1Department of Emergency Medicine, Southern Medical University Nanfang Hospital, Guangzhou, 510515, China.
Background:
Sepsis has a high mortality rate, which is expensive to treat, and is a major drain on healthcare resources; it seriously impacts the quality of human life. The clinical features of positive or non-positive blood cultures have been reported, but the clinical features of sepsis with different microbial infections and how they contribute to clinical outcomes have not been adequately described.
Methods:
We extracted clinical data of septic patients with a single pathogen from the online Medical Information Mart for Intensive Care(MIMIC)-IV database. Based on microbial cultures, patients were classified into Gram-negative, Gram-positive, and fungal groups. Then, we analyzed the clinical characteristics of sepsis patients with Gram-negative, Gram-positive, and fungal infections. The primary outcome was 28-day mortality. The secondary outcomes were in-hospital mortality, the length of hospital stay, the length of ICU stay, and the ventilation duration. In addition, Kaplan-Meier analysis was used for the 28-day cumulative survival rate of patients with sepsis. Finally, we performed further univariate and multivariate regression analyses for 28-day mortality and created a nomogram for predicting 28-day mortality.
Results:
The analysis showed that bloodstream infections showed a statistically significant difference in survival between Gram-positive and fungal organisms; drug resistance only reached statistical significance for Gram-positive bacteria. Through univariate and multivariate analysis, it was found that both the Gram-negative bacteria and fungi were independent risk factors for the short-term prognosis of sepsis patients. The multivariate regression model showed good discrimination, with a C-index of 0.788. We developed and validated a nomogram for the individualized prediction of 28-day mortality in patients with sepsis. Application of the nomogram still gave good calibration.
Conclusions:
Organism type of infection is associated with mortality of sepsis, and early identification of the microbiological type of a patient with sepsis will provide an understanding of the patient's condition and guide treatment.
Insights
Sepsis mortality differs by infection type; Gram-negative bacteria and fungi independently increase sepsis patient mortality risk. Identifying the specific pathogen early can guide treatment and improve outcomes.
Area of Science:
- Infectious Diseases
- Critical Care Medicine
- Medical Informatics
Background:
- Sepsis presents a significant global health challenge with high mortality and substantial healthcare costs.
- While general sepsis features are known, detailed clinical characteristics and outcome impacts of specific microbial infections remain underexplored.
Purpose of the Study:
- To investigate the clinical features and outcomes of sepsis patients based on different causative microorganisms (Gram-negative, Gram-positive, and fungal).
- To identify specific microbial types as independent risk factors for sepsis prognosis.
- To develop a predictive model for 28-day mortality in sepsis patients.
Main Methods:
- Retrospective analysis of clinical data from septic patients with single-pathogen infections using the MIMIC-IV database.
- Classification of patients into Gram-negative, Gram-positive, and fungal infection groups.
- Analysis of clinical characteristics, mortality (28-day and in-hospital), length of stay, and ventilation duration.
- Kaplan-Meier survival analysis and univariate/multivariate regression analyses.
- Development and validation of a nomogram for predicting 28-day sepsis mortality.
Main Results:
- A statistically significant difference in survival was observed between Gram-positive and fungal bloodstream infections.
- Gram-negative bacteria and fungi were identified as independent risk factors for short-term sepsis prognosis.
- The developed nomogram demonstrated good discrimination (C-index: 0.788) and calibration for predicting 28-day mortality.
Conclusions:
- The type of infecting organism significantly influences sepsis-related mortality.
- Early microbiological identification in sepsis is crucial for understanding patient condition and tailoring effective treatment strategies.
