BMC Infectious Diseases (Jun 2023)

Organism type of infection is associated with prognosis in sepsis: an analysis from the MIMIC-IV database

  • Qiuping Guo,
  • Peng Qu,
  • Wanfu Cui,
  • Mingrong Liu,
  • Huiling Zhu,
  • Weixin Chen,
  • Nan Sun,
  • Shiyu Geng,
  • Weihua Song,
  • Xu Li,
  • Anni Lou

DOI
https://doi.org/10.1186/s12879-023-08387-6
Journal volume & issue
Vol. 23, no. 1
pp. 1 – 11

Abstract

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Abstract 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.

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