A predictive model for the identification of the risk of sepsis in patients with Gram-positive bacteria in the intensive care unit.

ABSTRACT:

Background

Gram-positive bacterial infections are very common in the intensive care unit (ICU) and may lead to sepsis. However, there are no models to predict the risk of sepsis in persons with Gram-positive bacterial infections. Therefore, the purpose of this study was to create and validate a nomogram for predicting the risk of sepsis in patients with common gram-positive bacterial infections.

Methods

Patients infected with three common Gram-positive bacteria who were admitted to the Multiparameter Intelligent Monitoring in Intensive Care IV (MIMIC IV) database were included in this retrospective cohort study. A Cox regression model was used to develop a nomogram for predicting 3-day, 1-week, 2-week, and 1-month sepsis probability. The performance of the nomogram was analy

SUBMITTER: Chen X 

PROVIDER: S-EPMC10586955 | biostudies-literature | 2023 Sep

REPOSITORIES: biostudies-literature