Early prediction of survival at different time intervals in sepsis patients: A visualized prediction model with nomogram and observation study.

ABSTRACT:

Objectives

Sepsis is a major cause of death around the world. Complicated scoring systems require time to have data to predict short-term survival. Intensivists need a tool to predict survival in sepsis patients easily and quickly.

Materials and methods

This retrospective study reviewed the medical records of adult patients admitted to the surgical intensive care units between January 2009 and December 2011 in National Taiwan University Hospital. For this study, 739 patients were enrolled. We recorded the demographic and clinical variables of patients diagnosed with sepsis. A Cox proportional hazard model was used to analyze the survival data and determine significant risk factors to develop a prediction model. This model was used to create a nomogram for predicting the surv

SUBMITTER: Chen SH 

PROVIDER: S-EPMC8830554 | biostudies-literature | 2022 Jan-Mar

REPOSITORIES: biostudies-literature