Research status of risk prediction model for cardiogenic shock based on different patient population
CHEN Yan
AI Bo-wen
Abstract：Cardiogenic shock(CS)is characterized by complex complications and high mortality.Using the prognostic scoring model for CS to stratify the patients accurately and early identify the high-risk patients,which is of great significance to optimize the classified diagnosis and treatment measures and improve the outcome of patients.In recent years,new risk prediction models and machine learning(ML)intelligent analysis have improved the ability of risk classification and prognosis evaluation to CS patients compared with the traditional models,especially a model combining clinical variables with biomarkers has higher accuracy for predicting the CS risk.This paper reviewed the application and research status of CS risk prediction model and ML model based on different patient population.
Keywords：Cardiogenic shockRisk prediction modelPatient populationResearch status
Publication Date：2024-03-10
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：5( 232-236 )