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June 14, 2023Cardiovascular DiabetologyOpen Access

Machine learning-based models to predict one-year mortality among Chinese older patients with coronary artery disease combined with impaired glucose tolerance or diabetes mellitus

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Why the study?

Accurate survival prediction guides clinical decisions, motivating the development of a machine learning model to predict one-year mortality in older patients with CAD and IGT or DM.

Population

451 older patients with CAD combined with IGT or DM

Design

Prospective cohort study

Follow-up

One-year

Authors

YLYan LiLGLixun GuanCNChaoxue Ning

Discussion

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Member takes

Overview

High one-year mortality in this statin cohort warrants clinical caution; leaves open questions on comparative effectiveness requiring prospective trials.

Structured PICO

P
Population
451 older patients (aged >60 years) with coronary artery disease (CAD) combined with impaired glucose tolerance (IGT) or diabetes mellitus (DM), median age 86, 89.6% male, admitted to the Department of Geriatric Cardiology, Chinese PLA General Hospital.
I
Intervention
Machine learning-based prediction models (gradient boosting machine, random forest, decision tree, logistic regression) to predict one-year mortality.
O
Outcome
All-cause mortality within one year after dischargehard clinical

A gradient boosting machine model accurately predicts one-year mortality in older Chinese patients with CAD and impaired glucose tolerance or diabetes, identifying NT-proBNP, albumin, and statin use as key prognostic factors.

Cite This Study

Li et al. (2023) studied this question.

synapsesocial.com/papers/6a3f98dcf157b8c38b07cfb2https://doi.org/10.1186/s12933-023-01854-z
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