What question did this study set out to answer?

This research aims to develop a machine learning model to predict frailty risk in individuals with CKM.

March 21, 2026Cardiovascular Therapeutics0 citationsOpen Access

NHANES‐Derived Machine Learning Model for Early Identification of Frailty Risk in CKM: Optimizing Resource Allocation Through Predictive Analytics

WDWenlong DingUniversity of Science and Technology of China CFCaoyang FangUniversity of Science and Technology of China FSFachao ShiWannan Medical College

Key Points

This research aims to develop a machine learning model to predict frailty risk in individuals with CKM.
Utilized data from NHANES to train the machine learning model.
Focused on middle-aged and older adults with CKM Stages 0-3.
Employed predictive analytics for early risk identification.
The model effectively predicts frailty risk.
Identified high-risk individuals for early intervention.
Aids in optimizing healthcare resource allocation.

Abstract

The machine learning model developed in this study can effectively predict the risk of frailty in middle-aged and older adults with CKM Stages 0-3, providing a valuable tool for early identification of high-risk individuals in clinical practice. This model may help optimize healthcare resource allocation, guide-targeted interventions, and improve health management for patients with CKM.

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