Cardiovascular

Prediction Model for Frailty in Middle-Aged and Older Adults with Cardiovascular Disease.

TL;DR

A nomogram incorporating sleep duration, ADL, waist circumference, cognitive function, handgrip strength, age, and depression demonstrated good discrimination for predicting frailty risk in middle-aged and older adults with cardiovascular disease, with AUC values of 0.851 and 0.861 in training and validation cohorts respectively.

Key Findings

Frailty was identified in 12.5% of middle-aged and older adults with cardiovascular disease in the study sample.

  • 148 of 1184 participants were identified as frail
  • Participants were aged ≥45 years with cardiovascular disease
  • Data were drawn from the 2015 China Health and Retirement Longitudinal Study (CHARLS)
  • The sample was randomly divided into training and validation cohorts at a 7:3 ratio

Seven independent predictors of frailty were identified through LASSO regression followed by multivariable logistic regression.

  • Predictors identified were: sleep duration, activities of daily living (ADL), waist circumference, cognitive function, handgrip strength, age, and depression
  • LASSO regression was used for initial variable selection to reduce overfitting
  • Multivariable logistic regression was subsequently used to construct the nomogram model
  • The study used a cross-sectional design

The nomogram demonstrated good discrimination for predicting frailty in both training and validation cohorts.

  • AUC of 0.851 (95% CI: 0.814–0.888) in the training cohort
  • AUC of 0.861 (95% CI: 0.804–0.917) in the validation cohort
  • Performance was consistent between cohorts, suggesting the model does not substantially overfit

The nomogram showed good calibration between predicted and observed frailty outcomes.

  • Calibration was assessed using calibration plots and the Hosmer-Lemeshow test
  • Hosmer-Lemeshow test yielded P > 0.05 in both cohorts, indicating no significant lack of fit
  • Good agreement was found between predicted probabilities and observed outcomes

Decision curve analysis indicated favorable clinical utility of the nomogram for frailty prediction.

  • Decision curve analysis (DCA) was used to evaluate clinical net benefit across a range of threshold probabilities
  • DCA results indicated the nomogram provided favorable clinical utility
  • The authors conclude the tool may facilitate early screening and risk stratification in clinical practice

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Citation

Yang X, Zhou H, Huang C, Yuan M, Du X, Zhang C. (2026). Prediction Model for Frailty in Middle-Aged and Older Adults with Cardiovascular Disease.. Vascular health and risk management. https://doi.org/10.2147/VHRM.S581066