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Development and validation of a nomogram for predicting stroke risk in patients with hypercholesterolemia: a study
Fangjian Wang1, Zhihong Ren2, Xianning Fu3
1Department of Laboratory Medicine, Dazhou Integrated Traditional Chinese Medicine & Western Medicine Hospital, Dazhou Second People's Hospital, Dazhou, China.
Laboratory Medicine
|November 22, 2025
Summary
This study identified key stroke risk factors in hypercholesterolemia patients, developing a nomogram for personalized risk assessment. The tool shows excellent accuracy for predicting stroke in this population.
Area of Science:
- Cardiovascular Medicine
- Epidemiology
- Biostatistics
Background:
- Hypercholesterolemia is a significant risk factor for stroke.
- Identifying independent predictors is crucial for effective stroke prevention strategies.
Purpose of the Study:
- To identify independent risk factors for stroke in patients with hypercholesterolemia.
- To develop and validate a clinically applicable risk prediction nomogram.
Main Methods:
- Analysis of a nationally representative dataset (US National Health and Nutrition Examination Survey).
- Utilized least absolute shrinkage and selection operator (LASSO) regression and multivariate logistic regression.
- Model validation using receiver operating characteristic (ROC) curve analysis, calibration curves, and decision curve analysis.
Main Results:
- Identified four independent predictors: age, total cholesterol, serum urea nitrogen, and white blood cell count.
- The nomogram demonstrated excellent discriminatory capability (AUC 0.811 in training, 0.835 in validation).
- High concordance between predicted and observed outcomes, with significant clinical utility.
Conclusions:
- A novel nomogram for stroke risk prediction in hypercholesterolemia patients was developed.
- The nomogram exhibits robust performance and aids in personalized risk stratification.
- Facilitates tailored intervention strategies in clinical practice.
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