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A pragmatic nomogram using routinely collected clinical variables to screen prevalent HFpEF: development and temporal
Chunmei Chen1, Yuetong Liu2, Xinxin Mao1
1Department of General Internal Medicine, Guang 'anmen Hospital, China Academy of Chinese Medical Sciences, Beijing, China.
BMC Cardiovascular Disorders
|February 24, 2026
Summary
A new nomogram using non-imaging variables can estimate heart failure with preserved ejection fraction (HFpEF) risk. This tool aids in screening and prioritizing patients for echocardiography, especially where resources are limited.
Area of Science:
- Cardiology
- Medical Diagnostics
- Predictive Analytics
Background:
- Heart failure with preserved ejection fraction (HFpEF) diagnosis can be challenging.
- Current diagnostic pathways may rely on imaging resources that are not universally available.
- Efficient screening and triage tools are needed to identify patients at risk for HFpEF.
Purpose of the Study:
- To develop and validate a pragmatic nomogram for estimating the probability of prevalent HFpEF.
- To support screening, triage, and prioritization for echocardiography.
- To utilize routinely available clinical and laboratory variables, avoiding complex imaging.
Main Methods:
- A prediction model was developed using 2187 cases and validated with 2026 independent cases.
- LASSO regression analysis was employed for variable selection.
- Logistic regression established the final nomogram, with performance evaluated using bootstrapping.
Main Results:
- A nine-predictor nomogram was created, including Age, SBP, MONO%, RDW-CV, GLU, TG, HDL-C, Urea, and IgG.
- The nomogram showed good discrimination (C-index 0.762 training, 0.783 validation).
- Calibration was good, and internal/temporal validation confirmed model robustness.
Conclusions:
- The developed nomogram effectively estimates individualized HFpEF risk using non-imaging variables.
- It can aid in screening, triage, and efficient echocardiography resource allocation.
- The tool prioritizes echocardiographic referral, not replacing guideline-based diagnosis.
Keywords:
Chinese populationHeart failure with preserved ejection fractionLogistic modelsNomogramsScreening predictionMore Related Videos
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