The nomogram using nine routine clinical variables predicted prevalent HFpEF with a C-index of 0.762 in training and 0.783 in validation cohorts, demonstrating good discrimination and calibration.
Cross-Sectional (n=4,213)
No
Does a pragmatic nomogram using routinely collected clinical variables accurately estimate the probability of prevalent HFpEF in adult patients?
A pragmatic nomogram using nine routinely available clinical and laboratory variables can effectively estimate the individualized probability of prevalent HFpEF to help prioritize confirmatory echocardiography.
Effect estimate: C-index 0.762 in training cohort, 0.783 in validation cohort (95% CI AUC 0.76 (95% CI: 0.74–0.78) training; 0.78 (95% CI: 0.76–0.81) validation)
Abstract Objectives To develop and temporally validate a pragmatic nomogram based on routinely available clinical and laboratory variables to estimate the individualized probability of prevalent heart failure with preserved ejection fraction (HFpEF) at the index assessment, and to support screening or triage, and prioritization for confirmatory echocardiography in settings where comprehensive imaging resources are limited. Methods A total of 2187 cases were collected for the prediction model. Another 2026 cases from a new data set were utilized for performing independent temporal validation. The LASSO regression analysis was used to control possible variables. A final screening or triage nomogram for HFpEF was established based on logistic regression, and the discrimination and calibration of the established nomogram were evaluated by bootstrapping with 1000 resamples. Results The final nomogram for screening or triage prevalent HFpEF was constructed using nine predictors retained in the final model: Age, systolic blood pressure (SBP), monocyte ratio (MONO%), red cell distribution width–coefficient of variation (RDW-CV), fasting glucose (GLU), triglycerides (TG), high-density lipoprotein cholesterol (HDL-C), Urea, and immunoglobulin G (IgG). The model demonstrated good discrimination, with a C-index of 0.762 in the training cohort and 0.783 in the validation cohort. Calibration plots showed good agreement between predicted and observed probabilities in both cohorts. Internal and temporal validation indicated that the model was robust and reliable. Conclusions This cross-sectional screening prediction nomogram estimates individualized risk of prevalent HFpEF using readily non-imaging variables and may support screening or triage and efficient allocation of echocardiography resources across hospital and community workflows. The tool is intended to prioritize referral for echocardiographic confirmation rather than replace guideline-based diagnosis. Prospective multicenter studies are warranted to evaluate transportability, clinical utility, and implementation impact.
Chen et al. (Tue,) conducted a cross-sectional in Heart failure with preserved ejection fraction (HFpEF) (n=4,213). Nomogram using nine routinely collected clinical variables (Age, SBP, MONO%, RDW-CV, GLU, TG, HDL-C, Urea, IgG) to screen prevalent HFpEF vs. None (model development and validation study) was evaluated on Prevalent HFpEF diagnosis at index assessment confirmed by HFA-PEFF diagnostic algorithm (C-index 0.762 in training cohort, 0.783 in validation cohort, 95% CI AUC 0.76 (95% CI: 0.74–0.78) training; 0.78 (95% CI: 0.76–0.81) validation). The nomogram using nine routine clinical variables predicted prevalent HFpEF with a C-index of 0.762 in training and 0.783 in validation cohorts, demonstrating good discrimination and calibration.