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Updated: Jun 19, 2025

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Diagnostic Yield and Model Prediction Using Wearable Patch Device in HFpEF.

Ying Ju Chen1,2, Pei Hung Liao3, Chung Lieh Hung4,5

  • 1School of Nursing, National Taipei University of Nursing and Health Sciences, Taipei, Taiwan.

Studies in Health Technology and Informatics
|July 25, 2024
PubMed
Summary
This summary is machine-generated.

This study identified key predictors for Heart Failure with preserved Ejection Fraction (HFpEF), including age, BMI, eGFR, comorbidities like CAD and DM, and specific phonocardiogram indicators. These markers can aid in early HFpEF detection.

Keywords:
HFpEFmodelprognosticwearable

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Area of Science:

  • Cardiology
  • Medical Diagnostics
  • Gerontology

Background:

  • Heart failure (HF) is a growing global health concern, particularly impacting aging populations.
  • Heart Failure with preserved Ejection Fraction (HFpEF) presents unique diagnostic challenges.
  • Identifying reliable predictive markers for HFpEF is crucial for timely intervention.

Purpose of the Study:

  • To identify and validate predictive markers for Heart Failure with preserved Ejection Fraction (HFpEF).
  • To evaluate the efficacy of clinical parameters and phonocardiogram indicators in predicting HFpEF.
  • To establish a predictive model for HFpEF using logistic regression analysis.

Main Methods:

  • Logistic regression analysis was employed to assess predictive markers.
  • Key parameters scrutinized included age, Body Mass Index (BMI), estimated Glomerular Filtration Rate (eGFR), and comorbidities (atrial fibrillation, coronary artery disease (CAD), diabetes mellitus (DM)).
  • Phonocardiogram indicators, specifically third heart sound (S3) intensity and Systolic Dysfunction Index (SDI), were evaluated.

Main Results:

  • The logistic regression model identified age (≥ 65 years), BMI (≥ 25 kg/m2), eGFR (<60 mL/min/1.73m2), CAD, DM, S3 intensity (≥5), and SDI (≥5) as significant predictors of HFpEF.
  • The predictive model achieved an Area Under the Curve (AUC) of 0.816 (p < .001).
  • Receiver Operating Characteristic (ROC) analysis indicated a sensitivity of 0.755, specificity of 0.673, and a Youden's index (J) of 0.838.

Conclusions:

  • The study successfully identified a combination of clinical and phonocardiogram markers that effectively predict HFpEF.
  • The developed model demonstrates good diagnostic performance, suggesting potential clinical utility.
  • Further research is warranted to fully elucidate the clinical applicability and limitations of these predictive markers in diverse patient populations.