Diagnostic Yield and Model Prediction Using Wearable Patch Device in HFpEF.
Stud Health Technol Inform
; 315: 25-30, 2024 Jul 24.
Article
en En
| MEDLINE
| ID: mdl-39049220
ABSTRACT
Heart failure (HF) is a prevalent global health issue projected to escalate, notably in aging populations. The study aimed to identify predictive markers for Heart Failure with preserved Ejection Fraction (HFpEF). We scrutinized vital parameters like age, BMI, eGFR, and comorbidities like atrial fibrillation, coronary artery disease (CAD), diabetes mellites (DM). Evaluating phonocardiogram indicators-third heart sound(S3) and Systolic Dysfunction Index (SDI)-our logistic regression revealed age (≥ 65years), BMI (≥ 25 kg/m2), eGFR (<60 mL/min/1.73m2), CAD, DM, S3 intensity ≥5, and SDI ≥5 as HFpEF predictors, with AUC = 0.816 (p < .001). ROC diagnosis curve showed that the sensitivity, specificity and Youden's index J of the model were 0.755, 0.673 and 0.838, respectively. Nonetheless, further exploration is crucial to delineate the clinical applicability and constraints of these markers.
Palabras clave
Texto completo:
1
Colección:
01-internacional
Base de datos:
MEDLINE
Asunto principal:
Dispositivos Electrónicos Vestibles
/
Insuficiencia Cardíaca
Límite:
Aged
/
Female
/
Humans
/
Male
/
Middle aged
Idioma:
En
Revista:
Stud Health Technol Inform
Asunto de la revista:
INFORMATICA MEDICA
/
PESQUISA EM SERVICOS DE SAUDE
Año:
2024
Tipo del documento:
Article
País de afiliación:
Taiwán
Pais de publicación:
Países Bajos