{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,9]],"date-time":"2025-11-09T11:15:57Z","timestamp":1762686957144,"version":"3.40.5"},"reference-count":0,"publisher":"IOS Press","isbn-type":[{"type":"electronic","value":"9781643685274"}],"license":[{"start":{"date-parts":[[2024,7,24]],"date-time":"2024-07-24T00:00:00Z","timestamp":1721779200000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024,7,24]]},"abstract":"<jats:p>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\u2014third heart sound(S3) and Systolic Dysfunction Index (SDI)\u2014our logistic regression revealed age (\u2265 65years), BMI (\u2265 25 kg\/m2), eGFR (&lt;60 mL\/min\/1.73m2), CAD, DM, S3 intensity \u22655, and SDI \u22655 as HFpEF predictors, with AUC = 0.816 (p &lt; .001). ROC diagnosis curve showed that the sensitivity, specificity and Youden\u2019s 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.<\/jats:p>","DOI":"10.3233\/shti240100","type":"book-chapter","created":{"date-parts":[[2024,7,24]],"date-time":"2024-07-24T10:52:43Z","timestamp":1721818363000},"source":"Crossref","is-referenced-by-count":1,"title":["Diagnostic Yield and Model Prediction Using Wearable Patch Device in HFpEF"],"prefix":"10.3233","author":[{"ORCID":"https:\/\/orcid.org\/0009-0006-6125-9309","authenticated-orcid":false,"given":"Ying ju","family":"Chen","sequence":"first","affiliation":[{"name":"School of Nursing, National Taipei University of Nursing and Health Sciences, Taipei, Taiwan"},{"name":"Telehealth center, MacKay Memorial Hospital, Taipei, Taiwan"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3047-2394","authenticated-orcid":false,"given":"Pei Hung","family":"Liao","sequence":"additional","affiliation":[{"name":"National Taipei University of Nursing and Health Science School of Nursing, Taipei, Taiwan"}]},{"given":"Chung Lieh","family":"Hung","sequence":"additional","affiliation":[{"name":"Institute of Biomedical Sciences, MacKay Medical College, New Taipei, Taiwan"},{"name":"Department of Internal Medicine, MacKay Memorial Hospital, Taipei, Taiwan"}]}],"member":"7437","container-title":["Studies in Health Technology and Informatics","Innovation in Applied Nursing Informatics"],"original-title":[],"link":[{"URL":"https:\/\/ebooks.iospress.nl\/pdf\/doi\/10.3233\/SHTI240100","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,7,24]],"date-time":"2024-07-24T10:52:44Z","timestamp":1721818364000},"score":1,"resource":{"primary":{"URL":"https:\/\/ebooks.iospress.nl\/doi\/10.3233\/SHTI240100"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,7,24]]},"ISBN":["9781643685274"],"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/shti240100","relation":{},"ISSN":["0926-9630","1879-8365"],"issn-type":[{"type":"print","value":"0926-9630"},{"type":"electronic","value":"1879-8365"}],"subject":[],"published":{"date-parts":[[2024,7,24]]}}}