cartledge-utilityofpredicting-2020.pdf (471.26 kB)
The utility of predicting hospitalizations among patients with heart failure using mHealth: observational study
journal contribution
posted on 2020-12-01, 00:00 authored by Susie CartledgeSusie Cartledge, Ralph MaddisonRalph Maddison, S Vogrin, R Falls, O Tumur, I Hopper, C NeilBackground Heart failure decompensation is a major driver of hospitalizations and represents a significant burden to the health care system. Identifying those at greatest risk of admission can allow for targeted interventions to reduce this risk. Objective This paper aims to compare the predictive value of objective and subjective heart failure respiratory symptoms on imminent heart failure decompensation and subsequent hospitalization within a 30-day period. Methods A prospective observational pilot study was conducted. People living at home with heart failure were recruited from a single-center heart failure outpatient clinic. Objective (blood pressure, heart rate, weight, B-type natriuretic peptide) and subjective (4 heart failure respiratory symptoms scored for severity on a 5-point Likert scale) data were collected twice weekly for a 30-day period. Results A total of 29 participants (median age 79 years; 18/29, 62% men) completed the study. During the study period, 10 of the 29 participants (34%) were hospitalized as a result of heart failure. For objective data, only heart rate exhibited a between-group difference. However, it was nonsignificant for variability (P=.71). Subjective symptom scores provided better prediction. Specifically, the highest precision of heart failure hospitalization was observed when patients with heart failure experienced severe dyspnea, orthopnea, and bendopnea on any given day (area under the curve of 0.77; sensitivity of 83%; specificity of 73%). Conclusions The use of subjective respiratory symptom reporting on a 5-point Likert scale may facilitate a simple and low-cost method of predicting heart failure decompensation and imminent hospitalization. Serial collection of symptom data could be augmented using ecological momentary assessment of self-reported symptoms within a mobile health monitoring strategy for patients at high risk for heart failure decompensation.
History
Journal
JMIR mHealth and uHealthVolume
8Issue
12Article number
e18496Pagination
1 - 10Publisher
JMIR Publications Inc.Location
Toronto, Ont.Publisher DOI
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ISSN
2291-5222eISSN
2291-5222Language
engPublication classification
C1 Refereed article in a scholarly journalUsage metrics
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