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The Utility of Predicting Hospitalizations Among Patients With Heart Failure Using mHealth: Observational Study

BACKGROUND: 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...

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Autores principales: Cartledge, Susie, Maddison, Ralph, Vogrin, Sara, Falls, Roman, Tumur, Odgerel, Hopper, Ingrid, Neil, Christopher
Formato: Online Artículo Texto
Lenguaje:English
Publicado: JMIR Publications 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7785406/
https://www.ncbi.nlm.nih.gov/pubmed/33350962
http://dx.doi.org/10.2196/18496
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author Cartledge, Susie
Maddison, Ralph
Vogrin, Sara
Falls, Roman
Tumur, Odgerel
Hopper, Ingrid
Neil, Christopher
author_facet Cartledge, Susie
Maddison, Ralph
Vogrin, Sara
Falls, Roman
Tumur, Odgerel
Hopper, Ingrid
Neil, Christopher
author_sort Cartledge, Susie
collection PubMed
description BACKGROUND: 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.
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spelling pubmed-77854062021-01-11 The Utility of Predicting Hospitalizations Among Patients With Heart Failure Using mHealth: Observational Study Cartledge, Susie Maddison, Ralph Vogrin, Sara Falls, Roman Tumur, Odgerel Hopper, Ingrid Neil, Christopher JMIR Mhealth Uhealth Original Paper BACKGROUND: 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. JMIR Publications 2020-12-22 /pmc/articles/PMC7785406/ /pubmed/33350962 http://dx.doi.org/10.2196/18496 Text en ©Susie Cartledge, Ralph Maddison, Sara Vogrin, Roman Falls, Odgerel Tumur, Ingrid Hopper, Christopher Neil. Originally published in JMIR mHealth and uHealth (http://mhealth.jmir.org), 22.12.2020. https://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR mHealth and uHealth, is properly cited. The complete bibliographic information, a link to the original publication on http://mhealth.jmir.org/, as well as this copyright and license information must be included.
spellingShingle Original Paper
Cartledge, Susie
Maddison, Ralph
Vogrin, Sara
Falls, Roman
Tumur, Odgerel
Hopper, Ingrid
Neil, Christopher
The Utility of Predicting Hospitalizations Among Patients With Heart Failure Using mHealth: Observational Study
title The Utility of Predicting Hospitalizations Among Patients With Heart Failure Using mHealth: Observational Study
title_full The Utility of Predicting Hospitalizations Among Patients With Heart Failure Using mHealth: Observational Study
title_fullStr The Utility of Predicting Hospitalizations Among Patients With Heart Failure Using mHealth: Observational Study
title_full_unstemmed The Utility of Predicting Hospitalizations Among Patients With Heart Failure Using mHealth: Observational Study
title_short The Utility of Predicting Hospitalizations Among Patients With Heart Failure Using mHealth: Observational Study
title_sort utility of predicting hospitalizations among patients with heart failure using mhealth: observational study
topic Original Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7785406/
https://www.ncbi.nlm.nih.gov/pubmed/33350962
http://dx.doi.org/10.2196/18496
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