Early indication of decompensated heart failure in patients on home-telemonitoring: a comparison of prediction algorithms based on daily weight and noninvasive transthoracic bio-impedance

Cuba Gyllensten, I., Bonomi, A. G., Goode, K. M., Reiter, H., Habetha, J., Amft, O. and Cleland, J. G.F. (2016) Early indication of decompensated heart failure in patients on home-telemonitoring: a comparison of prediction algorithms based on daily weight and noninvasive transthoracic bio-impedance. JMIR Medical Informatics, 4(1), e3. (doi: 10.2196/medinform.4842) (PMID:26892844) (PMCID:PMC4777885)

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Abstract

Background: Heart Failure (HF) is a common reason for hospitalization. Admissions might be prevented by early detection of and intervention for decompensation. Conventionally, changes in weight, a possible measure of fluid accumulation, have been used to detect deterioration. Transthoracic impedance may be a more sensitive and accurate measure of fluid accumulation. Objective: In this study, we review previously proposed predictive algorithms using body weight and noninvasive transthoracic bio-impedance (NITTI) to predict HF decompensations. Methods: We monitored 91 patients with chronic HF for an average of 10 months using a weight scale and a wearable bio-impedance vest. Three algorithms were tested using either simple rule-of-thumb differences (RoT), moving averages (MACD), or cumulative sums (CUSUM). Results: Algorithms using NITTI in the 2 weeks preceding decompensation predicted events (P<.001); however, using weight alone did not. Cross-validation showed that NITTI improved sensitivity of all algorithms tested and that trend algorithms provided the best performance for either measurement (Weight-MACD: 33%, NITTI-CUSUM: 60%) in contrast to the simpler rules-of-thumb (Weight-RoT: 20%, NITTI-RoT: 33%) as proposed in HF guidelines. Conclusions: NITTI measurements decrease before decompensations, and combined with trend algorithms, improve the detection of HF decompensation over current guideline rules; however, many alerts are not associated with clinically overt decompensation.

Item Type:Articles
Additional Information:This work was supported by the EU Marie Curie Network iCareNet under grant number 264738. Data were provided by the MyHeart project, which was partially financed by the EU FP6 program under grant number 507816.
Status:Published
Refereed:Yes
Glasgow Author(s) Enlighten ID:Cleland, Professor John
Authors: Cuba Gyllensten, I., Bonomi, A. G., Goode, K. M., Reiter, H., Habetha, J., Amft, O., and Cleland, J. G.F.
Subjects:R Medicine > R Medicine (General)
College/School:College of Medical Veterinary and Life Sciences > School of Health & Wellbeing > Robertson Centre
Journal Name:JMIR Medical Informatics
Publisher:JMIR Publications
ISSN:2291-9694
ISSN (Online):2291-9694
Copyright Holders:Copyright © 2016 The Authors
First Published:First published in JMIR Medical Informatics 4(1): e3
Publisher Policy:Reproduced under a Creative Commons License

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