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Integrating innovative sensors

INTRODUCTION: Heart failure is a significant and growing health problem. To enable a preventative health care system in heart failure, a move is required from the current, intermittent episodical treatment to continuous and ubiquitous access to medical excellence. Home telemonitoring systems that mo...

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Autores principales: Caffarel, Jennifer, Saalbach, Axel, Bonomi, Alberto, Habetha, Joerg, Harris, Matthew, Schauerte, Patrik, Villacastin, Juan Perez, Bover, Ramon, Zugck, Christian, Vogt, Juergen, Alberola, Arcadi García, Cleland, John
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Igitur, Utrecht Publishing & Archiving 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3571128/
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author Caffarel, Jennifer
Saalbach, Axel
Bonomi, Alberto
Habetha, Joerg
Harris, Matthew
Schauerte, Patrik
Villacastin, Juan Perez
Bover, Ramon
Zugck, Christian
Vogt, Juergen
Alberola, Arcadi García
Cleland, John
author_facet Caffarel, Jennifer
Saalbach, Axel
Bonomi, Alberto
Habetha, Joerg
Harris, Matthew
Schauerte, Patrik
Villacastin, Juan Perez
Bover, Ramon
Zugck, Christian
Vogt, Juergen
Alberola, Arcadi García
Cleland, John
author_sort Caffarel, Jennifer
collection PubMed
description INTRODUCTION: Heart failure is a significant and growing health problem. To enable a preventative health care system in heart failure, a move is required from the current, intermittent episodical treatment to continuous and ubiquitous access to medical excellence. Home telemonitoring systems that monitor vital body signs and symptoms with wearable technology, have been proposed to enhance treatment and anticipation of adverse events in heart failure patients (decompensation). AIMS AND OBJECTIVES: We investigated whether the data recorded in a home telemonitoring system using innovative sensors had predictive value in detecting heart failure related events. METHODS: In the MyHeart observational clinical trial, 148 heart failure patients were followed daily for up to one year using an innovative telemonitoring system recording symptoms questionnaires, basic parameters such as body weight and blood pressure, as well as advanced information provided by a bed sensor monitoring night heart rate and activity and a thorax bioimpedance (BIM) device, designed to monitor fluid accumulation in the lungs. The area under the receiver operator characteristic curve (AUC) was used to evaluate the predictive value for heart failure related events of single and combined telemonitoring measurements. RESULTS: The telemonitoring system including innovative sensors was rated positively by the patients, which is further supported by the reasonable compliance rates (>65%) measured. The most predictive variables 14 days preceding an event were thoracic bioimpedance (area under the curve of 0.70), night breathing rate and some symptoms. The initial multiparametric analysis achieved a mean accuracy of 80.6% but would require more data to confirm its generalisation ability. CONCLUSIONS: The measurements performed during the MyHeart trial with 148 patients and 12 months’ follow-up provided evidence supporting the development of predictive algorithms of decompensation to support heart failure management at home. An innovative wearable monitor of thoracic congestion by means of bioimpedance was tested and showed the highest predictive value for heart failure decompensation among a large set of monitored vital signs and symptoms.
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spelling pubmed-35711282013-04-16 Integrating innovative sensors Caffarel, Jennifer Saalbach, Axel Bonomi, Alberto Habetha, Joerg Harris, Matthew Schauerte, Patrik Villacastin, Juan Perez Bover, Ramon Zugck, Christian Vogt, Juergen Alberola, Arcadi García Cleland, John Int J Integr Care Conference Abstract INTRODUCTION: Heart failure is a significant and growing health problem. To enable a preventative health care system in heart failure, a move is required from the current, intermittent episodical treatment to continuous and ubiquitous access to medical excellence. Home telemonitoring systems that monitor vital body signs and symptoms with wearable technology, have been proposed to enhance treatment and anticipation of adverse events in heart failure patients (decompensation). AIMS AND OBJECTIVES: We investigated whether the data recorded in a home telemonitoring system using innovative sensors had predictive value in detecting heart failure related events. METHODS: In the MyHeart observational clinical trial, 148 heart failure patients were followed daily for up to one year using an innovative telemonitoring system recording symptoms questionnaires, basic parameters such as body weight and blood pressure, as well as advanced information provided by a bed sensor monitoring night heart rate and activity and a thorax bioimpedance (BIM) device, designed to monitor fluid accumulation in the lungs. The area under the receiver operator characteristic curve (AUC) was used to evaluate the predictive value for heart failure related events of single and combined telemonitoring measurements. RESULTS: The telemonitoring system including innovative sensors was rated positively by the patients, which is further supported by the reasonable compliance rates (>65%) measured. The most predictive variables 14 days preceding an event were thoracic bioimpedance (area under the curve of 0.70), night breathing rate and some symptoms. The initial multiparametric analysis achieved a mean accuracy of 80.6% but would require more data to confirm its generalisation ability. CONCLUSIONS: The measurements performed during the MyHeart trial with 148 patients and 12 months’ follow-up provided evidence supporting the development of predictive algorithms of decompensation to support heart failure management at home. An innovative wearable monitor of thoracic congestion by means of bioimpedance was tested and showed the highest predictive value for heart failure decompensation among a large set of monitored vital signs and symptoms. Igitur, Utrecht Publishing & Archiving 2012-06-15 /pmc/articles/PMC3571128/ Text en Copyright 2012, International Journal of Integrated Care (IJIC) http://creativecommons.org/licenses/by/3.0/ This work is licensed under a (http://creativecommons.org/licenses/by/3.0) Creative Commons Attribution 3.0 Unported License
spellingShingle Conference Abstract
Caffarel, Jennifer
Saalbach, Axel
Bonomi, Alberto
Habetha, Joerg
Harris, Matthew
Schauerte, Patrik
Villacastin, Juan Perez
Bover, Ramon
Zugck, Christian
Vogt, Juergen
Alberola, Arcadi García
Cleland, John
Integrating innovative sensors
title Integrating innovative sensors
title_full Integrating innovative sensors
title_fullStr Integrating innovative sensors
title_full_unstemmed Integrating innovative sensors
title_short Integrating innovative sensors
title_sort integrating innovative sensors
topic Conference Abstract
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3571128/
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