Cargando…

Wearable Health Technology for Preoperative Risk Assessment in Elderly Patients: The WELCOME Study

Preoperative identification of high-risk groups has been extensively studied to improve patients’ outcomes. Wearable devices, which can track heart rate and physical activity data, are starting to be evaluated for patients’ management. We hypothesized that commercial wearable devices (WD) may provid...

Descripción completa

Detalles Bibliográficos
Autores principales: Greco, Massimiliano, Angelucci, Alessandra, Avidano, Gaia, Marelli, Giovanni, Canali, Stefano, Aceto, Romina, Lubian, Marta, Oliva, Paolo, Piccioni, Federico, Aliverti, Andrea, Cecconi, Maurizio
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9955976/
https://www.ncbi.nlm.nih.gov/pubmed/36832119
http://dx.doi.org/10.3390/diagnostics13040630
_version_ 1784894479230042112
author Greco, Massimiliano
Angelucci, Alessandra
Avidano, Gaia
Marelli, Giovanni
Canali, Stefano
Aceto, Romina
Lubian, Marta
Oliva, Paolo
Piccioni, Federico
Aliverti, Andrea
Cecconi, Maurizio
author_facet Greco, Massimiliano
Angelucci, Alessandra
Avidano, Gaia
Marelli, Giovanni
Canali, Stefano
Aceto, Romina
Lubian, Marta
Oliva, Paolo
Piccioni, Federico
Aliverti, Andrea
Cecconi, Maurizio
author_sort Greco, Massimiliano
collection PubMed
description Preoperative identification of high-risk groups has been extensively studied to improve patients’ outcomes. Wearable devices, which can track heart rate and physical activity data, are starting to be evaluated for patients’ management. We hypothesized that commercial wearable devices (WD) may provide data associated with preoperative evaluation scales and tests, to identify patients with poor functional capacity at increased risk for complications. We conducted a prospective observational study including seventy-year-old patients undergoing two-hour surgeries under general anesthesia. Patients were asked to wear a WD for 7 days before surgery. WD data were compared to preoperatory clinical evaluation scales and with a 6-min walking test (6MWT). We enrolled 31 patients, with a mean age of 76.1 (SD ± 4.9) years. There were 11 (35%) ASA 3–4 patients. 6MWT results averaged 328.9 (SD ± 99.5) m. Daily steps and 𝑉𝑂2𝑚𝑎𝑥 as recorded using WD and were associated with 6MWT performance (R = 0.56, p = 0.001 and r = 0.58, p = 0.006, respectively) and clinical evaluation scales. This is the first study to evaluate WD as preoperative evaluation tools; we found a strong association between 6MWT, preoperative scales, and WD data. Low-cost wearable devices are a promising tool for the evaluation of cardiopulmonary fitness. Further research is needed to validate WD in this setting.
format Online
Article
Text
id pubmed-9955976
institution National Center for Biotechnology Information
language English
publishDate 2023
publisher MDPI
record_format MEDLINE/PubMed
spelling pubmed-99559762023-02-25 Wearable Health Technology for Preoperative Risk Assessment in Elderly Patients: The WELCOME Study Greco, Massimiliano Angelucci, Alessandra Avidano, Gaia Marelli, Giovanni Canali, Stefano Aceto, Romina Lubian, Marta Oliva, Paolo Piccioni, Federico Aliverti, Andrea Cecconi, Maurizio Diagnostics (Basel) Article Preoperative identification of high-risk groups has been extensively studied to improve patients’ outcomes. Wearable devices, which can track heart rate and physical activity data, are starting to be evaluated for patients’ management. We hypothesized that commercial wearable devices (WD) may provide data associated with preoperative evaluation scales and tests, to identify patients with poor functional capacity at increased risk for complications. We conducted a prospective observational study including seventy-year-old patients undergoing two-hour surgeries under general anesthesia. Patients were asked to wear a WD for 7 days before surgery. WD data were compared to preoperatory clinical evaluation scales and with a 6-min walking test (6MWT). We enrolled 31 patients, with a mean age of 76.1 (SD ± 4.9) years. There were 11 (35%) ASA 3–4 patients. 6MWT results averaged 328.9 (SD ± 99.5) m. Daily steps and 𝑉𝑂2𝑚𝑎𝑥 as recorded using WD and were associated with 6MWT performance (R = 0.56, p = 0.001 and r = 0.58, p = 0.006, respectively) and clinical evaluation scales. This is the first study to evaluate WD as preoperative evaluation tools; we found a strong association between 6MWT, preoperative scales, and WD data. Low-cost wearable devices are a promising tool for the evaluation of cardiopulmonary fitness. Further research is needed to validate WD in this setting. MDPI 2023-02-08 /pmc/articles/PMC9955976/ /pubmed/36832119 http://dx.doi.org/10.3390/diagnostics13040630 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Greco, Massimiliano
Angelucci, Alessandra
Avidano, Gaia
Marelli, Giovanni
Canali, Stefano
Aceto, Romina
Lubian, Marta
Oliva, Paolo
Piccioni, Federico
Aliverti, Andrea
Cecconi, Maurizio
Wearable Health Technology for Preoperative Risk Assessment in Elderly Patients: The WELCOME Study
title Wearable Health Technology for Preoperative Risk Assessment in Elderly Patients: The WELCOME Study
title_full Wearable Health Technology for Preoperative Risk Assessment in Elderly Patients: The WELCOME Study
title_fullStr Wearable Health Technology for Preoperative Risk Assessment in Elderly Patients: The WELCOME Study
title_full_unstemmed Wearable Health Technology for Preoperative Risk Assessment in Elderly Patients: The WELCOME Study
title_short Wearable Health Technology for Preoperative Risk Assessment in Elderly Patients: The WELCOME Study
title_sort wearable health technology for preoperative risk assessment in elderly patients: the welcome study
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9955976/
https://www.ncbi.nlm.nih.gov/pubmed/36832119
http://dx.doi.org/10.3390/diagnostics13040630
work_keys_str_mv AT grecomassimiliano wearablehealthtechnologyforpreoperativeriskassessmentinelderlypatientsthewelcomestudy
AT angeluccialessandra wearablehealthtechnologyforpreoperativeriskassessmentinelderlypatientsthewelcomestudy
AT avidanogaia wearablehealthtechnologyforpreoperativeriskassessmentinelderlypatientsthewelcomestudy
AT marelligiovanni wearablehealthtechnologyforpreoperativeriskassessmentinelderlypatientsthewelcomestudy
AT canalistefano wearablehealthtechnologyforpreoperativeriskassessmentinelderlypatientsthewelcomestudy
AT acetoromina wearablehealthtechnologyforpreoperativeriskassessmentinelderlypatientsthewelcomestudy
AT lubianmarta wearablehealthtechnologyforpreoperativeriskassessmentinelderlypatientsthewelcomestudy
AT olivapaolo wearablehealthtechnologyforpreoperativeriskassessmentinelderlypatientsthewelcomestudy
AT piccionifederico wearablehealthtechnologyforpreoperativeriskassessmentinelderlypatientsthewelcomestudy
AT alivertiandrea wearablehealthtechnologyforpreoperativeriskassessmentinelderlypatientsthewelcomestudy
AT cecconimaurizio wearablehealthtechnologyforpreoperativeriskassessmentinelderlypatientsthewelcomestudy