Accurate Prediction Equations for Ventilatory Thresholds in Cardiometabolic Disease When Gas Exchange Analysis is Unavailable: Development and Validation.

Autor:	Milani JGPO; Rehabilitation Research Center (REVAL), Faculty of Rehabilitation Sciences, Hasselt University, Hasselt, Belgium.; Graduate Programme in Health Sciences and Technologies, University of Brasilia (UnB), Brasilia, DF, Brazil., Milani M; Rehabilitation Research Center (REVAL), Faculty of Rehabilitation Sciences, Hasselt University, Hasselt, Belgium.; Graduate Programme in Health Sciences and Technologies, University of Brasilia (UnB), Brasilia, DF, Brazil.; Heart Centre Hasselt, Jessa Hospital, Hasselt, Belgium., Machado FVC; Rehabilitation Research Center (REVAL), Faculty of Rehabilitation Sciences, Hasselt University, Hasselt, Belgium.; Heart Centre Hasselt, Jessa Hospital, Hasselt, Belgium.; Biomedical Research Institute (BIOMED), Faculty of Medicine and Life Sciences, Hasselt, Belgium., Wilhelm M; Centre for Rehabilitation & Sports Medicine, Inselspital, Bern University Hospital, University of Bern, Switzerland., Marcin T; Centre for Rehabilitation & Sports Medicine, Inselspital, Bern University Hospital, University of Bern, Switzerland., D'Ascenzi F; Department of Medical Biotechnologies, Sports Cardiology and Rehab Unit, University of Siena, Italy., Cavigli L; Department of Medical Biotechnologies, Sports Cardiology and Rehab Unit, University of Siena, Italy., Keytsman C; Heart Centre Hasselt, Jessa Hospital, Hasselt, Belgium., Falter M; Heart Centre Hasselt, Jessa Hospital, Hasselt, Belgium.; Faculty of Medicine and Life Sciences, Hasselt University, Hasselt, Belgium.; Department of Cardiology, Faculty of Medicine, KU Leuven, Leuven, Belgium., Bonnechere B; Rehabilitation Research Center (REVAL), Faculty of Rehabilitation Sciences, Hasselt University, Hasselt, Belgium.; Technology-Supported and Data-Driven Rehabilitation, Data Sciences Institute, University of Hasselt, Diepenbeek, Belgium.; Centre of expertise in Care Innovation, Department of PXL - Healthcare, PXL University of Applied Sciences and Arts, Hasselt, Belgium., Meesen R; Rehabilitation Research Center (REVAL), Faculty of Rehabilitation Sciences, Hasselt University, Hasselt, Belgium., Braga F; Laboratório de Performance Humana, Rio de Janeiro, Brazil.; State University of Rio de Janeiro, Rio de Janeiro, Brazil., Cipriano GFB; Graduate Programme in Health Sciences and Technologies, University of Brasilia (UnB), Brasilia, DF, Brazil.; Rehabilitation Sciences Programme, University of Brasilia (UnB), Brasilia, DF, Brazil., Cornelissen V; Department of Rehabilitation Sciences, KU Leuven, Leuven, Belgium., Verboven K; Rehabilitation Research Center (REVAL), Faculty of Rehabilitation Sciences, Hasselt University, Hasselt, Belgium.; Biomedical Research Institute (BIOMED), Faculty of Medicine and Life Sciences, Hasselt, Belgium., Junior GC; Graduate Programme in Health Sciences and Technologies, University of Brasilia (UnB), Brasilia, DF, Brazil.; Graduate Program in Human Movement and Rehabilitation of Evangelical (PPGMHR), UniEVANGÉLICA, Anápolis, Brazil., Hansen D; Rehabilitation Research Center (REVAL), Faculty of Rehabilitation Sciences, Hasselt University, Hasselt, Belgium.; Heart Centre Hasselt, Jessa Hospital, Hasselt, Belgium.; Biomedical Research Institute (BIOMED), Faculty of Medicine and Life Sciences, Hasselt, Belgium.
Jazyk:	angličtina
Zdroj:	European journal of preventive cardiology [Eur J Prev Cardiol] 2024 Apr 18. Date of Electronic Publication: 2024 Apr 18.
DOI:	10.1093/eurjpc/zwae149
Abstrakt:	Aims: To develop and validate equations predicting heart rate (HR) at the first and second ventilatory thresholds (VTs) and an optimized range-adjusted prescription for patients with cardiometabolic disease (CMD). To compare their performance against guideline-based exercise intensity domains. Methods: Cross-sectional study involving 2,868 CMD patients from nine countries. HR predictive equations for first and second VTs (VT1, VT2) were developed using multivariate linear regression with 975 cycle-ergometer cardiopulmonary exercise tests (CPET). 'Adjusted' percentages of peak HR (%HRpeak) and HR reserve (%HRR) were derived from this group. External validation with 1,893 CPET (cycle-ergometer or treadmill) assessed accuracy, agreement, and reliability against guideline-based %HRpeak and %HRR prescriptions using mean absolute percentage error (MAPE), Bland-Altman analyses, intraclass correlation coefficients (ICC). Results: HR predictive equations (R²: 0.77 VT1, 0.88 VT2) and adjusted %HRR (VT1: 42%, VT2: 77%) were developed. External validation demonstrated superiority over widely used guideline-directed intensity domains for %HRpeak and %HRR. The new methods showed consistent performance across both VTs with lower MAPE (VT1: 7.1%, VT2: 5.0%), 'good' ICC for VT1 (0.81, 0.82) and 'excellent' for VT2 (0.93). Guideline-based exercise intensity domains had higher MAPE (VT1: 6.8%-21.3%, VT2: 5.1%-16.7%), 'poor' to 'good' ICC for VT1, and 'poor' to 'excellent' for VT2, indicating inconsistencies related to specific VTs across guidelines. Conclusion: Developed and validated HR predictive equations and the optimized %HRR for CMD patients for determining VT1 and VT2 outperformed the guideline-based exercise intensity domains and showed ergometer interchangeability. They offer a superior alternative for prescribing moderate intensity exercise when CPET is unavailable. (© The Author(s) 2024. Published by Oxford University Press on behalf of the European Society of Cardiology. All rights reserved. For commercial re-use, please contact reprints@oup.com for reprints and translation rights for reprints. All other permissions can be obtained through our RightsLink service via the Permissions link on the article page on our site—for further information please contact journals.permissions@oup.com.)
Databáze:	MEDLINE
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