Accurate Prediction Equations for Ventilatory Thresholds in Cardiometabolic Disease When Gas Exchange Analysis is Unavailable: Development and Validation.
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BORIS DOI
Date of Publication
November 18, 2024
Publication Type
Article
Division/Institute
Author
Milani, Juliana Goulart Prata Oliveira | |
Milani, Mauricio | |
Machado, Felipe Vilaça Cavallari | |
D'Ascenzi, Flavio | |
Cavigli, Luna | |
Keytsman, Charly | |
Falter, Maarten | |
Bonnechere, Bruno | |
Meesen, Raf | |
Braga, Fabrício | |
Cipriano, Graziella França Bernardelli | |
Cornelissen, Veronique | |
Verboven, Kenneth | |
Junior, Gerson Cipriano | |
Hansen, Dominique |
Subject(s)
Series
European journal of preventive cardiology
ISSN or ISBN (if monograph)
2047-4881
Publisher
Oxford University Press
Language
English
Publisher DOI
PubMed ID
38636093
Uncontrolled Keywords
Description
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.
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.
File(s)
File | File Type | Format | Size | License | Publisher/Copright statement | Content | |
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zwae149.pdf | text | Adobe PDF | 1.62 MB | publisher | accepted |