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

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

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BORIS DOI
10.48350/196092
Date of Publication
November 18, 2024
Publication Type
Article
Division/Institute

Rehabilitation und Sp...

Universitätsklinik fü...

Author
Milani, Juliana Goulart Prata Oliveira
Milani, Mauricio
Machado, Felipe Vilaça Cavallari
Wilhelm, Matthiasorcid-logo
Rehabilitation und Sportmedizin
Universitätsklinik für Kardiologie
Marcin, Thimoorcid-logo
Universitätsklinik für Kardiologie
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)

600 - Technology::610...

Series
European journal of preventive cardiology
ISSN or ISBN (if monograph)
2047-4881
Publisher
Oxford University Press
Language
English
Publisher DOI
10.1093/eurjpc/zwae149
PubMed ID
38636093
Uncontrolled Keywords

Cardiac Rehabilitatio...

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.
Handle
https://boris-portal.unibe.ch/handle/20.500.12422/176857
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zwae149.pdftextAdobe PDF1.62 MBpublisheracceptedOpen
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