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Updated: Aug 5, 2026
Integration of Brain Tissue Saturation Monitoring in Cardiopulmonary Exercise Testing in Patients with Heart Failure
Published on: October 1, 2019
Non-invasive prediction of the first ventilatory threshold in Chinese patients with chronic heart failure for
Xiaoling Liu1, Jue Yuan1,2, Qingxuan Yang1
1Department of Rehabilitation, Tongji Hospital Affiliated to Tongji University, School of Medicine, Tongji University, Shanghai, China.
Purpose:
This study aimed to develop non-invasive prediction models for the first ventilatory threshold (VT1) in patients with chronic heart failure (CHF), to address the inaccuracy of guideline-recommended, percentage-based exercise intensity prescriptions (40%-69% peak VO2, 55%-75% peak HR) and the limited accessibility of gold-standard cardiopulmonary exercise testing (CPET).
Methods:
We analyzed 225 CHF patients who underwent standardized CPET. Using multivariate linear regression with ten-fold cross-validation, we developed prediction models for VT1 oxygen consumption (VO2) and heart rate (HR) based on readily available clinical parameters, including resting/peak exercise data, demographics, comorbidities, and medication. Model performance was evaluated using R 2, root mean squared error (RMSE), mean absolute error (MAE), intraclass correlation coefficient (ICC), and Bland-Altman analysis.
Results:
Traditional percentage-based methods were inadequate: 80% of patients achieved VO2-VT1 at 60%-90% of peak VO2, and 75.6% reached HR-VT1 at 70%-90% of peak HR. The VO2-VT1 prediction model showed strong agreement (R 2 = 0.65, RMSE = 1.42 mL/kg/min, ICC = 0.79). The HR-VT1 model demonstrated moderate-to-strong agreement (R 2 = 0.57, RMSE = 8.4 bpm, ICC = 0.71). Bland-Altman analysis indicated good agreement for both models (Within LoA: 95.1% and 95.6%).
Conclusion:
CHF patients exhibit distinct exercise intensity patterns. Our validated models enable accurate, individualized estimation of VT1 parameters using basic clinical and exercise test data, offering a practical alternative to full CPET for personalized exercise prescription in resource-limited settings.
