American journal of translational research · 2025
Predictive value of cardiopulmonary exercise test parameters for atrial fibrillation risk in hypertrophic cardiomyopathy patients.
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Wang Ling, Liu Lili, Guo Langtao
Аннотация
OBJECTIVE: To investigate the relationship between cardiopulmonary exercise test (CPET) parameters and the occurrence of atrial fibrillation (AF) in patients with hypertrophic cardiomyopathy (HCM).
METHODS: A retrospective study was conducted on 160 HCM patients hospitalized at Quanzhou First Hospital Affiliated to Fujian Medical University from June 2020 to December 2023. Patients were divided into AF (n=62) and non-AF (n=98) groups. Univariate analysis and logistic regression were used to compare demographic and CPET parameters between groups. A nomogram model was developed to predict AF risk.
RESULTS: AF prevalence was 38.75%. Peak Oxygen Uptake per kilogram (Peak VO2/kg), Metabolic Equivalent of Task (METs), and Oxygen Uptake at Anaerobic threshold per kilogram (VO2/kg AT) were lower in the AF group compared to the non-AF group, while Ventilation to Carbon Dioxide Production Slope (VE/VCO2 slope) was higher (all P<0.05). Pearson correlation analysis showed a significant negative correlation between Peak VO2/kg and New York Heart Association (NYHA) classification (r=-0.231, P=0.003). Logistic regression identified NYHA classification, smoking history, and VE/VCO2 slope as risk factors for AF, while Peak VO2/kg, METs, and VO2/kg AT were protective factors (P<0.05). The nomogram model had an area under curve (AUC) of 0.867 (0.808-0.925), demonstrating good calibration and clinical utility.
CONCLUSION: CPET parameters, combined with clinical indicators, can effectively predict AF risk in HCM patients. The nomogram model provides a valuable tool for clinical risk assessment.
METHODS: A retrospective study was conducted on 160 HCM patients hospitalized at Quanzhou First Hospital Affiliated to Fujian Medical University from June 2020 to December 2023. Patients were divided into AF (n=62) and non-AF (n=98) groups. Univariate analysis and logistic regression were used to compare demographic and CPET parameters between groups. A nomogram model was developed to predict AF risk.
RESULTS: AF prevalence was 38.75%. Peak Oxygen Uptake per kilogram (Peak VO2/kg), Metabolic Equivalent of Task (METs), and Oxygen Uptake at Anaerobic threshold per kilogram (VO2/kg AT) were lower in the AF group compared to the non-AF group, while Ventilation to Carbon Dioxide Production Slope (VE/VCO2 slope) was higher (all P<0.05). Pearson correlation analysis showed a significant negative correlation between Peak VO2/kg and New York Heart Association (NYHA) classification (r=-0.231, P=0.003). Logistic regression identified NYHA classification, smoking history, and VE/VCO2 slope as risk factors for AF, while Peak VO2/kg, METs, and VO2/kg AT were protective factors (P<0.05). The nomogram model had an area under curve (AUC) of 0.867 (0.808-0.925), demonstrating good calibration and clinical utility.
CONCLUSION: CPET parameters, combined with clinical indicators, can effectively predict AF risk in HCM patients. The nomogram model provides a valuable tool for clinical risk assessment.