Development of a composite model derived from cardiopulmonary exercise tests to predict mortality risk in patients with mild-to-moderate heart failure

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Abstract

Objective

Cardiopulmonary exercise testing (CPET) is used to predict outcome in patients with mild-to-moderate heart failure (HF). Single CPET-derived variables are often used, but we wanted to see if a composite score achieved better predictive power.

Methods

Retrospective analysis of patient records at the department of cardiology, Castle Hill Hospital, Kingston-upon-Hull. 387 patients (median (25th–75th percentile)) (age 65 (56–72) years; 79% men; LVEF 34 (31–37) %) were included. Patients underwent a symptom-limited, maximal CPET on a treadmill. During a median follow-up of 8.6±2.1 years in survivors, 107 patients died. Survival models were built and validated using a hybrid approach between the bootstrap and Cox regression. Nine CPET-derived variables were included. Z-score defined each variable’s predictive strength. Model coefficients were converted to a risk score.

Results

Four CPET-related variables were independent predictors of all-cause mortality in the survival model: the presence of exertional oscillatory ventilation (EOV), increasing slope of the relation between ventilation and carbon dioxide production (VE/VCO2 slope), decreasing oxygen uptake efficiency slope (OUES), and an increase in the lowest ventilatory equivalent for carbon dioxide (VEqCO2 nadir). Individual predictors of mortality ranged from 0.60 to 0.71 using Harrell's C-statistic, but the optimal combination of EOV+VE/VCO2 slope+OUES+VEqCO2 nadir reached 0.75. The Hull CPET risk score had a significantly higher area under the curve (0.78) when compared to the HF Survival Score (AUC=0.70; p<0.001).

Conclusions

A composite risk score using variables from CPET out-performs the traditional single variable approach in predicting outcome in patients with mild-to-moderate HF.

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