Prognostic value of the post-training oxygen uptake efficiency slope in patients with coronary artery disease

    loading  Checking for direct PDF access through Ovid

Abstract

Background

Peak oxygen uptake is an independent predictor of mortality in patients with coronary artery disease (CAD). However, patients with CAD are not always capable of reaching peak effort, and therefore submaximal gas exchange variables such as the oxygen uptake efficiency slope (OUES) have been introduced. Baseline exercise capacity as expressed by OUES provides prognostic information and this parameter responds to training. Therefore, we aimed to assess the prognostic value of post-training OUES in patients with CAD.

Methods

We included 960 patients with CAD (age 60.6 ± 9.5 years; 853 males) who completed a cardiac rehabilitation program between 2000 and 2011. The OUES was calculated before and after cardiac rehabilitation and information on mortality was obtained. The relationships of post-training OUES with all-cause and cardiovascular (CV) mortality was assessed by Cox proportional hazards regression analyses. Receiver operator characteristic curve analysis was performed in order to obtain the optimal cut-off value.

Results

During 7.37 ± 3.20 years of follow-up (range: 0.45-13.75 years), 108 patients died, among whom 47 died due to CV reasons. The post-training OUES was related to all-cause (hazard ratio: 0.50, p < 0.001) and CV (hazard ratio: 0.40, p < 0.001) mortality. When significant covariates, including baseline OUES, were entered into the Cox regression analysis, post-training OUES remained related to all-cause and CV mortality (hazard ratio: 0.40, p < 0.01 and 0.26, p < 0.01, respectively). In addition, the change in OUES due to exercise training was positively related to mortality (hazard ratio: 0.49, p < 0.01).

Conclusion

Post-training OUES has stronger prognostic value compared to baseline OUES. The lack of improvement in exercise capacity expressed by OUES after an exercise training program relates to a worse prognosis and can help distinguish patients with favorable and unfavorable prognoses.

Related Topics

    loading  Loading Related Articles