Can factors related to mortality be used to predict the follow-up health-related quality of life (HRQoL) in cardiac surgery patients?

Background: Optimal selection of patients and choice of treatment methods in cardiac surgery calls for methods to predict outcome both in terms of mortality and health-related quality of life (HRQoL). Our target was to evaluate whether indicators predicting mortality can also be used to predict follow-up HRQoL.

Methods: Preoperative and intensive care-related data of 571 elective cardiac surgery patients treated in the Helsinki University Central Hospital were used to predict, in a stepwise (forward) binary logistic regression, the probability of being dead at six months after operation. Furthermore, Tobit regression models were employed to predict the follow-up HRQoL of patients using also treatment complications and patients' experiences of pain and restlessness during treatment as explanatory variables.

Results: The EuroSCORE, renal, respiratory and neurological complications as well as urgent sternotomy were all statistically significant predictors of mortality. By contrast, follow-up HRQoL was predicted by the baseline HRQoL, diabetes and male gender as well as experience of pain and restlessness during the ICU stay.

Conclusion: Mortality and HRQoL after cardiac surgery appear to be explained by different factors. Pain and restlessness during ICU treatment affect follow-up HRQoL in a negative manner and as potentially modifiable factors, need attention during treatment.