A simple predictive model of prolonged intensive care unit stay after surgery for acquired heart valve disease.

BACKGROUND AND AIM OF THE STUDY

The study aim was to construct a simple model (the Fuwai risk score) to predict prolonged intensive care unit (ICU) stay after surgery to treat acquired heart valve disease.

METHODS

Data were collected retrospectively from 2,218 consecutive patients who underwent surgery for acquired heart valve disease. Prolonged ICU stay was defined as > or =5 days. A simple logistic score was calculated using the logistic coefficient, and the additive score by odds ratio. The Fuwai risk score, EuroSCORE and Parsonnet score were applied to predict a prolonged ICU stay and mortality. A C statistic (receiver operating characteristic curve) was used to test discrimination of the models. Calibration was assessed with a Hosmer-Lemeshow goodness-of-fit statistic.

RESULTS

The simple logistic model of the Fuwai risk score showed very good discriminatory ability (C statistic 0.76) and calibration (Hosmer-Lemeshow, p = 0.25) in predicting prolonged ICU stay, while the additive algorithm had good discriminatory ability (C statistic 0.75) but poor calibration (p <0.001). The additive algorithm greatly underestimated the risk for high-risk patients. The Fuwai risk score showed good discriminatory ability, but poor calibration in predicting mortality. Neither the EuroSCORE nor Parsonnet score was superior to the Fuwai risk score.

CONCLUSION

The logistic algorithm of the Fuwai risk score is a simple, objective, convenient and accurate scoring system which may be used to predict prolonged ICU stay after surgery to treat acquired heart valve disease.