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Anaesth Intensive Care · Sep 2009
Randomized Controlled Trial Comparative StudyThe performance of customised APACHE II and SAPS II in predicting mortality of mixed critically ill patients in a Thai medical intensive care unit.
- B Khwannimit and R Bhurayanontachai.
- Medical Intensive Care Unit, Songklanagarind Hospital, Faculty of Medicine, Prince of Songkla University, Hat Yai, Songkhla, Thailand. kbordin@medicine.psu.ac.th
- Anaesth Intensive Care. 2009 Sep 1;37(5):784-90.
AbstractThe aim of this study was to evaluate and compare the performance of customised Acute Physiology and Chronic Health Evaluation HII (APACHE II) and Simplified Acute Physiology Score HII (SAPS II) in predicting hospital mortality of mixed critically ill Thai patients in a medical intensive care unit. A prospective cohort study was conducted over a four-year period. The subjects were randomly divided into calibration and validation groups. Logistic regression analysis was used for customisation. The performance of the scores was evaluated by the discrimination, calibration and overall fit in the overall group and across subgroups in the validation group. Two thousand and forty consecutive intensive care unit admissions during the study period were split into two groups. Both customised models showed excellent discrimination. The area under the receiver operating characteristic curve of the customised APACHE II was greater than the customised SAPS II (0.925 and 0.892, P < 0.001). Hosmer-Lemeshow goodness-of-fit showed good calibration for the customised APACHE II in overall populations and various subgroups but insufficient calibration for the customised SAPS II. The customised SAPS II showed good calibration in only the younger, postoperative and sepsis patients subgroups. The overall performance of the customised APACHE II was better than the customised SAPS II (Brier score 0.089 and 0.109, respectively). Our results indicate that the customised APACHE II shows better performance than the customised SAPS II in predicting hospital mortality and could be used to predict mortality and quality assessment in our unit or other intensive care units with a similar case mix.
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