Year : 2019  |  Volume : 13  |  Issue : 5  |  Page : 654-659

Effectiveness of APACHE II and SAPS II scoring models in foreseeing the outcome of critically ill COPD patients

Chest Department, Faculty of Medicine, Assiut University, Assiut, Egypt

Correspondence Address:
MD Yousef Ahmed
Chest Department, Faculty of Medicine, Assiut University Hospital, Assiut, 71515
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Source of Support: None, Conflict of Interest: None

DOI: 10.4103/ejb.ejb_72_19

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Background Acute Physiology and Chronic Health Evaluation II (APACHE II) and Simplified Acute Physiology Score II (SAPS II) scoring systems are the two models that are greatly used by the majority of ICUs to predict clinical consequence. Objective The aim of the study was to assess the performance of APACHE II and SAPS II scoring methods in foreseeing death among critically ill chronic obstructive pulmonary disease (COPD) patients. Materials and methods This prospective research included 104 COPD patients who were admitted to the respiratory intensive care unit (RICU) at Assiut University Hospital. The patients were classified as survivors and nonsurvivors. Each scoring system was assessed for its discrimination, calibration, and overall performance. Results On the basis of the outcome of the study population, 36 (34.6%) patients were non-survivors while 68 (65.4%) patients were survivors. Both APACHE II and SAPS II scores were significantly higher in nonsurvivors. The discriminative power of both models was good as determined by the receiver operating characteristic curve. At a cutoff point greater than 20 for APACHE II and greater than 48 for SAPS II, survival or death can be predicted. The Lemeshow–Hosmer goodness-of-fit C statistics showed good performance and good calibration for both models. APACHE II score had the least Brier score and reliability but had the highest resolution. Conclusion The conclusions made were first, APACHE II and SAPS II have nearly similar performance in predicting mortality among COPD patients but with some preference for APACHE. Second, Both models have good discrimination and good calibration.

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