2 research outputs found

    Is SAPS 3 better than APACHE II at predicting mortality in critically ill transplant patients?

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    OBJECTIVES: This study compared the accuracy of the Simplified Acute Physiology Score 3 with that of Acute Physiology and Chronic Health Evaluation II at predicting hospital mortality in patients from a transplant intensive care unit. METHOD: A total of 501 patients were enrolled in the study (152 liver transplants, 271 kidney transplants, 54 lung transplants, 24 kidney-pancreas transplants) between May 2006 and January 2007. The Simplified Acute Physiology Score 3 was calculated using the global equation (customized for South America) and the Acute Physiology and Chronic Health Evaluation II score; the scores were calculated within 24 hours of admission. A receiver-operating characteristic curve was generated, and the area under the receiver-operating characteristic curve was calculated to identify the patients at the greatest risk of death according to Simplified Acute Physiology Score 3 and Acute Physiology and Chronic Health Evaluation II scores. The Hosmer-Lemeshow goodness-of-fit test was used for statistically significant results and indicated a difference in performance over deciles. The standardized mortality ratio was used to estimate the overall model performance. RESULTS: The ability of both scores to predict hospital mortality was poor in the liver and renal transplant groups and average in the lung transplant group (area under the receiver-operating characteristic curve = 0.696 for Simplified Acute Physiology Score 3 and 0.670 for Acute Physiology and Chronic Health Evaluation II). The calibration of both scores was poor, even after customizing the Simplified Acute Physiology Score 3 score for South America. CONCLUSIONS: The low predictive accuracy of the Simplified Acute Physiology Score 3 and Acute Physiology and Chronic Health Evaluation II scores does not warrant the use of these scores in critically ill transplant patients

    Is SAPS 3 better than APACHE II at predicting mortality in critically ill transplant patients?

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    OBJECTIVES: This study compared the accuracy of the Simplified Acute Physiology Score 3 with that of Acute Physiology and Chronic Health Evaluation II at predicting hospital mortality in patients from a transplant intensive care unit. METHOD: A total of 501 patients were enrolled in the study (152 liver transplants, 271 kidney transplants, 54 lung transplants, 24 kidney-pancreas transplants) between May 2006 and January 2007. The Simplified Acute Physiology Score 3 was calculated using the global equation (customized for South America) and the Acute Physiology and Chronic Health Evaluation II score; the scores were calculated within 24 hours of admission. A receiver-operating characteristic curve was generated, and the area under the receiver-operating characteristic curve was calculated to identify the patients at the greatest risk of death according to Simplified Acute Physiology Score 3 and Acute Physiology and Chronic Health Evaluation II scores. The Hosmer-Lemeshow goodness-of-fit test was used for statistically significant results and indicated a difference in performance over deciles. The standardized mortality ratio was used to estimate the overall model performance. RESULTS: The ability of both scores to predict hospital mortality was poor in the liver and renal transplant groups and average in the lung transplant group (area under the receiver-operating characteristic curve = 0.696 for Simplified Acute Physiology Score 3 and 0.670 for Acute Physiology and Chronic Health Evaluation II). The calibration of both scores was poor, even after customizing the Simplified Acute Physiology Score 3 score for South America. CONCLUSIONS: The low predictive accuracy of the Simplified Acute Physiology Score 3 and Acute Physiology and Chronic Health Evaluation II scores does not warrant the use of these scores in critically ill transplant patients
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