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The purpose of this study was to determine the statistical model that best predicted mortality from blunt trauma using a contemporary population-based database.1994-1995 New York State Trauma Registry data for patients with blunt injuries were used to predict mortality using three statistical models: (1) the original Trauma and Injury Severity Score (TRISS) model based on Major Trauma Outcome Study data, (2) a new TRISS model whose coefficients were derived using New York data, and (3) the International Classification of Disease, Ninth Revision-based Injury Severity Score (ICISS) with predicted survival values obtained from the Agency for Health Care Policy and Research's Health Care Utilization Project. The models were compared with respect to discrimination (using the C statistic) and calibration (using the Hosmer-Lemeshow [H-L] statistic). In addition, the models were tested to see how well they predicted outcomes for each of the three mechanisms of blunt injury.The ICISS model had a significantly higher C statistic (0.878) and a better H-L statistic (29.38) for predicting mortality for all adult patients with blunt injuries. The original TRISS model had very poor calibration (H-L = 687.38). None of the three models predicted mortality accurately for victims of motor vehicle crashes or victims of low falls. When separate models were developed for all motor vehicle crashes, low falls, and other blunt injuries, the ICISS and New York TRISS models both fit well, although the calibration was marginal in most cases. The ICISS model had a statistically significantly higher C statistic for other blunt injuries and for motor vehicle crashes. The New York TRISS model had better calibration for low falls.The ICISS has promise as an alternative to TRISS, but many more comparative studies need to be undertaken using updated TRISS coefficients. Models should also be developed for mechanisms of injury, not just for blunt and penetrating injuries.