Annual Meeting of the American Association for the Surgery of Trauma and the Japanese Association for Acute Medicine. Hawaii, USA, 1997/09/24.
Since their inception, the Injury Severity Score (ISS) and the Trauma and Injury Severity Score (TRISS) have been suggested as measures of the quality of trauma care.
In concept, they are designed to accurately assess injury severity and predict expected outcomes.
ICISS, an injury severity methodology based on International Classification of Diseases, Ninth Revision, codes, has been demonstrated to be superior to ISS and TRISS.
The purpose of the present study was to compare the ability of TRISS to ICISS as predictors of survival and other outcomes of injury (hospital length of stay and hospital charges).
It was our hypothesis that ICISS would outperform ISS and TRISS in each of these outcome predictions.
« Training » data for creation of ICISS predictions were obtained from a state hospital discharge data base. « Test » data were obtained from a state trauma registry.
ISS, TRISS, and ICISS were compared as predictors of patient survival.
They were also compared as indicators of resource utilization by assessing their ability to predict patient hospital length of stay and hospital charges.
Finally, a neural network was trained on the ICISS values and applied to the test data set in an effort to further improve predictive power.
The techniques were compared by comparing each patient's outcome as predicted by the model to the actual outcome.
Seven thousand seven hundred five patients had complete data available for analysis. (...)
Mots-clés Pascal : Traumatisme, Evaluation, Indice gravité, Echelle évaluation, Valeur prédictive, Survie, Evolution, Etude statistique, Homme
Mots-clés Pascal anglais : Trauma, Evaluation, Severity score, Evaluation scale, Predictive value, Survival, Evolution, Statistical study, Human
Notice produite par :
Inist-CNRS - Institut de l'Information Scientifique et Technique
Cote : 98-0171534
Code Inist : 002B16N. Création : 21/07/1998.