Consensus or data-derived anatomic injury severity scoring?
BACKGROUND
Anatomic injury severity scores can be grouped into two classes; consensus-derived and data-derived. The former, including the Injury Severity Score (ISS), the New Injury Severity Score (NISS), and the Anatomic Profile Score (APS), are based on the severity score of the Abbreviated Injury Scale (AIS), assigned by clinical experts. The latter, including the International Classification of Disease Injury Severity Score (ICISS) and the Trauma Registry Abbreviated Injury Scale Score (TRAIS) are based on survival probabilities calculated in large trauma databases. We aimed to compare the predictive accuracy of consensus-derived and data-derived severity scores when considered alone and in combination with age and physiologic status.


METHODS
Analyses were based on 25,111 patients from the trauma registries of the four Level I trauma centers in the province of Quebec, Canada, abstracted between April 1998 and March 2005. The predictive validity of each severity score was evaluated in logistic regression models predicting hospital mortality using measures of discrimination (Area Under the Receiver Operating Characteristics curve [AUC]) and calibration (Hosmer-Lemeshow statistic [HL]).


RESULTS
Data-derived scores had consistently better predictive accuracy than consensus-derived scores in univariate models (p < 0.0001) but very little difference between scores was observed in models including information on age and physiologic status. The difference in AUC between the least accurate severity score (ISS) and the most accurate severity score (TRAIS) was 15% in anatomic-only models but fell to 2% in models including age and physiologic status.


CONCLUSIONS
Data-derived scores provide more accurate mortality prediction than consensus-derived scores do when only anatomic injury severity is considered but offer little advantage if age and physiologic status are taken into account. This may be because of the fact that data-derived scores are not an independent measure of anatomic injury severity.
Moore
Lynne
L
Trauma and Emergency Medicine Research Unit, Department of Social and Preventative Medicne, Centre Hospitalier Affilié Universitaire Québec (Enfant-Jésus Hospital), Laval University, Quebec City, Quebec, Canada. Lynne.moore@cha.quebec.qc
Lavoie
André
A
Le Sage
Natalie
N
Bergeron
Eric
E
Emond
Marcel
M
Abdous
Belkacem
B
D000293:Adolescent; D000368:Aged; D000369:Aged, 80 and over; D005260:Female; D017052:Hospital Mortality; D006801:Humans; D015601:Injury Severity Score; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D011237:Predictive Value of Tests; D011379:Prognosis; D015203:Reproducibility of Results; D015599:Trauma Severity Indices; D014947:Wounds and Injuries / Q000145:classification* / Q000401:mortality