SAPS II revisited.
OBJECTIVE
To construct and validate an update of the Simplified Acute Physiology Score II (SAPS II) for the evaluation of clinical performance of Intensive Care Units (ICU).


METHODS
Retrospective analysis of prospectively collected multicenter data in 32 ICUs located in the Paris area belonging to the Cub-Rea database and participating in a performance evaluation project.


METHODS
33,471 patients treated between 1999 and 2000.


RESULTS
Two logistic regression models based on SAPS II were developed to estimate in-hospital mortality among ICU patients. The second model comprised reevaluation of original items of SAPS II and integration of the preadmission location and chronic comorbidity. Internal and external validation were performed. In the two validation samples the most complex model had better calibration than the original SAPS II for in-hospital mortality but its discrimination was not significantly higher (area under ROC curve 0.89 vs. 0.87 for SAPS II). Second-level customization and integration of new items improved uniformity of fit for various categories of patients except for diagnosis-related groups. The rank order of ICUs was modified according to the model used.


CONCLUSIONS
The overall performance of SAPS II derived models was good, even in the context of a community cohort and routinely gathered data. However, one-half the variation of outcome remains unexplained after controlling for admission characteristics, and uniformity of prediction across diagnostic subgroups was not achieved. Differences in case-mix still limit comparisons of quality of care.
Aegerter
Philippe
P
Department of Biostatistics, Hôpital Ambroise Paré, Assistance Publique Hôpitaux de Paris, Boulogne, France.
Boumendil
Ariane
A
Retbi
Aurélia
A
Minvielle
Etienne
E
Dervaux
Benoit
B
Guidet
Bertrand
B
D018806:APACHE; D000293:Adolescent; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D005260:Female; D005602:France; D017052:Hospital Mortality; D006801:Humans; D007362:Intensive Care Units / Q000706:statistics & numerical data*; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D015233:Models, Statistical; D017063:Outcome Assessment, Health Care / Q000379:methods*; D000091402:Prohibitins; D012372:ROC Curve; D012720:Severity of Illness Index