Ability of physiological parameters versus clinical categories to predict mortality on admission to an internal medicine ward.
BACKGROUND
The prediction of mortality in internal medicine departments may help in taking diagnostic and therapeutic decisions. We analyzed the usefulness of two mortality prediction models, one physiological and the other mainly clinical, and determined whether one approach is better than the other to predict mortality at admission.


METHODS
This is a prospective observational cohort study in patients admitted to an acute internal medicine ward in a tertiary care, urban, university teaching hospital in Spain. Five hundred consecutive patients either electively admitted or coming from the emergency department from May to December 2008 were analyzed. Medical history, physical examination and routine clinical laboratory tests were performed on admission. At discharge, diagnosis and dead or survived status was recorded. Logistic regression analyses were used to test variables that emerged as independent predictors of mortality. The area under the curve was used to determine which model best predicted mortality.


RESULTS
Mortality in the ward was 13.0%. Age, chronic respiratory failure, creatinine, mean arterial pressure, respiratory rate and Glasgow coma scale independently predicted mortality. ROC curves showed that the physiological model was superior to the clinical model, but differences were not statistically significant. The predictive capacity improved when the two models were combined but the improvement was not significant.


CONCLUSIONS
Both models are satisfactory predictors of in-hospital mortality for management purposes but neither proved to be a useful tool for individual predictions. Complementary approaches need to be considered.
Francia
Esther
E
Internal Medicine Department, Hospital de Santa Creu i Sant Pau. Universitat Autònoma de Barcelona, Barcelona, Spain.
Torres
Olga
O
Laiz
Ana
A
Ruiz
Domingo
D
Gich
Ignasi
I
Casademont
Jordi
J
D000368:Aged; D005260:Female; D005544:Forecasting; D017052:Hospital Mortality; D006757:Hospital Units; D006801:Humans; D007388:Internal Medicine; D008297:Male; D015233:Models, Statistical; D008991:Monitoring, Physiologic; D010343:Patient Admission; D010361:Patients / Q000145:classification; D011379:Prognosis; D011446:Prospective Studies