Prediction of hospital mortality from admission laboratory data and patient age: a simple model.

摘要: Objective: To devise a simple clinical scoring system, using age of patients and laboratory data available on admission, to predict in-hospital mortality unselected medical surgical patients. Methods: All admitted as emergencies large teaching hospital in Liverpool the 5 months July–November 2004 were reviewed retrospectively, identifying all who died controls survived. Laboratory admission extracted form derivation dataset. Factors that predicted determined logistic regression analysis then used construct models tested receiver operating characteristic curves. Models simplified include only seven items, with minimal loss predictive efficiency. The model was second validation dataset same October November 2004. Results: included 550 1100 controls. After comparisons, 22 dummy variables given weightings discriminant create curve area under (AUC) 0.884. most variables, which can each be assigned scores 2, 3 or 4 an index predicting outcome; contained 4828 (overall 4.7%), showed this system accurately AUC 0.848, compared 0.861 containing 23 original variables. Conclusion: A predicts patients, patient small number parameters very soon after admission.