Developing and validating a model for predicting 7-day mortality of patients admitted from the emergency department: an initial alarm score by a prospective prediction model study

OBJECTIVES: To set up a prediction model for the 7-day in-hospital mortality of patients admitted from the emergency department (ED) because it is high but no appropriate initial alarm score is available. DESIGN: This is a prospective cohort study for prediction model development. SETTING: In a tertiary referred hospital in northern Taiwan. PARTICIPANTS: ED-admitted medical patients in hospitalist care wards were enrolled during May 2010 to October 2016. Two-thirds of them were randomly assigned to a derivation cohort for development of the model and cross-validation was performed in the validation cohort. PRIMARY OUTCOME MEASURED: 7-day in-hospital mortality. RESULTS: During the study period, 8649 patients were enrolled for analysis. The mean age was 71.05 years, and 51.91% were male. The most common admission diagnoses were pneumonia (36%) and urinary tract infection (20.05%). In the derivation cohort, multivariable Cox proportional hazard regression revealed that a low Barthel Index Score, triage level 1 at the ED, presence of cancer, metastasis and admission diagnoses of pneumonia and sepsis were independently associated with 7 days in-hospital mortality. Based on the probability developed from the multivariable model, the area under the receiver operating characteristic curve in the derivation group was 0.81 (0.79–0.85). The result in the validation cohort was comparable. The prediction score modified by the six independent factors had high sensitivity of 88.03% and a negative predictive value of 99.51% for a cut-off value of 4, whereas the specificity and positive predictive value were 89.61% and 10.55%, respectively, when the cut-off value was a score of 6. CONCLUSION: The 7-day in-hospital mortality in the hospitalist care ward is 2.8%. The initial alarm score could help clinicians to prioritise or exclude patients who need urgent and intensive care.