Validating a prognostic model rich single dating sites
Baseline characteristics of patients in the development cohort stratified by mortality status are shown in Table 1.
The average age of participants was 65.8 years (range: 16–105 years).
We conclude that the risk of mortality among ED patients could be accurately predicted by using common clinical signs and biochemical tests.
Medical patients admitted to Emergency Department (ED) are highly heterogeneous in terms of disease spectrum and severity.
However, after excluding patients who did not meet the inclusion criteria and patients who withdrew from the study, 1765 patients remained for the model development.
During the follow-up period, the 30-day incidence of mortality in the development cohort was 9.8% (n = 173).
There was no statistically significant difference in age between survivors and deceased.
Between 19 October 2013 and 31 March 2014, 2060 patients had been recruited for the validation cohort.However, the degree of discrimination, as measured by the area under the receiver operating characteristic curve (AUC), was between 0.70 and 0.80, suggesting that there is room for further improvement of the existing prognostic models.In developing countries, EDs are normally overcrowded, and staff constantly struggle with an overwhelming number of patients from unplanned admissions.The Bayesian Model Averaging method within the Cox’s regression model was used to identify independent risk factors for mortality.