![]() ![]() ![]() The sensitivity was 94.4%, with a specificity of 62.7%. The laboratory admission data was predictive with an AUROC of 0.85 (95% CI: 0.85, 0.86). ![]() The Acute Illness Severity was based on the admission Manchester triage category and biochemical laboratory score these latter were based on the serum albumin, sodium, potassium, urea, red cell distribution width, and troponin status. ![]() The previously validated Acute Illness Severity model was then transposed to a Kattan-style nomogram with a Stata user-written program. For emergency medical admissions (96,305 episodes in 50,612 patients) between 20, the relationship between 30-day in-hospital mortality and admission laboratory data was determined using logistic regression. We describe a nomogram to explain an Acute Illness Severity model, derived from emergency room triage and admission laboratory data, to predict 30-day in-hospital survival following an emergency medical admission. ![]()
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