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Objective: To study the impact of delayed admission by more than 4 hours on the outcomes of critically ill patients., Methods: This was a retrospective observational study in which adult patients admitted directly from the emergency department to the intensive care unit were divided into two groups: Timely Admission if they were admitted within 4 hours and Delayed Admission if admission was delayed for more than 4 hours. Intensive care unit length of stay and hospital/intensive care unit mortality were compared between the groups. Propensity score matching was performed to correct for imbalances. Logistic regression analysis was used to explore delayed admission as an independent risk factor for intensive care unit mortality., Results: During the study period, 1,887 patients were admitted directly from the emergency department to the intensive care unit, with 42% being delayed admissions. Delayed patients had significantly longer intensive care unit lengths of stay and higher intensive care unit and hospital mortality. These results were persistent after propensity score matching of the groups. Delayed admission was an independent risk factor for intensive care unit mortality (OR = 2.6; 95%CI 1.9 - 3.5; p < 0.001). The association of delay and intensive care unit mortality emerged after a delay of 2 hours and was highest after a delay of 4 hours., Conclusion: Delayed admission to the intensive care unit from the emergency department is an independent risk factor for intensive care unit mortality, with the strongest association being after a delay of 4 hours.

Objective: To evaluate the hypothesis that the Modified Early Warning Score (MEWS) at the time of intensive care unit discharge is associated with readmission and to identify the MEWS that most reliably predicts intensive care unit readmission within 48 hours of discharge., Methods: This was a retrospective observational study of the MEWSs of discharged patients from the intensive care unit. We compared the demographics, severity scores, critical illness characteristics, and MEWSs of readmitted and non-readmitted patients, identified factors associated with readmission in a logistic regression model, constructed a Receiver Operating Characteristic (ROC) curve of the MEWS in predicting the probability of readmission, and presented the optimum criterion with the highest sensitivity and specificity., Results: The readmission rate was 2.6%, and the MEWS was a significant predictor of readmission, along with intensive care unit length of stay > 10 days and tracheostomy. The ROC curve of the MEWS in predicting the readmission probability had an AUC of 0.82, and a MEWS > 6 carried a sensitivity of 0.78 (95%CI 0.66 - 0.9) and specificity of 0.9 (95%CI 0.87 - 0.93)., Conclusion: The MEWS is associated with intensive care unit readmission, and a score > 6 has excellent accuracy as a prognostic predictor.