Determinants and outcomes associated with decisions to deny or to delay intensive care unit admission in Morocco

Abstract

To report determinants and outcomes associated with decisions to deny or to delay intensive care unit (ICU) admission in critically ill patients. An observational prospective study over a 6-month period. All adult patients triaged for admission to a medical ICU were included prospectively. Age, gender, reasons for requesting ICU admission, severity of underlying disease, severity of acute illness, mortality and ICU characteristics were recorded. Multinomial logistic regression analysis was used for evaluating predicting factors of refused ICU admission. ICU admission was requested for 398 patients: 110 were immediately admitted (27.8%), 142 were never admitted (35.6%), and 146 were admitted at a later time (36.6%). The reasons for refusal were: too sick to benefit (31, 10.8%), too well to benefit (55, 19.1%), unit full (117, 40.6%), and more data about the patient were needed to make a decision (85, 29.5%). Multivariate analysis revealed that late ICU admission was associated with the lack of available ICU beds (OR 1.91; 95% CI 1.46-2.50; p=0.003), cardiac disease (OR 7.77; 95% CI 2.41-25.04; p<0.001), neurological disease (OR 3.78; 95% CI 1.40-10.26; p=0.009), shock and sepsis (OR 2.55; 95% CI 1.06-6.13; p=0.03), and metabolic disease (OR 2.84; 95% CI 1.11-7.30; p=0.02). Factors for ICU refusal for never admitted patients were: severity of acute illness (OR 4.83; 95% CI 1.11-21.01; p=0.03), cardiac disease (OR 14.26; 95% CI 3.95-51.44; p<0.001), neurological disease (OR 4.05; 95% CI 1.33-12.28; p=0.01) and lack of available ICU beds (OR 6.26; 95% CI 4.14-9.46; p<0.001). Hospital mortality was 33.3% (37/110) for immediately admitted patients, 43.8% (64/146) for patients admitted later and 49.3% (70/142) for never admitted patients. Refusal of ICU admission was correlated with the severity of acute illness, lack of ICU beds and reasons for admission request. Further efforts are needed to define which patients are most likely to benefit from ICU admission and to improve the accuracy of data on ICU refusal rates.