Abstract

To analyze the utilization of intensive care unit (ICU) days in a Canadian medical-surgical ICU and to identify ICU patients with prolonged ICU length of stay (LOS). Prospective descriptive study. A Canadian tertiary care medical-surgical ICU. Consecutive patients admitted to an adult medical-surgical ICU. Neurosurgical, cardiac surgical, and coronary care unit patients were excluded. For each ICU admission, patient demographics, diagnosis, Acute Physiology and Chronic Health Evaluation II (APACHE II) score, ICU LOS, and hospital mortality were collected. The patients' risk of death was calculated using the APACHE II equation. Admissions were stratified by ICU LOS into four groups: 1 to 2, 3 to 6, 7 to 13, and > or = 14 days. Among the four LOS groups, the number of ICU days and observed and predicted death rates were compared. Admissions were also stratified by risk of death into five probability range quintiles. Among the five risk groups, ICU LOS was compared between survivors and nonsurvivors. A total of 1,960 admissions utilized 9,298 ICU days. ICU LOS (mean +/- SEM) was 4.74 +/- 0.2 (median, 2; range, 1 to 178) days. Short-stay patients (ICU LOS < or = 2 days) accounted for 60.3% of total admissions but consumed only 16.4% of total ICU days. Long-stay patients (ICU LOS > or = 14 days) accounted for 7.3% of total admissions but consumed 43.5% of total ICU days. Among the long-stay patients, the most common reasons for admission were pneumonia, multiple trauma, neuromuscular weakness, and septic shock. The mortality for long-stay patients approached 50%. When analyzed by patients' mortality risks, those with a risk of death >0.8 (predicted to die) or <0.2 (predicted to live) whose outcomes were opposite to that predicted had twice the ICU LOS compared with patients whose outcomes were consistent with prediction. In a Canadian medical-surgical ICU, patients with ICU LOS > or = 14 days accounted for 7.3% of total admissions but consumed 43.5% of total ICU days. Identification of patients with prolonged ICU LOS who would ultimately die in the ICU may lead to earlier withdrawal of therapy in these patients, resulting in a substantial reduction in suffering and cost savings. In our study population, outcome prediction using the APACHE II equation did not provide sufficient power to accurately discriminate between nonsurvivors and survivors.

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