Objective: To develop daily prognostic estimates for individual patients treated in adult intensive care units (ICU).
Design: Prospective, multicenter, inception cohort analysis.
Setting: Forty-two ICUs at 40 U.S. hospitals with > 200 beds including 20 ICUs in tertiary care centers with major teaching activities.
Patients: A consecutive sample of 17,440 ICU admissions.
Measurements and main results: A series of multivariate equations were developed using the patient's primary reason for ICU admission, age, chronic health status, treatment before ICU admission, admission Acute Physiology Score, current day Acute Physiology Score, and change between the current and previous day's Acute Physiology Score. The equations were used to create daily risk predictions and cross-validated within the 17,440-patient sample. The single most important factor determining daily risk of hospital death during each of the initial 7 days of ICU care was the current day's Acute Physiology Score of the Acute Physiology and Chronic Health Evaluation (APACHE) III score. The admission Acute Physiology Score and change from previous to current day's Acute Physiology Score were also important, as were ICU admission diagnosis, age, chronic health status, and treatment before ICU admission. Equations incorporating these risk factors had receiver operating characteristics areas ranging from 0.9 on the first ICU day to 0.84 for patients remaining in the ICU for 7 days. The percent of cases with cross-validated predicted risks over 90% increased from 2.3% (n = 406) of cases on day 1 to 9% of all patients remaining in the ICU on ICU day 7 (n = 218). The 1,033 patients who had a daily risk estimate of > 90% during any of their initial 7 ICU days had a 90% mortality rate and represented 47% of all ICU deaths and 31% of the total number of hospital deaths.
Conclusions: Equations using initial and repeated physiologic measurements provide a high degree of explanatory power for subsequent hospital mortality rate. These daily prognostic estimates deserve evaluation for their potential role in improving the process and outcome from clinical decision-making.