DAILY PROGNOSTIC ESTIMATES FOR CRITICALLY ILL ADULTS IN INTENSIVE-CARE UNITS - RESULTS FROM A PROSPECTIVE, MULTICENTER, INCEPTION COHORT ANALYSIS

Objective: To develop daily prognostic estimates for individual patien ts treated in adult intensive care units (ICU). Design: Prospective, m ulticenter, inception cohort analysis. Setting: Forty-two ICUs at 40 U .S. hospitals with >200 beds including 20 ICUs in tertiary care center s with major teaching activities. Patients: A consecutive sample of 17 ,440 ICU admissions. Measurements and Main Results: A series of multiv ariate equations were developed using the patient's primary reason for ICU admission, age, chronic health status, treatment before ICU admis sion, admission Acute Physiology Score, current day Acute Physiology S core, and change between the current and previous day's Acute Physiolo gy Score. The equations were used to create daily risk predictions and cross-validated within the 17,440-patient sample. The single most imp ortant 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) I II score. The admission Acute Physiology Score and change from previou s to current day's Acute Physiology Score were also important, as were ICU admission diagnosis, age, chronic health status, and treatment be fore ICU admission. Equations incorporating these risk factors had rec eiver operating characteristics areas ranging from 0.9 on the first IC U day to 0.84 for patients remaining in the ICU for 7 days. The percen t of cases with cross-validated predicted risks over 90% increased fro m 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 ris k estimate of >90% during any of their initial 7 ICU days had a 90% mo rtality rate and represented 47% of all ICU deaths and 31% of the tota l 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.