Pre-admission functional status impacts the performance of the APACHE IV model of mortality prediction in critically ill patients

Abstract

Background: Functional status (FS) before intensive care unit (ICU) admission is associated with short-term and long-term outcomes among critically ill patients. However, measures of FS are generally not integrated into ICU-specific mortality prediction models. Methods: This retrospective cohort study used prospectively collected data from 9638 consecutive patients admitted to a single ICU between 1 October 2005 and 30 September 2015. For each ICU admission, FS was prospectively determined and classified into three discrete categories based on performance of basic daily living activities (FS1 - fully independent; FS2 - partly dependent; FS3 - completely dependent). We prospectively calculated Acute Physiology and Chronic Health Evaluation (APACHE) IV predicted mortality percentage (APIV PM) for each admission and calculated observed-expected mortality ratios (OEMR), stratified by FS category and APIV PM. We calculated area under the receiver operator characteristic curve (AUC) for APIV PM and mortality for the entire cohort and the three FS categories. Results: Patients had a median (IQR) age of 67 (52-80) years and mean (SD) APIV PM was 18.3% (24.3%). Of these, 7714 (80.0%) were classified as FS1, 1728 (17.9%) as FS2 and 196 (2.0%) as FS3. FS1 patients were younger, had less comorbid disease, and lower APIV PM compared to FS2 and FS3. The OEMR were significantly lower for FS1 (0.67) than FS2 (0.93) or FS3 (0.90) (p < 0.0001 for both comparisons). Among patients with APIV PM 0-10%, 10-25%, 25-50% and ≥50% the OEMR for FS1 were 0.33, 0.49, 0.61 and 0.86. The AUC (95% CI) for APIV PM and mortality for FS1, FS2 and FS3 were 0.924 (0.914-0.933), 0.837 (0.816-0.858) and 0.775 (0.705-0.8456), respectively (p < 0.001 for each comparison). Multivariable analysis demonstrated that FS2 (OR 2.18 (1.84-2.57) (p < 0.0001)) and FS3 (OR 1.99 (1.34-2.96) (p = 0.0006)) were independently associated with increased risk of mortality. Conclusions: Baseline FS prior to critical illness is a strong independent predictor of mortality and impacts the relationship between observed and APIV PM in those with lower illness severity. Future iterations of mortality prediction models should integrate a baseline measure of FS to improve performance.