Abstract

Abstract Introduction Any Frailty Index (FI) measures overall health. The FI-Lab employs common laboratory data and clinical measures to do so. Objective To examine how an FI-lab constructed from vital signs, laboratory tests, and electrocardiographic data is associated with in-patient admission and time to death. FI-Lab performance was compared with an FI from a Comprehensive Geriatric Assessment (FI-CGA), the Clinical Frailty Scale (CFS), and the Canadian Triage Acuity Scale (CTAS). Method Participants were Emergency Department (ED) patients aged 65+ years referred to Internal Medicine, staffed by a geriatrician (KR). Fifty-seven FI-Lab variables were binarized (0 = no deficit; 1 = deficit) using standard normal ranges. Each FI was calculated as the fraction of items present as deficits. Age- and sex-adjusted Cox proportional hazard and logistic regression models were used to assess relationships with all-cause mortality, and in-patient admission, respectively. Results Of 808 patients, an FI-Lab was calculable in 807. Median age was 81 years (IQR:13); 55.7% were female. FI-Lab values ranged from 0.05–0.78 (Mean: 0.51; Standard deviation (SD) 0.10). Females (0.50±0.11) had lower FI-Lab scores than males (Mean: 0.52±0.09; p=0.003). At 30 days, each 0.01 FI-Lab unit increase showed higher mortality Hazard Rate (HR) (95% Confidence Interval (CI):1.04 (1.02–1.06) and inpatient admission risk: Odds ratio (OR) 1.02 (1.00–1.03), as did the FI-CGA (1.04; 1.02-1.04) and CTAS (1.46; 1.02-2.10). Similar results held for inpatient admission, save for CTAS (0.95; 0.54-1.64). By two years, only the FI-lab and CFS significantly predicted mortality risk. Conclusion FI-Lab scores were associated with higher mortality rates and in-patient admission risk in older ED patients referred to Medicine. In acute care, the FI-Lab appears to integrate baseline frailty with illness severity. As such data often are routinely available, the FI-Lab might be an additional passive measure of frailty-related risk, potentially available in real time.

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