Abstract
OBJECTIVE: Frailty is common among older adults with multimorbidity presenting to emergency departments (EDs), yet rapid, practical tools for identifying current frailty status in this setting remain limited. We aimed to identify factors associated with frailty and to develop a clinically applicable nomogram for frailty screening in the ED. METHODS: We conducted a hospital-based cross-sectional study including 486 multimorbid adults aged ≥60 years in a tertiary ED. Frailty was assessed using the 5-item FRAIL scale. Candidate variables were pre-specified and screened using the least absolute shrinkage and selection operator (LASSO) regression, and the variables selected by LASSO were then entered into a multivariable logistic regression to develop a model to identify frailty status. The model was developed using the full dataset (n = 486) and internally validated using 1,000 bootstrap resamples. Discrimination was evaluated using receiver operating characteristic (ROC) curves and the area under the curve (AUC). Calibration was assessed using calibration plots, the calibration intercept, the calibration slope, and the Brier score. Clinical utility and potential impact were assessed using decision curve analysis (DCA) and clinical impact curves (CIC). RESULTS: The prevalence of frailty was 32.3%. Six independent factors were retained in the nomogram: number of medications, fall risk, Charlson Comorbidity Index (CCI), nutritional status, anxiety, and ADL dependence. The nomogram demonstrated good discrimination (AUC = 0.877) and remained after 1,000 bootstrap resamples (AUC = 0.883). Calibration was acceptable, with intercepts of -0.028 and slopes of 0.926; Brier scores were 0.133 and 0.140 for the uncalibrated and calibrated logistic models, respectively. The Hosmer-Lemeshow test indicated good model fit (χ (2) = 8.876, p = 0.262). DCA and CIC indicated favorable clinical utility and good accuracy in identifying frailty. CONCLUSION: The nomogram may be an effective tool for assessing current frailty status among multimorbid older adults in an emergency setting. It could support routine frailty screening, facilitate communication among healthcare professionals, and inform individualized care planning.