Older patients are heavy users of emergency department (ED) resources and are at high risk for short-term ED visits, often leading to adverse outcomes. We aim to elucidate the characteristics of older patients who undergo 72-h ED returns, and develop a prediction model for unfavorable outcomes to facilitate clinical practices. This retrospective observational study enrolled older patients who shortly returned to the ED of a tertiary hospital within 72 h between 2019 and 2020. The study population was divided into development and validation datasets. The primary outcome was high-risk ED returns, defined as intensive care unit admission or in-hospital mortality after ED returns. Multivariable logistic regression was performed to identify predictors of high-risk returns, and a prediction model was built accordingly. A total of 1118 encounters were enrolled in our development dataset, with a mean age of 79.4 ± 9.5 years. Through multivariable analysis, independent predictors of high-risk ED returns were identified. A simple prediction model (ReC-FLASH) was developed, demonstrating a C-statistic of 0.862 (95% CI: 0.822-0.903, P Return" triage ≤ 2, "Cancer," "Functional" bed-ridden status, "Liver" disease, complaint of "Air" hunger, "Stroke," and "Hypertension." This is the first study to propose a risk prediction model for older patients who undergo short-term ED returns. The ReC-FLASH model is straightforward and practical, facilitating early identification and management of high-risk patients, thereby improving outcomes for this vulnerable population and potentially rescuing more lives.
Chen et al. (2026) studied this question.