286 Predictors and Outcomes of Older Persons Attending the Emergency Department of a Large Acute Dublin Teaching Hospital.

Background An emergency department (ED) visit is often considered a sentinel event for an older person due to elevated risks of deleterious outcomes. This prospective cohort study explored factors associated with disposition post ED index visit and unscheduled 30 day revisit. Methods Consecutive ED attendees aged ≥70 years, and Manchester Triage System 3-5, in a 6-month period, were eligible for inclusion. Participants underwent an interdisciplinary assessment by a Home FIRsT (Frailty Intervention & Response Team) member. Logistic regression analyses were performed to identify factors predictive of admission post ED index visit and unscheduled revisit. Predictive validity of frailty instruments were performed using receiver operating characteristic (ROC) curves Results 1,156 ED attendances were included - 59% were female; median age was 80 years; 66% were discharged home post index visit; 17.8% had an unscheduled ED revisit within 30 days. Age and sex did not predict hospital admission. Hospital admission post ED visit was imperfectly predicted by mild-moderate frailty: Clinical Frailty Scale 5-6 (Odds Ratio (OR) 1.83 (95% CI 1.11 – 3.04), p=0.019); 'Think Frailty' 3 (OR 1.75 (95% CI 1.07 – 2.85), p=0.025) and 4 (OR 2.32 (95% CI 1.16 – 4.63), p=0.017). Paradoxically, higher frailty scores were not predictive. Cognitive impairment (4AT 1-3) similarly predicted admission (OR 1.62 (95% 1.16 – 2.27, p=0.005), while delirium (4AT ≥4) was the strongest predictor of admission (OR 5.87 (95% CI 3.17 – 10.88, p<0.001). ROC curves of both frailty scales showed moderate 'diagnostic accuracy' for admission, but less so for unscheduled revisits. Conclusion Home FIRsT operationalised the assessment of frailty and delirium in the ED. Delirium is a strong predictor of admission post ED index visit, more than frailty status. Older persons have a high rate of 30-day unscheduled revisits; however, it is difficult to produce models from patient information available at index visit that can reliably predict unscheduled revisits. [ABSTRACT FROM AUTHOR]