Predictors and outcomes of frequent XXXX unit users.

@entity662 @entity1 @entity308 @entity453
AIM: To determine predictors of frequent @entity662 unit (CPU) users and to identify characteristics and outcomes of their CPU visits. @entity1 AND METHODS: Observational prospective case-control study. Frequent CPU user was defined by 3 or more CPU visits within the study year. A control @entity1 and a control visit were randomly selected for each case @entity1 and case visit. Demographic, clinical, and outcome variables were collected from medical record and phone interview performed in a 30-day interval. A multivariate logistic regression analysis was used to identify frequent CPU users' predictors. RESULTS: Of 1934 @entity1 presenting during the year, 80 (4.1%) met the definition for case @entity1 . They accounted for 352 (13%) of 2709 CPU visits. Sixty-seven (83.7%) case @entity1 and 71 (88.7%) control @entity1 were contacted. The final predictors were the following: Karnofsky Performance Scale of 70 or lesser (odds ratio [OR], 5.24 [95% confidence interval {CI}, 1.71-16.06]), previous hospitalization (OR, 3.76 [95% CI, 1.49-9.49]), previously known @entity453 (OR, 3.72 [95% CI, 1.32-10.52]), and symptoms of @entity308 (OR, 2.98 [95% CI, 1.14-7.78]). Case visits were more likely at night (OR, 2.41 [95% CI, 1.64- 3.52]), generated more diagnostic uncertainty (OR, 2.39 [95% CI, 1.71-3.35]), but did not increase the need of hospital admission. CONCLUSIONS: Frequent CPU user is associated with previously known @entity453 , previous hospitalization, impaired performance status, and presence of symptoms of @entity308 . They are more likely to arrive on CPU at night and generate more diagnostic uncertainty.
