title: Soft tissue infections and emergency department disposition: predicting the need for inpatient admission.
abstract: OBJECTIVE
  Little empiric evidence exists to guide emergency department (ED) disposition of patients presenting with soft tissue infections. This study's objective was to generate a clinical decision rule to predict the need for greater than 24-hour hospital admission for patients presenting to the ED with soft tissue infection.
  
  
  METHODS
  This was a retrospective cohort study of consecutive patients presenting to a tertiary care hospital ED with diagnosis of nonfacial soft tissue infection. Standardized chart review was used to collect 29 clinical variables. The primary outcome was >24-hour hospital admission (either general admission or ED observation unit), regardless of initial disposition. Patients initially discharged home and later admitted for more than 24 hours were included in the outcome. Data were analyzed using classification and regression tree (CART) analysis and multivariable logistic regression.
  
  
  RESULTS
  A total of 846 patients presented to the ED with nonfacial soft tissue infection. After merging duplicate records, 674 patients remained, of which 81 (12%) required longer than 24-hour admission. Using CART, the strongest predictors of >24-hour admission were patient temperature at ED presentation and mechanism of infection. In the multivariable logistic regression model, initial patient temperature (odds ratio [OR] for each degree over 37 degrees C = 2.91, 95% confidence interval [CI] = 1.65 to 5.12) and history of fever (OR = 3.02, 95% CI = 1.41 to 6.43) remained the strongest predictors of hospital admission. Despite these findings, there was no combination of factors that reliably identified more than 90% of target patients.
  
  
  CONCLUSIONS
  Although we were unable to generate a high-sensitivity decision rule to identify ED patients with soft tissue infection requiring >24-hour admission, the presence of a fever (either by initial ED vital signs or by history) was the strongest predictor of need for >24-hour hospital stay. These findings may help guide disposition of patients presenting to the ED with nonfacial soft tissue infections.
authors.affiliation: From the Center for Policy and Research in Emergency Medicine, Department of Emergency Medicine, Oregon Health & Science University (AS, MAB, OJM, CDN), Portland, OR; and the Southwest Washington Medical Center (BJ), Vancouver, WA.
authors.forename: Alfredo
authors.initials: A
authors.lastname: Sabbaj
authors.affiliation: From the Center for Policy and Research in Emergency Medicine, Department of Emergency Medicine, Oregon Health & Science University (AS, MAB, OJM, CDN), Portland, OR; and the Southwest Washington Medical Center (BJ), Vancouver, WA.
authors.forename: Brett
authors.initials: B
authors.lastname: Jensen
authors.affiliation: From the Center for Policy and Research in Emergency Medicine, Department of Emergency Medicine, Oregon Health & Science University (AS, MAB, OJM, CDN), Portland, OR; and the Southwest Washington Medical Center (BJ), Vancouver, WA.
authors.forename: Mary Ann
authors.initials: MA
authors.lastname: Browning
authors.affiliation: From the Center for Policy and Research in Emergency Medicine, Department of Emergency Medicine, Oregon Health & Science University (AS, MAB, OJM, CDN), Portland, OR; and the Southwest Washington Medical Center (BJ), Vancouver, WA.
authors.forename: O John
authors.initials: OJ
authors.lastname: Ma
authors.affiliation: From the Center for Policy and Research in Emergency Medicine, Department of Emergency Medicine, Oregon Health & Science University (AS, MAB, OJM, CDN), Portland, OR; and the Southwest Washington Medical Center (BJ), Vancouver, WA.
authors.forename: Craig D
authors.initials: CD
authors.lastname: Newgard
mesh_terms: D015331:Cohort Studies; D015897:Comorbidity; D003661:Decision Support Techniques; D004636:Emergency Service, Hospital; D005334:Fever / Q000453:epidemiology; D006801:Humans; D007902:Length of Stay / Q000706:statistics & numerical data; D016015:Logistic Models; D015999:Multivariate Analysis; D020380:Needs Assessment / Q000706:statistics & numerical data*; D016017:Odds Ratio; D009922:Oregon / Q000453:epidemiology; D010343:Patient Admission / Q000706:statistics & numerical data*; D012189:Retrospective Studies; D012680:Sensitivity and Specificity; D018461:Soft Tissue Infections / Q000453:epidemiology / Q000628:therapy*