title: Predictors of time from hospital arrival to initial brain-imaging among suspected stroke patients: the North Carolina Collaborative Stroke Registry.
abstract: OBJECTIVE
  We examined patient demographic and hospital characteristics and clinical predictors of delay time from hospital arrival until CT among 20 374 patients enrolled in the North Carolina Collaborative Stroke Registry (January 2005 to April 2008).
  
  
  METHODS
  Delay time was log-transformed in linear regression analyses and dichotomized (<or=25 minutes, >25 minutes) in logistic regression analyses to correspond to a 1999 National Institute of Neurological Disorders and Stroke guideline.
  
  
  RESULTS
  In multiple linear regression analyses, prehospital delay time, mode of transport, race, gender, presumptive diagnosis, time of day of arrival, weekday versus weekend arrival, and hospital type (defined by Joint Commission Primary Stroke Center certification and teaching status) were significantly associated with CT delay. In analyses of 3549 patients arriving within 2 hours of symptom onset, time of day of arrival and weekday versus weekend arrival were no longer significant. Among patients arriving within 2 hours of symptom onset, the strongest independent predictors of meeting the National Institute of Neurological Disorders and Stroke (NINDS) guideline were arrival by emergency medical services versus other modes of transportation (odds ratio, 95% CI=2.3 [1.9, 2.8]) and a presumptive diagnosis of transient ischemic attack versus unspecified stroke type (odds ratio, 95% CI=0.4 [0.3, 0.5]).
  
  
  CONCLUSIONS
  Most patients do not arrive to the hospital in a timely manner and cannot be considered for time-dependent therapies. Among those that do, disparities exist in time to receipt of CT scan, suggesting room for improvement in hospital-level stroke systems of care.
authors.affiliation: Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27514, USA. kathryn_rose@unc.edu
authors.forename: Kathryn M
authors.initials: KM
authors.lastname: Rose
authors.forename: Wayne D
authors.initials: WD
authors.lastname: Rosamond
authors.forename: Sara L
authors.initials: SL
authors.lastname: Huston
authors.forename: Carol V
authors.initials: CV
authors.lastname: Murphy
authors.forename: Charles H
authors.initials: CH
authors.lastname: Tegeler
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D001921:Brain / Q000000981:diagnostic imaging; D002391:Catchment Area, Health; D002487:Centers for Disease Control and Prevention, U.S. / Q000458:organization & administration; D042241:Early Diagnosis; D004632:Emergency Medical Services / Q000706:statistics & numerical data; D005006:Ethnicity / Q000706:statistics & numerical data; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D009657:North Carolina / Q000453:epidemiology; D010343:Patient Admission / Q000706:statistics & numerical data; D012042:Registries / Q000706:statistics & numerical data*; D020521:Stroke / Q000175:diagnosis / Q000000981:diagnostic imaging* / Q000453:epidemiology; D013997:Time Factors; D014057:Tomography, X-Ray Computed / Q000706:statistics & numerical data*; D014187:Transportation of Patients / Q000706:statistics & numerical data; D014481:United States