title: Prediction of length of stay of first-ever ischemic stroke.
abstract: OBJECTIVE
  Accurate information about hospital resource utilization is necessary for management of healthcare service. The purpose of this study was to determine the demographic and clinical predictors of length of hospital stay (LOS) of acute care hospitalization for first-ever ischemic stroke patients.
  
  
  METHODS
  A group of 330 patients who suffered from first-ever ischemic stroke and were consecutively admitted to a medical center in southern Taiwan were followed prospectively. Because our intention was to identify the major predictors of LOS from the information available at admission, we evaluated only those factors that could be assessed at the time of admission. Univariate analysis and multiple regression analysis were used to identify the main predictors of LOS.
  
  
  RESULTS
  The median LOS was 7 days (mean, 11 days; range, 1 to 122 days). Among the prespecified demographic and clinical characteristics, National Institutes of Health Stroke Scale (NIHSS) score at admission, the quadratic term of the initial NIHSS score, modified Barthel Index score at admission, small-vessel occlusion stroke, sex, and smoking were the main explanatory factors for LOS. In particular, for each 1-point increase in the total score of NIHSS, LOS increased approximately 1 day for patients with mild or moderate (score 0 to 15 points) neurological impairments, while LOS decreased approximately 1 day for patients with severe (score >15 points) neurological impairments.
  
  
  CONCLUSIONS
  The severity of stroke, as rated by the total score on NIHSS, is an important factor that influences LOS after acute stroke hospitalization.
authors.affiliation: First Department of Neurology, Chang Gung Memorial Hospital, Kaohsiung, Taiwan. changkcc@ms24.hinet.net
authors.forename: Ku-Chou
authors.initials: KC
authors.lastname: Chang
authors.forename: Mei-Chiun
authors.initials: MC
authors.lastname: Tseng
authors.forename: Hsu-Huei
authors.initials: HH
authors.lastname: Weng
authors.forename: Yin-Hui
authors.initials: YH
authors.lastname: Lin
authors.forename: Chia-Wei
authors.initials: CW
authors.lastname: Liou
authors.forename: Teng-Yeow
authors.initials: TY
authors.lastname: Tan
mesh_terms: D000293:Adolescent; D000328:Adult; D017677:Age Distribution; D000368:Aged; D001281:Atrial Fibrillation / Q000453:epidemiology; D002545:Brain Ischemia / Q000175:diagnosis* / Q000453:epidemiology / Q000628:therapy; D015897:Comorbidity; D003710:Demography; D005260:Female; D006801:Humans; D007297:Inpatients / Q000706:statistics & numerical data*; D007902:Length of Stay / Q000191:economics / Q000706:statistics & numerical data*; D008297:Male; D008875:Middle Aged; D015999:Multivariate Analysis; D017063:Outcome Assessment, Health Care; D011237:Predictive Value of Tests; D011446:Prospective Studies; D012044:Regression Analysis; D015203:Reproducibility of Results; D012307:Risk Factors; D012720:Severity of Illness Index; D017678:Sex Distribution; D020521:Stroke / Q000175:diagnosis* / Q000453:epidemiology / Q000628:therapy; D013624:Taiwan / Q000453:epidemiology