title: The Canadian Neurological Scale and the NIHSS: development and validation of a simple conversion model.
abstract: BACKGROUND
  The Canadian Neurological Scale (CNS) and the National Institutes of Health Stroke Scale (NIHSS) are among the most reliable stroke severity assessment scales. The CNS requires less extensive neurological evaluation and is quicker and simpler to administer.
  
  
  OBJECTIVE
  Our aim was to develop and validate a simple conversion model from the CNS to the NIHSS.
  
  
  METHODS
  A conversion model was developed using data from a consecutive series of acute-stroke patients who were scored using both scales. The model was then validated in an external dataset in which all patients were prospectively assessed for stroke severity using both scales by different observers which consisted of neurology residents or stroke fellows.
  
  
  RESULTS
  In all, 168 patients were included in the model development, with a median age of 73 years (20-94). Men constituted 51.8%. The median NIHSS score was 6 (0-31). The median CNS score was 8.5 (1.5-11.5). The relationship between CNS and NIHSS could be expressed as the formula: NIHSS = 23 - 2 x CNS. A cohort of 350 acute-stroke patients with similar characteristics was used for model validation. There was a highly significant positive correlation between the observed and predicted NIHSS score (r = 0.87, p < 0.001). The predicted NIHSS score was on average 0.61 higher than the observed NIHSS score (95% CI = 0.31-0.91).
  
  
  CONCLUSIONS
  The CNS can be reliably converted to the NIHSS using a simple conversion formula: NIHSS = 23 - 2 x CNS. This finding may have a practical impact by permitting reliable comparisons with NIHSS-based evaluations and simplifying the routine assessment of acute-stroke patients in more diverse settings.
authors.affiliation: Division of Neurology, Department of Medicine, Faculty of Medicine, Siriraj Hospital, Mahidol University, Bangkok, Thailand. siysl@mahidol.ac.th
authors.forename: Yongchai
authors.initials: Y
authors.lastname: Nilanont
authors.forename: Chulaluk
authors.initials: C
authors.lastname: Komoltri
authors.forename: Gustavo
authors.initials: G
authors.lastname: Saposnik
authors.forename: Robert
authors.initials: R
authors.lastname: Côté
authors.forename: Silvia
authors.initials: S
authors.lastname: Di Legge
authors.forename: Yaping
authors.initials: Y
authors.lastname: Jin
authors.forename: Naraporn
authors.initials: N
authors.lastname: Prayoonwiwat
authors.forename: Niphon
authors.initials: N
authors.lastname: Poungvarin
authors.forename: Vladimir
authors.initials: V
authors.lastname: Hachinski
mesh_terms: D000208:Acute Disease; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D016009:Chi-Square Distribution; D005260:Female; D006305:Health Status Indicators; D006801:Humans; D016014:Linear Models; D008297:Male; D008875:Middle Aged; D015233:Models, Statistical; D009316:National Institutes of Health (U.S.); D015588:Observer Variation; D009864:Ontario; D011237:Predictive Value of Tests; D011446:Prospective Studies; D015203:Reproducibility of Results; D012189:Retrospective Studies; D012720:Severity of Illness Index; D020521:Stroke / Q000175:diagnosis* / Q000503:physiopathology / Q000523:psychology; D013785:Thailand; D014481:United States; D055815:Young Adult