Predicting functional outcome after stroke by modelling baseline clinical and CT variables.
BACKGROUND
we aimed to assess whether the performance of stroke outcome models comprising simple clinical variables could be improved by the addition of more complex clinical variables and information from the first computed tomography (CT) scan.


METHODS
538 consecutive acute ischaemic and haemorrhagic stroke patients were enrolled in a Stroke Outcome Study between 2001 and 2002. Independent survival (modified Rankin scale <or=2) was assessed at 6 months. Models based on clinical and radiological variables from the first assessment were developed using multivariate logistic regression analysis.


RESULTS
three models were developed (I-III). Model I included age, pre-stroke independence, arm power and a stroke severity score (area under a receiver operating characteristic curve, AUC = 0.882) but performed no better than Model II, which comprised age, pre-stroke independence, normal verbal component of the Glasgow coma score, arm power and being able to walk without assistance (AUC 0.876). Model III, including two radiological variables and clinical variables, was not statistically superior to model II (AUC 0.901, P = 0.12). Model II was externally validated in two independent datasets (AUCs of 0.773 and 0.787).


CONCLUSIONS
this study demonstrates an externally validated stroke outcome prediction model using simple clinical variables. Outcome prediction was not significantly improved with CT-derived radiological variables or more complex clinical variables.
Reid
John M
JM
Department of Neurology, Aberdeen Royal Infirmary, Foresterhill, Aberdeen AB25 2ZN, UK. johnmreid@doctors.net.uk
Gubitz
Gord J
GJ
Dai
Dingwei
D
Kydd
David
D
Eskes
Gail
G
Reidy
Yvette
Y
Christian
Christine
C
Counsell
Carl E
CE
Dennis
Martin
M
Phillips
Stephen J
SJ
D000203:Activities of Daily Living; D000208:Acute Disease; D000368:Aged; D000369:Aged, 80 and over; D019540:Area Under Curve; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D015233:Models, Statistical; D017063:Outcome Assessment, Health Care / Q000379:methods*; D011237:Predictive Value of Tests; D011379:Prognosis; D012372:ROC Curve; D012720:Severity of Illness Index; D020521:Stroke / Q000000981:diagnostic imaging* / Q000401:mortality; D000071939:Stroke Rehabilitation; D015996:Survival Rate; D014057:Tomography, X-Ray Computed