Risk stratification for predicting 30-day mortality of intracerebral hemorrhage.
OBJECTIVE
The aim of this study was to develop a grading scale for predicting the 30-day mortality of spontaneous intracerebral hemorrhage (ICH) using initial evaluation data.


METHODS
Univariate and multivariate logistic regression models were used to identify independent risk factors and to construct a grading scale for predicting the outcome of ICH.


METHODS
The Taichung Veterans General Hospital in Taichung, Taiwan.


METHODS
Two hundred and ninety-three patients were diagnosed with spontaneous ICH between 1 January 2006 and 31 December 2007.


METHODS
Development of the simplified ICH score (sICH score) for predicting the 30-day mortality of ICH.


METHODS
The discrimination of the prediction model was determined by measuring the accuracy, sensitivity, specificity and the area under the receiver operating characteristic curves (AUC).


RESULTS
The accuracy of the sICH score was 80.5%, the sensitivity was 82.5% and the specificity was 80.2%. The AUCs are as follows: sICH score, 0.89 (0.84-0.94); ICH score, 0.74 (0.65-0.83) and ICH-GS, 0.74 (0.65-0.83).


CONCLUSIONS
The sICH score showed best discrimination among tested models. Also, it was easier for physicians without special training in neurology or radiology to use this scale. With statistical power and ease of use, the sICH score is a very suitable model for risk stratification of spontaneous ICH.
Chuang
Ya-Ching
YC
Department of Anesthesiology, Taichung Veterans General Hospital, Taichung, Taiwan.
Chen
Yung-Ming
YM
Peng
Shih-Kuei
SK
Peng
Shih-Yen
SY
D000367:Age Factors; D000368:Aged; D000369:Aged, 80 and over; D002543:Cerebral Hemorrhage / Q000401:mortality*; D005260:Female; D006801:Humans; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D015233:Models, Statistical; D011379:Prognosis; D012372:ROC Curve; D018570:Risk Assessment; D012737:Sex Factors