Related Experiment Video
Updated: Feb 16, 2026

A Low Mortality Rat Model to Assess Delayed Cerebral Vasospasm After Experimental Subarachnoid Hemorrhage
Published on: January 17, 2013
Prediction of 30-day mortality in spontaneous cerebellar hemorrhage
Diaa Al Safatli1, Albrecht Guenther2, Aaron Lawson McLean1
1Department of Neurosurgery, Jena University Hospital, Friedrich Schiller University Jena, Germany.
Background:
Cerebellar hemorrhage is a potentially life-threatening condition and an understanding of the factors influencing outcome is essential for sound clinical decision-making.
Methods:
We retrospectively evaluated data from 50 consecutive patients who suffered a first spontaneous cerebellar hemorrhage (SCH) from 2005 to 2014, analysing their short-term outcomes and identifying possible clinical, radiological and therapeutic risk factors for poor prognosis and death within 30 days.
Results:
Among 50 patients with first SCH, the mean age was 72 ± 10 years. Median Glasgow Coma Scale (GCS) score on admission was 11 [interquartile range (IQR) = 7-11]. Among 50 patients, 19 patients (38%) underwent surgical hemorrhage evacuation with placement of an external ventricular drain (EVD), 12 patients (24%) received an EVD only and 19 patients (38%) were treated conservatively. The 30-day mortality rate was 36%. In multivariate analysis only the GCS score on admission was a significant predictor of 30-day mortality [odds ratio (OR) = 0.598; 95% confidence interval (CI) = 0.406-0.879; P = 0.009]. For prediction of 30-day mortality, receiver operating characteristic curve analysis confirmed that the best cut-off point was a GCS score of 10 on admission [area under the curve: 0.882, 95% CI = 0.717-1, P < 0.001].
Conclusion:
Lower GCS score on admission was associated with increased 30-day mortality and poorer short-term outcome in patients with SCH. For patients with a GCS score <10 on admission, it is important to balance the possibility of survival afforded by further therapy against the formidable risk of significant functional disability and poor quality of life.
Related Concept Videos
Spontaneity
Predicting Molecular Geometry
Prediction Intervals
However, the point estimate is most likely not the exact value of the population parameter, but close to it. After calculating point estimates, we construct interval estimates, called confidence intervals or prediction intervals. This prediction interval comprises a range of values unlike the point estimate and is a better predictor of the observed sample value, y.
Spontaneous and Induced Mutations
Sensitivity, Specificity, and Predicted Value
Sensitivity is the...
End Point Prediction: Gran Plot
For potentiometric titration, the Gran plot is created by plotting...

