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Decision tree analysis confirmed some of the results of logistic regression and challenged others. This investigation shows that there is knowledge to be gained from analyzing observational data with the aid of decision tree analysis.

Background and Purpose-The characteristics of intracerebral hemorrhage (ICH) may vary by ICH location because of differences in the distribution of underlying cerebral small vessel diseases. Therefore, we investigated the incidence, characteristics, and outcome of lobar and nonlobar ICH. Methods-In a population-based, prospective inception cohort study of ICH, we used multiple overlapping sources of case ascertainment and follow-up to identify and validate ICH diagnoses in 2010 to 2011 in an adult population of 695 335. Results-There were 128 participants with first-ever primary ICH. The overall incidence of lobar ICH was similar to nonlobar ICH (9.

Background: Information collected at baseline can be useful in predicting patient outcome after head injury. The appearance of the CT brain scan may add useful baseline information. The aim of this study was to evaluate which features on the admission CT scan might add significantly to other baseline clinical information for predicting survival in patients with head injury. Methods: Baseline CT scans were reviewed for patients with all grades of traumatic head injury in a head injury registry, in which baseline demographic and injury status and outcome at 1 year were recorded. Details from the CT scan on haemorrhage, brain swelling, and focal or diffuse damage were noted blind to clinical or outcome information and the scans classified according to the simple seven point grading (normal, mild, moderate, or severe focal injury, mild, moderate, or severe diffuse injury). An existing CT scoring system, the trauma coma databank (TCDB) classification, was also used. Logistic regression modelling was used to test the value of the CT appearance, in addition to the other baseline clinical characteristics, in predicting survival at 1 year. Results: 425 CT scans were read from patients with all severities of injury. Significant independent outcome predictors were age, Glasgow coma score (GCS), pupil reaction, presence of subarachnoid blood, and the simple grading of the overall appearance of the scan (all p<0.001). The TCDB classification was not a significant predictor of outcome. Conclusion: Age, GCS, and pupil reaction were all previously shown to be significant predictors of patient survival after head injury. A further two, easy to identify, CT scan variables are independent prognostic variables, and might help to identify patients at high risk of death at the time of admission.

Analysis 2.2. Comparison 2 Surgery vs cervical collar in cervical radiculopathy, Outcome 2 Radicular pain (current-VAS