Prediction and Outcome Analyses in Acute Neurological Diseases

Most treatments and interventions in health care are aimed at optimizing clinical outcomes. Ischemic stroke, aneurysmal subarachnoid hemorrhage (aSAH) and traumatic brain injury (TBI) are acute neurological diseases with a heterogeneous disease course that are often associated with poor functional outcomes and reduced quality of life. This stimulates measurement of clinical outcomes in terms of prognosis, variation across settings and new assessment methods.
The overall aim of this thesis is to identify patients at high risk for poor outcome after acute neurological diseases (Part II) and to enhance knowledge on outcome variation and statistical efficiency of new outcome measures (Part III).
Specific research questions are:
1. What characteristics are associated with poor outcome after acute neurological diseases?
2. What is the methodological quality of existing prognostic models in acute neurological diseases?
3. Do these models provide reliable predictions for patients in specific clinical settings?
4. What are the differences in clinical outcomes between patients with aSAH in a range of international hospitals, and can these differences be explained by variation in case-mix?
5. What is the statistical efficiency of new outcome measures for acute neurological diseases?