Text mining-based measurement of precision of polysomnographic reports as basis for intervention.

Background: Text mining can be applied to automate knowledge extraction from unstructured data included in medical reports and generate quality indicators applicable for medical documentation. The primary objective of this study was to apply text mining methodology for the analysis of polysomnographic medical reports in order to quantify sources of variation - here the diagnostic precision vs. the inter-rater variability - in the work-up of sleep-disordered breathing.

Presence of pluripotent CD133+ cells correlates with malignancy of gliomas.

Background: Presence of CD133(+) cancer stem cells has been demonstrated within glioblastoma multiforme (GBM), the most malignant phenotype of gliomas (WHO grade IV). Since GBM frequently develops from low grade gliomas (WHO grade II) we assessed a possible qualitative or quantitative correlation of CD133(+) cells and glioma grade to get new insights in gliomagenesis.

Results: The amount of CD133(+) cells within the bulk tumor mass, analyzed by immunostaining and Western blotting, showed a clear quantitative correlation with glioma grade (WHO degrees II, III and IV).