Total Cerebral Blood Flow in Patients with Cardioembolic Stroke: Is It Clinically Meaningful?

Chronic hypoperfusion may hinder the washout of emboli coming from the heart and facilitate the formation of intra-cavitary thrombi. We investigated whether a decreased total cerebral blood flow (tCBF) resulted in recurrence of stroke and other vascular events in consecutive patients with cardioembolic stroke. We excluded patients with extra-cranial carotid or vertebral stenosis. The recorded tCBF was the sum of blood flow in both the carotid and vertebral extra-cranial arteries as measured with ultrasonography. Patients were followed up to assess stroke recurrence, vascular events and mortality. We also recorded demographic data, vascular risk factors, treatment data, echocardiographic variables and the C congestive heart failure history H Hypertension history A Age D Diabetes S Sex S2 Stroke/TIA/Thromboembolism history Vasc Vascular Disease history (CHA2DS2-VASc) score. We studied 79 patients (age 77.9 ± 8.4 y). Mean tCBF was 65.5 ± 15.7 mL/100 g/min. Cox regression analysis found that CHA2 DS2-VASc score and ejection fraction were associated with tCBF. After a mean follow-up of 22 ± 8.5 mo, 7.6% of patients experienced a recurrent stroke, 12.7% experienced a vascular event and 21.5% of patients died. Clinical outcomes were not predicted by tCBF.

Knowledge retrieval from PubMed abstracts and electronic medical records with the Multiple Sclerosis Ontology.

BACKGROUND: In order to retrieve useful information from scientific literature and electronic medical records (EMR) we developed an ontology specific for Multiple Sclerosis (MS). METHODS: The MS Ontology was created using scientific literature and expert review under the Protégé OWL environment. We developed a dictionary with semantic synonyms and translations to different languages for mining EMR. The MS Ontology was integrated with other ontologies and dictionaries (diseases/comorbidities, gene/protein, pathways, drug) into the text-mining tool SCAIView. We analyzed the EMRs from 624 patients with MS using the MS ontology dictionary in order to identify drug usage and comorbidities in MS. Testing competency questions and functional evaluation using F statistics further validated the usefulness of MS ontology. RESULTS: Validation of the lexicalized ontology by means of named entity recognition-based methods showed an adequate performance (F score = 0.73). The MS Ontology retrieved 80% of the genes associated with MS from scientific abstracts and identified additional pathways targeted by approved disease-modifying drugs (e.g. apoptosis pathways associated with mitoxantrone, rituximab and fingolimod). The analysis of the EMR from patients with MS identified current usage of disease modifying drugs and symptomatic therapy as well as comorbidities, which are in agreement with recent reports. CONCLUSION: The MS Ontology provides a semantic framework that is able to automatically extract information from both scientific literature and EMR from patients with MS, revealing new pathogenesis insights as well as new clinical information.