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Neurological research · Jul 2015
Comparative Study Observational StudyBiochemical neuromonitoring of poor-grade aneurysmal subarachnoid hemorrhage: comparative analysis of metabolic events detected by cerebral microdialysis and by retrograde jugular vein catheterization.
- Yannick Tholance, Gleicy Keli Barcelos, Frédéric Dailler, Bernard Renaud, Stéphane Marinesco, and Armand Perret-Liaudet.
- Neurol. Res. 2015 Jul 1; 37 (7): 578-87.
ObjectivesIn severe aneurysmal subarachnoid hemorrhage (aSAH), pathological changes in cerebral energy metabolism can be detected either by local measurements using cerebral microdialysis (cMD) together with brain tissue oxygen probe or by global measurements of arterio-jugular difference performed with retrograde jugular vein catheter. Our main objective was to compare the two methods of detection and assess whether combining biomarkers from both procedures could improve outcome prediction, which has never been studied before.MethodsThis study included 400 sets of paired arterial and jugular venous samples and 3138 brain microdialyzates obtained from 18 poor-grade aSAH patients. Using Glasgow outcome scale (GOS), neurochemical data from unfavorable (GOS 1-3) and favorable (GOS 4-5) outcome groups were compared.ResultsThe lactate/pyruvate ratio was found as the most sensitive marker for predicting unfavorable outcome (90%), although not specific. In contrast, hypoxic lactate events and those of metabolic ratio (MR) < 3.44, most frequently observed in the unfavorable outcome group than in the favorable one (13.9 vs 0.9% and 33.3 vs 3.75% respectively), were shown to be more specific biomarkers (86%) to predict unfavorable outcome, but less sensitive ( < 70%). The combination of these three biomarkers improved the accuracy of outcome prediction (sensitivity 90% and specificity 71%).DiscussionBoth retrograde jugular venous catheterization (RJVC) and cMD contribute to monitor poor-grade aSAH patients. In this preliminary study, we show that these two techniques are complementary and their combination increases the accuracy of outcome prediction.
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