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ORIGINAL ARTICLE
Year : 2019  |  Volume : 6  |  Issue : 2  |  Page : 200-205

Assessment of brain midline shift using sonography in neurocritical patients


Department of Critical Care Medicine, Faculty of Medicine, University of Alexandria, Alexandria, Egypt

Correspondence Address:
Tamer A Helmy
Professor in Department of Critical Care Medicine, Alexandria university, Alexandria
Egypt
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/roaic.roaic_47_18

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Introduction Brain midline shift (MLS) is a life-threatening condition that requires urgent diagnosis and treatment. Aim of the work The aim of this study was to assess the brain MLS using transcranial sonography (TCS) and compare it with that of plain computed tomography (CT) in neurocritical patients. Patients and methods The study was carried out on 50 neurocritical patients admitted to the Alexandria Main University Hospitals at the Critical Care Medicine Units with a Glasgow coma score of less than 8. The ultrasound (US) MLS was measured through the temporal bone window by measuring the difference between the distance from the skull to the third ventricle on both sides as soon as possible before obtaining the brain CT. CT MLS was determined by measuring either the difference between the distance from the external bone table and the center of the third ventricle bilaterally (method 1) or the distance between the ideal midline and the septum pellucidum (method 2). Results A total of 50 neurocritical patients were included. The MLS (mean±SD) was 4.18±2.15 mm using US and 5.06±2.47 mm using CT (method 1) and 5.23±2.60 mm using CT (method 2). The Pearson’s correlation coefficient (r) between US MLS and CT MLS was 0.986 with method 1 (P<0.001) and 0.984 with method 2 (P<0.001). The area under the receiver operating characteristic curve for detecting a significant MLS with TCS was 0.990 (95% confidence interval=0.916–1.000%) in (method 1) and, using 4 mm as a cutoff, the sensitivity was 94.7%, the specificity 93.5%, and the positive predictive value was 90% and the negative predictive value was 96.7%. The area under the receiver operating characteristic curve for detecting a significant MLS with TCS was 0.988 (95% confidence interval=0.916–1.000%) (in method 2) and, with a cutoff of 4 mm, the sensitivity was 95% %, the specificity was 96.6%, and the positive predictive value was 95% and the negative predictive value was 96.7%. Conclusion This study suggests that TCS could detect MLS with reasonable accuracy in neurocritical patients and that could serve as a bedside tool to facilitate early diagnosis and treatment for patients with a significant intracranial mass effect.


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