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  • Title: Characteristics of stroke mechanisms in patients with medullary infarction.
    Author: Lee MJ, Park YG, Kim SJ, Lee JJ, Bang OY, Kim JS.
    Journal: Eur J Neurol; 2012 Nov; 19(11):1433-9. PubMed ID: 22524973.
    Abstract:
    BACKGROUND: Few studies have focused on the mechanisms underlying medullary infarctions. Our aim in this study was to investigate stroke mechanisms in patients with medullary infarctions and to determine the clinical, radiological and laboratory characteristics of these patients with different underlying stroke etiologies. METHODS: Consecutive patients with medullary infarction were analysed. Stroke mechanisms were classified as large artery disease (LAD), cardiogenic embolism (CE), small vessel disease (SVD), arterial dissection or undetermined etiology. Clinical, radiological and laboratory factors were analysed according to the location of the lesion and stroke mechanisms. RESULTS: A total of 77 patients were enrolled in this study. Amongst them, 53 (68.8%) patients had lateral medullary infarction (LMI), 22 (28.6%) had medial medullary infarction (MMI), and the remaining 2 (2.6%) had hemimedullary infarction. In both LMI and MMI patients, LAD was the most frequently encountered stroke mechanism. Arterial dissection was the second most common cause followed by SVD and CE in patients with LMI, whereas SVD was more frequently observed (P < 0.001) and dissection and CE were less prevalent (P < 0.001 and P = 0.024, respectively) in MMI than in LMI. Regarding differences amongst stroke etiologies, patients with dissection were younger and had a significantly lower incidence of metabolic syndrome (P = 0.002 and P = 0.009, respectively) than patients with LAD and SVD. Patients in the LAD (19/34, 60%) and dissection groups (12/14, 75%) had abnormal perfusion-weighted MRI (PWI) findings, whereas all patients with SVD (9/9) had normal PWI findings (P < 0.001). CONCLUSIONS: Stroke mechanisms in medullary infarction differ between LMI and MMI. Clinical and radiological characteristics, especially PWI features, are helpful in discriminating the etiologies of stroke in these patients.
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