Annals of African Medicine
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Year : 2014  |  Volume : 13  |  Issue : 4  |  Page : 157-160

Benin stroke score in the diagnosis of acute brain infarct: A pilot study in Senegalese Africans

1 Neurology Unit, Department of Medicine, University of Benin Teaching Hospital, Benin City, Nigerian; West African Health Organisation's 2012 PEPL Research Fellow, CHNU, Dakar, Senegal
2 Neurology Unit, Department of Medicine, University of Benin Teaching Hospital, Benin City, Nigerian
3 Department of Neurology, Centre Hospitalier National Universitaire, Dakar, Senegal

Correspondence Address:
Imarhiagbe Frank Aiwansoba
Neurology Unit, Department of Medicine, University of Benin Teaching Hospital, P.O.BOX 7184, GPO, Benin City, Nigeria

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Source of Support: None, Conflict of Interest: None

DOI: 10.4103/1596-3519.142278

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Background: The Benin stroke score (BSS) is a validated tool in the diagnosis of intracerebral hemorrhage (ICH) but not in the diagnosis of brain infarct. The aim of this report is to specifically validate the BSS in the clinical diagnosis of acute brain infarct. Materials and Methods: A total of 60 participants with a presumptive diagnosis of acute stroke in a busy tertiary neurologic care centre in Francophone West Africa were evaluated within 48 h of onset of symptoms with the BSS after basic data were obtained, before computed tomography or magnetic resonance imaging scans was used as gold standard. BSS is a three-item tool that scores age, supine diastolic blood pressure, and Glasgow coma scale with a minimum score of 0 and a maximum score of 3.5. A score of 2.5 or less is diagnostic for a brain infarct. Results: The sensitivity, specificity, positive predictive value, negative predictive value, positive and negative likelihood ratios of BSS in the diagnosis of brain infarct were 83.78%, 69.56%, 81.57%, 72.72%, 2.75, and 0.23, respectively. BSS agreed with neuroimaging in the diagnosis of all stroke subtypes significantly on kappa statistics (k = 0.538, P < 0.001) and interrater and intrarater reliability between two cadres of medical personnel in the use of BSS were significant (r = 0.9. 0.95, 0.95, P < 0.001, <0.001, <0.001), respectively. Conclusion: BSS as a simple clinical tool could be used with appreciable levels of accuracy in the clinical diagnosis of acute brain infarct where neuroimaging may not be available or immediately inaccessible, much the same way it is being used for ICH.

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