BACKGROUND AND PURPOSE: The Oxfordshire Community Stroke Project (OCSP) is a common clinical stroke classification tool. We evaluated the accuracy of OCSP classification with a prospective magnetic resonance imaging (MRI) study. METHODS: Stroke/transient ischemic attack patients presenting within 48 hours of onset were included in the study (n=130). Following computed tomography scan, OCSP classification, total anterior circulation infarcts (TACI), partial anterior circulation infarcts (PACI), lacunar circulation infarcts (LACI), and posterior circulation infarcts (POCI) were performed by 3 independent examiners. All patients underwent diffusion-weighted MRI with planimetric volume measurement and classification into OCSP categories, organized by lesion location. RESULTS: Patients were clinically classified as TACI (12 patients), PACI (62 patients), LACI (38 patients), and POCI (18 patients). In 101 patients with diffusion-weighted MRI lesions, correct classification rates were: TACI (83.3%), PACI (83%), LACI (39%), and POCI (86%). OCSP had the following sensitivity (SE), specificity (SP), and positive predictive value (PPV): TACI (SE, 100%; SP, 98%; PPV, 83%), PACI (SE, 73%; SP, 78%; PPV, 83%), LACI (SE, 47%; SP, 83%; PPV, 39%), and POCI (SE, 92%; SP, 98%; PPV, 86%). Sixty-one percent of patients in the LACI group had radiographic appearances consistent with PACI, and 15% of those classified as PACI had lacunar infarcts. No differences in stroke severity existed between patients classified correctly (median National Institutes of Health Stroke Scale [NIHSS]=4; interquartile range [IQR]=7) or incorrectly (median NIHSS=3; IQR=3). Patients classified correctly had larger infarct volume (median=6.75 mL; IQR=33.2) than did those who were incorrectly classified (1.86 mL; IQR=5; P=0.008). CONCLUSIONS: OCSP classification does not permit accurate discrimination between lacunar and small-volume cortical infarcts. Differential patterns of investigation for stroke etiology should not be based solely on clinical criteria.
BACKGROUND AND PURPOSE: The Oxfordshire Community Stroke Project (OCSP) is a common clinical stroke classification tool. We evaluated the accuracy of OCSP classification with a prospective magnetic resonance imaging (MRI) study. METHODS:Stroke/transient ischemic attack patients presenting within 48 hours of onset were included in the study (n=130). Following computed tomography scan, OCSP classification, total anterior circulation infarcts (TACI), partial anterior circulation infarcts (PACI), lacunar circulation infarcts (LACI), and posterior circulation infarcts (POCI) were performed by 3 independent examiners. All patients underwent diffusion-weighted MRI with planimetric volume measurement and classification into OCSP categories, organized by lesion location. RESULTS:Patients were clinically classified as TACI (12 patients), PACI (62 patients), LACI (38 patients), and POCI (18 patients). In 101 patients with diffusion-weighted MRI lesions, correct classification rates were: TACI (83.3%), PACI (83%), LACI (39%), and POCI (86%). OCSP had the following sensitivity (SE), specificity (SP), and positive predictive value (PPV): TACI (SE, 100%; SP, 98%; PPV, 83%), PACI (SE, 73%; SP, 78%; PPV, 83%), LACI (SE, 47%; SP, 83%; PPV, 39%), and POCI (SE, 92%; SP, 98%; PPV, 86%). Sixty-one percent of patients in the LACI group had radiographic appearances consistent with PACI, and 15% of those classified as PACI had lacunar infarcts. No differences in stroke severity existed between patients classified correctly (median National Institutes of Health Stroke Scale [NIHSS]=4; interquartile range [IQR]=7) or incorrectly (median NIHSS=3; IQR=3). Patients classified correctly had larger infarct volume (median=6.75 mL; IQR=33.2) than did those who were incorrectly classified (1.86 mL; IQR=5; P=0.008). CONCLUSIONS: OCSP classification does not permit accurate discrimination between lacunar and small-volume cortical infarcts. Differential patterns of investigation for stroke etiology should not be based solely on clinical criteria.
Authors: Mindy Y Q Tan; Shaloo Singhal; Henry Ma; Ronil V Chandra; Jamie Cheong; Benjamin B Clissold; John Ly; Velandai Srikanth; Thanh G Phan Journal: Front Neurol Date: 2016-12-05 Impact factor: 4.003
Authors: Peter Sommer; Leonhard Seyfang; Alexandra Posekany; Julia Ferrari; Wilfried Lang; Elisabeth Fertl; Wolfgang Serles; Thomas Töll; Stefan Kiechl; Stefan Greisenegger Journal: J Neurol Date: 2016-11-07 Impact factor: 4.849