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Article
February 1987

Interobserver Reliability in the Interpretation of Computed Tomographic Scans of Stroke Patients

Author Affiliations

From the Ben Gurion University of the Negev, Beer-Sheva, Israel (Dr Shinar); University of Minnesota, Minneapolis (Dr Gross); the Department of Neurology, Michael Reese Hospital and Medical Center, Chicago (Dr Hier); the Department of Neurology, Tufts University Medical Center, Boston (Dr Caplan); New York Neurological Institute, Columbia University, New York (Dr Mohr); the Department of Neurology, University of Maryland Hospital and Medical Center, Baltimore (Dr Price); the Department of Neurology, Boston University Medical Center (Drs Wolf and Kase); the National Cancer Institute, Bethesda, Md (Ms Fishman); the Biometry and Field Studies Branch, National Institute of Neurological and Communicative Disorders and Stroke, National Institutes of Health, Bethesda, Md (Mr Barwick); and Kunitz and Associates, Rockville, Md (Dr Kunitz).

Arch Neurol. 1987;44(2):149-155. doi:10.1001/archneur.1987.00520140021012
Abstract

• Interobserver reliability in interpretation of computed tomographic images was studied by six senior neurologists who independently evaluated on a standardized Stroke Data Bank form the brain lesions of 17 patients. The results analyzed with k statistics yielded moderate to substantial agreement on most items of interest including the stroke pathology and anatomy. In general, the levels of agreement were as high as previously reported for the diagnosis of the mechanism of the stroke, and much higher than on many stroke history items and items of neurologic examination. Excellent agreement was obtained for the detection of infarcts and intracerebral hemorrhage, and substantial agreement was obtained on whether the computed tomographic images were normal or indicative of small deep infarcts, superficial and deep infarcts, and aneurysms. The level of agreement on anatomy of the lesions was best for the frontal, parietal, and temporal lobes, putamen, cerebellum, and subarachnoid space. Implications for clinical research and diagnosis are discussed.

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