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ED misdiagnosis of cerebrovascular events in the era of modern neuroimaging A meta-analysis

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NEUROLOGY
卷 88, 期 15, 页码 1468-1477

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LIPPINCOTT WILLIAMS & WILKINS
DOI: 10.1212/WNL.0000000000003814

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  1. NIH [NCRR K23 RR17324, NIDCD U01 DC013778]
  2. Agency for Healthcare Research and Quality [AHRQ HS017755]

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Objective: With the emergency department (ED) being a high-risk site for diagnostic errors, we sought to estimate ED diagnostic accuracy for identifying acute cerebrovascular events. Methods: MEDLINE and Embase were searched for studies (1995-2016) reporting ED diagnostic accuracy for ischemic stroke, TIA, or subarachnoid hemorrhage (SAH). Two independent reviewers determined inclusion. We identified 1,693 unique citations, examined 214 full articles, and analyzed 23 studies. Studies were rated on risk of bias (QUADAS-2). Diagnostic data were extracted. We prospectively defined clinical presentation subgroups to compare odds of misdiagnosis. Results: Included studies reported on 15,721 patients. Studies were at low risk of bias. Overall sensitivity (91.3% [95% confidence interval (CI) 90.7-92.0]) and specificity (92.7% [91.7-93.7]) for a cerebrovascular etiology was high, but there was significant variation based on clinical presentation. Misdiagnosis was more frequent among subgroups with milder (SAH with normal vs abnormal mental state; false-negative rate 23.8% vs 4.2%, odds ratio [OR] 7.03 [4.80-10.31]), nonspecific (dizziness vs motor findings; false-negative rate 39.4% vs 4.4%, OR 14.22 [9.76-20.74]), or transient (TIA vs ischemic stroke; false discovery rate 59.7% vs 11.7%, OR 11.21 [6.66-18.89]) symptoms. Conclusions: Roughly 9% of cerebrovascular events are missed at initial ED presentation. Risk of misdiagnosis is much greater when presenting neurologic complaints are mild, nonspecific, or transient (range 24%-60%). This difference suggests that many misdiagnoses relate to symptom-specific factors. Future research should emphasize studying causes and designing error-reduction strategies in symptom-specific subgroups at greatest risk of misdiagnosis.

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