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(Stroke. 2004;35:57.)
© 2004 American Heart Association, Inc.
Original Contributions |
From the Department of Medicine (Neurology) (J.R.L., R.B., D.T.L.), Multidisciplinary Neuroprotection Laboratories (J.R.L., D.T.L.), and Department of Anesthesiology (W.D.W., H.P.G., M.F.N., D.T.L.), Duke University Medical Center, Durham, NC.
Correspondence to Daniel T. Laskowitz, MD, Box 2900, Duke University Medical Center, Durham, NC 27710. E-mail danl{at}neuro.duke.edu
Background and Purpose The absence of a widely available and sensitive diagnostic test for acute cerebral ischemia remains a significant limitation in the diagnosis and management of stroke. The objective of this study was to examine the feasibility of developing a diagnostic panel of blood-borne biochemical markers of cerebral ischemia.
Methods Serial blood samples were obtained from patients (n=65 with suspected ischemic stroke, n=157 control subjects) presenting to an academic medical center emergency department. We analyzed 26 blood-borne markers believed to play a role in the ischemic cascade and created a 3-variable logistic regression model to predict the clinical diagnosis of stroke, defined as persistent neurological symptoms of cerebral ischemia lasting >24 hours.
Results Of the 26 blood-borne markers analyzed, univariate logistic analysis revealed that 4 were highly correlated with stroke (P<0.001): a marker of glial activation (S100ß), 2 markers of inflammation (matrix metalloproteinase-9 and vascular cell adhesion molecule), and 1 marker of thrombosis (von Willebrand factor). When the outcome level was set to a cutoff of P=0.1, our logistic model provided a sensitivity and specificity of 90% for predicting stroke.
Conclusions A panel of blood-borne biochemical markers may be helpful in identifying patients with acute cerebral ischemia who could benefit from urgent care. Such a test may also be helpful in identifying stroke patients in the prehospital setting so that they could be fast-tracked to an institution equipped to care for patients with acute stroke.
Key Words: diagnosis stroke stroke assessment
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