BACKGROUND AND PURPOSE: One of the significant limitations in the evaluation and management of patients with suspected acute cerebral ischemia is the absence of a widely available, rapid, and sensitive diagnostic test. The objective of the current study was to assess whether a test using a panel of biomarkers might provide useful diagnostic information in the early evaluation of stroke by differentiating patients with cerebral ischemia from other causes of acute neurological deficit. METHODS: A total of 1146 patients presenting with neurological symptoms consistent with possible stroke were prospectively enrolled at 17 different sites. Timed blood samples were assayed for matrix metalloproteinase 9, brain natriuretic factor, d-dimer, and protein S100beta. A separate cohort of 343 patients was independently enrolled to validate the multiple biomarker model approach. RESULTS: A diagnostic tool incorporating the values of matrix metalloproteinase 9, brain natriuretic factor, d-dimer, and S-100beta into a composite score was sensitive for acute cerebral ischemia. The multivariate model demonstrated modest discriminative capabilities with an area under the receiver operating characteristic curve of 0.76 for hemorrhagic stroke and 0.69 for all stroke (likelihood test P<0.001). When the threshold for the logistic model was set at the first quartile, this resulted in a sensitivity of 86% for detecting all stroke and a sensitivity of 94% for detecting hemorrhagic stroke. Moreover, results were reproducible in a separate cohort tested on a point-of-care platform. CONCLUSIONS: These results suggest that a biomarker panel may add valuable and time-sensitive diagnostic information in the early evaluation of stroke. Such an approach is feasible on a point-of-care platform. The rapid identification of patients with suspected stroke would expand the availability of time-limited treatment strategies. Although the diagnostic accuracy of the current panel is clearly imperfect, this study demonstrates the feasibility of incorporating a biomarker based point-of-care algorithm with readily available clinical data to aid in the early evaluation and management of patients at high risk for cerebral ischemia.
BACKGROUND AND PURPOSE: One of the significant limitations in the evaluation and management of patients with suspected acute cerebral ischemia is the absence of a widely available, rapid, and sensitive diagnostic test. The objective of the current study was to assess whether a test using a panel of biomarkers might provide useful diagnostic information in the early evaluation of stroke by differentiating patients with cerebral ischemia from other causes of acute neurological deficit. METHODS: A total of 1146 patients presenting with neurological symptoms consistent with possible stroke were prospectively enrolled at 17 different sites. Timed blood samples were assayed for matrix metalloproteinase 9, brain natriuretic factor, d-dimer, and protein S100beta. A separate cohort of 343 patients was independently enrolled to validate the multiple biomarker model approach. RESULTS: A diagnostic tool incorporating the values of matrix metalloproteinase 9, brain natriuretic factor, d-dimer, and S-100beta into a composite score was sensitive for acute cerebral ischemia. The multivariate model demonstrated modest discriminative capabilities with an area under the receiver operating characteristic curve of 0.76 for hemorrhagic stroke and 0.69 for all stroke (likelihood test P<0.001). When the threshold for the logistic model was set at the first quartile, this resulted in a sensitivity of 86% for detecting all stroke and a sensitivity of 94% for detecting hemorrhagic stroke. Moreover, results were reproducible in a separate cohort tested on a point-of-care platform. CONCLUSIONS: These results suggest that a biomarker panel may add valuable and time-sensitive diagnostic information in the early evaluation of stroke. Such an approach is feasible on a point-of-care platform. The rapid identification of patients with suspected stroke would expand the availability of time-limited treatment strategies. Although the diagnostic accuracy of the current panel is clearly imperfect, this study demonstrates the feasibility of incorporating a biomarker based point-of-care algorithm with readily available clinical data to aid in the early evaluation and management of patients at high risk for cerebral ischemia.
Authors: Jeffrey L Saver; Steven Warach; Scott Janis; Joanne Odenkirchen; Kyra Becker; Oscar Benavente; Joseph Broderick; Alexander W Dromerick; Pamela Duncan; Mitchell S V Elkind; Karen Johnston; Chelsea S Kidwell; James F Meschia; Lee Schwamm Journal: Stroke Date: 2012-02-02 Impact factor: 7.914
Authors: Glen C Jickling; Huichun Xu; Boryana Stamova; Bradley P Ander; Xinhua Zhan; Yingfang Tian; Dazhi Liu; Renée J Turner; Matthew Mesias; Piero Verro; Jane Khoury; Edward C Jauch; Arthur Pancioli; Joseph P Broderick; Frank R Sharp Journal: Ann Neurol Date: 2010-11 Impact factor: 10.422
Authors: Mary F Lopez; David A Sarracino; Amol Prakash; Michael Athanas; Bryan Krastins; Taha Rezai; Jennifer N Sutton; Scott Peterman; Oksana Gvozdyak; Sherry Chou; Eng Lo; Ferdinand Buonanno; MingMing Ning Journal: Proteomics Clin Appl Date: 2012-04 Impact factor: 3.494
Authors: Timothy D Girard; Lorraine B Ware; Gordon R Bernard; Pratik P Pandharipande; Jennifer L Thompson; Ayumi K Shintani; James C Jackson; Robert S Dittus; E Wesley Ely Journal: Intensive Care Med Date: 2012-08-18 Impact factor: 17.440
Authors: Michael V DeFazio; Richard A Rammo; Jaime R Robles; Helen M Bramlett; W Dalton Dietrich; M Ross Bullock Journal: World Neurosurg Date: 2013-01-08 Impact factor: 2.104