title: Population-based study of blood biomarkers in prediction of subacute recurrent stroke.
abstract: OBJECTIVE
  Risk of recurrent stroke is high in the first few weeks after transient ischemic attack or stroke and clinical risk prediction tools have only limited accuracy, particularly after the hyperacute phase. Previous studies of the predictive value of biomarkers have been small, been done in selected populations, and have not concentrated on the acute phase or on intensively treated populations. We aimed to determine the predictive value of a panel of blood biomarkers in intensively treated patients early after transient ischemic attack and stroke.
  
  
  METHODS
  We studied 14 blood biomarkers related to inflammation, thrombosis, atherogenesis, and cardiac or neuronal cell damage in early transient ischemic attack or ischemic stroke in a population-based study (Oxford Vascular Study). Biomarker levels were related to 90-day risk of recurrent stroke as hazard ratio (95% confidence interval) per decile increase, adjusted for age and sex.
  
  
  RESULTS
  Among 1292 eligible patients, there were 53 recurrent ischemic strokes within 90 days. There were moderate correlations (r=0.40-0.61; P<0.0001) between the inflammatory biomarkers and between the cell damage and thrombotic subsets. Associations with risk of early recurrent stroke were weak, with significant associations limited to interleukin-6 (adjusted hazard ratio, 1.12; 1.01-1.24; P=0.033) and C-reactive protein (adjusted hazard ratio, 1.15; 1.02-1.30; P=0.022) after adjusting for age, sex, hypertension, smoking, and diabetes mellitus although P-selectin seemed to predict stroke after transient ischemic attack (adjusted hazard ratio, 1.28; 1.00-1.63; P=0.046).
  
  
  CONCLUSIONS
  In the largest study to date, we found limited predictive use for early recurrent stroke for a panel of inflammatory, thrombotic, and cell damage biomarkers.
authors.affiliation: From the Stroke Prevention Research Unit, Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, Oxford, United Kingdom.
authors.forename: Helen C
authors.initials: HC
authors.lastname: Segal
authors.affiliation: From the Stroke Prevention Research Unit, Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, Oxford, United Kingdom.
authors.forename: Annette I
authors.initials: AI
authors.lastname: Burgess
authors.affiliation: From the Stroke Prevention Research Unit, Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, Oxford, United Kingdom.
authors.forename: Debbie L
authors.initials: DL
authors.lastname: Poole
authors.affiliation: From the Stroke Prevention Research Unit, Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, Oxford, United Kingdom.
authors.forename: Ziyah
authors.initials: Z
authors.lastname: Mehta
authors.affiliation: From the Stroke Prevention Research Unit, Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, Oxford, United Kingdom.
authors.forename: Louise E
authors.initials: LE
authors.lastname: Silver
authors.affiliation: From the Stroke Prevention Research Unit, Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, Oxford, United Kingdom. peter.rothwell@clneuro.ox.ac.uk.
authors.forename: Peter M
authors.initials: PM
authors.lastname: Rothwell
mesh_terms: D000368:Aged; D015415:Biomarkers / Q000097:blood*; D005260:Female; D006801:Humans; D007118:Immunoassay; D007249:Inflammation / Q000097:blood / Q000150:complications; D008297:Male; D008875:Middle Aged; D012008:Recurrence; D020521:Stroke / Q000097:blood* / Q000209:etiology
chemical_list: D015415:Biomarkers
keywords: biomarkers; early recurrent stroke; prediction