title: Patient phenotypes associated with outcomes after aneurysmal subarachnoid hemorrhage: a principal component analysis.
abstract: OBJECTIVE
  Predictors of outcome after aneurysmal subarachnoid hemorrhage have been determined previously through hypothesis-driven methods that often exclude putative covariates and require a priori knowledge of potential confounders. Here, we apply a data-driven approach, principal component analysis, to identify baseline patient phenotypes that may predict neurological outcomes.
  
  
  METHODS
  Principal component analysis was performed on 120 subjects enrolled in a prospective randomized trial of clazosentan for the prevention of angiographic vasospasm. Correlation matrices were created using a combination of Pearson, polyserial, and polychoric regressions among 46 variables. Scores of significant components (with eigenvalues>1) were included in multivariate logistic regression models with incidence of severe angiographic vasospasm, delayed ischemic neurological deficit, and long-term outcome as outcomes of interest.
  
  
  RESULTS
  Sixteen significant principal components accounting for 74.6% of the variance were identified. A single component dominated by the patients' initial hemodynamic status, World Federation of Neurosurgical Societies score, neurological injury, and initial neutrophil/leukocyte counts was significantly associated with poor outcome. Two additional components were associated with angiographic vasospasm, of which one was also associated with delayed ischemic neurological deficit. The first was dominated by the aneurysm-securing procedure, subarachnoid clot clearance, and intracerebral hemorrhage, whereas the second had high contributions from markers of anemia and albumin levels.
  
  
  CONCLUSIONS
  Principal component analysis, a data-driven approach, identified patient phenotypes that are associated with worse neurological outcomes. Such data reduction methods may provide a better approximation of unique patient phenotypes and may inform clinical care as well as patient recruitment into clinical trials.
  
  
  BACKGROUND
  http://www.clinicaltrials.gov. Unique identifier: NCT00111085.
authors.affiliation: From the Division of Neurosurgery, St Michael's Hospital, Labatt Family Centre of Excellence in Brain Injury and Trauma Research, Keenan Research Centre of the Li Ka Shing Knowledge Institute of St Michael's Hospital, Toronto, Ontario, Canada (G.M.I., B.R.M.); Department of Surgery (G.M.I., R.L.M.) and Institute of Medical Science (G.M.I.), University of Toronto, Toronto, Ontario, Canada; and Department of Medical Imaging, Hospital for Sick Children, Toronto, Ontario, Canada (G.M.I., B.R.M.).
authors.forename: George M
authors.initials: GM
authors.lastname: Ibrahim
authors.forename: Benjamin R
authors.initials: BR
authors.lastname: Morgan
authors.forename: R Loch
authors.initials: RL
authors.lastname: Macdonald
mesh_terms: D002545:Brain Ischemia / Q000150:complications / Q000473:pathology; D002533:Cerebral Angiography; D004146:Dioxanes / Q000627:therapeutic use; D004311:Double-Blind Method; D005260:Female; D006801:Humans; D020300:Intracranial Hemorrhages / Q000150:complications; D008297:Male; D008875:Middle Aged; D009422:Nervous System Diseases / Q000209:etiology / Q000503:physiopathology; D010641:Phenotype; D025341:Principal Component Analysis; D011446:Prospective Studies; D011725:Pyridines / Q000627:therapeutic use; D011743:Pyrimidines / Q000627:therapeutic use; D013345:Subarachnoid Hemorrhage / Q000473:pathology* / Q000628:therapy*; D013449:Sulfonamides / Q000627:therapeutic use; D013777:Tetrazoles / Q000627:therapeutic use; D014057:Tomography, X-Ray Computed; D016896:Treatment Outcome; D020301:Vasospasm, Intracranial / Q000209:etiology / Q000503:physiopathology / Q000517:prevention & control
chemical_list: D004146:Dioxanes; D011725:Pyridines; D011743:Pyrimidines; D013449:Sulfonamides; D013777:Tetrazoles; C109641:clazosentan
keywords: coronary vasospasm; outcome assessment (health care); principal component analysis; subarachnoid hemorrhage