title: Prediction models for intracranial hemorrhage or major bleeding in patients on antiplatelet therapy: a systematic review and external validation study.
abstract: ESSENTIALS: Prediction models may help to identify patients at high risk of bleeding on antiplatelet therapy. We identified existing prediction models for bleeding and validated them in patients with cerebral ischemia. Five prediction models were identified, all of which had some methodological shortcomings. Performance in patients with cerebral ischemia was poor.
  
  
  CONCLUSIONS
  Background Antiplatelet therapy is widely used in secondary prevention after a transient ischemic attack (TIA) or ischemic stroke. Bleeding is the main adverse effect of antiplatelet therapy and is potentially life threatening. Identification of patients at increased risk of bleeding may help target antiplatelet therapy.
  
  
  OBJECTIVE
  This study sought to identify existing prediction models for intracranial hemorrhage or major bleeding in patients on antiplatelet therapy and evaluate their performance in patients with cerebral ischemia.
  
  
  METHODS
  We systematically searched PubMed and Embase for existing prediction models up to December 2014. The methodological quality of the included studies was assessed with the CHARMS checklist. Prediction models were externally validated in the European Stroke Prevention Study 2, comprising 6602 patients with a TIA or ischemic stroke. We assessed discrimination and calibration of included prediction models.
  
  
  RESULTS
  Five prediction models were identified, of which two were developed in patients with previous cerebral ischemia. Three studies assessed major bleeding, one studied intracerebral hemorrhage and one gastrointestinal bleeding. None of the studies met all criteria of good quality. External validation showed poor discriminative performance, with c-statistics ranging from 0.53 to 0.64 and poor calibration.
  
  
  CONCLUSIONS
  A limited number of prediction models is available that predict intracranial hemorrhage or major bleeding in patients on antiplatelet therapy. The methodological quality of the models varied, but was generally low. Predictive performance in patients with cerebral ischemia was poor. In order to reliably predict the risk of bleeding in patients with cerebral ischemia, development of a prediction model according to current methodological standards is needed.
authors.affiliation: Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, the Netherlands.
authors.forename: N A
authors.initials: NA
authors.lastname: Hilkens
authors.affiliation: Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, the Netherlands.|Department of Neurology and Neurosurgery, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, the Netherlands.
authors.forename: A
authors.initials: A
authors.lastname: Algra
authors.affiliation: Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, the Netherlands.
authors.forename: J P
authors.initials: JP
authors.lastname: Greving
mesh_terms: D000465:Algorithms; D000925:Anticoagulants / Q000009:adverse effects; D001241:Aspirin / Q000009:adverse effects; D002545:Brain Ischemia / Q000150:complications* / Q000175:diagnosis / Q000188:drug therapy; D002138:Calibration; D002543:Cerebral Hemorrhage / Q000517:prevention & control*; D004176:Dipyridamole / Q000009:adverse effects; D005060:Europe; D005260:Female; D006471:Gastrointestinal Hemorrhage / Q000517:prevention & control*; D006470:Hemorrhage / Q000175:diagnosis; D006801:Humans; D002546:Ischemic Attack, Transient / Q000150:complications* / Q000188:drug therapy; D008297:Male; D010975:Platelet Aggregation Inhibitors / Q000009:adverse effects*; D012044:Regression Analysis; D012306:Risk
chemical_list: D000925:Anticoagulants; D010975:Platelet Aggregation Inhibitors; D004176:Dipyridamole; D001241:Aspirin
keywords: antiplatelet agents; clinical prediction rule; intracranial hemorrhage; review systematic; stroke