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Predicting freedom from clinical events in non-ST-elevation acute coronary syndromes
  1. C P Gale,
  2. B A Cattle,
  3. A D Simms,
  4. D C Greenwood,
  5. R M West
  1. Division of Biostatisitcs, University of Leeds, Leeds, UK
  1. Dr C P Gale, Biostatistics Unit, Leeds Institute of Genetics Health and Therapeutics, University of Leeds, Clarendon Way, West Yorkshire, Leeds LS2 9JT, UK; c.p.gale{at}leeds.ac.uk

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To the editor: We read with interest the paper presented by Brieger et al1 and feel that it is most worthy of comment. The authors describe the development and internal validation of a risk score for patients with non-ST elevation acute coronary syndrome (NSTEACS), from a global registry, that predicts inpatient freedom-from-events. They present an alternative concept to ACS risk characterisation—rather than the identification of high-risk subjects who merit more intensive management, they elect to create a model that can assist healthcare workers identify lower-risk patients who may benefit less from such treatments. They argue that this is important because the discriminative performance of ACS risk scores designed to identify patients at higher risk of adverse outcomes is limited when applied to patients at lower risk of adverse events. We believe that several key points deserve clarification.

  • Whereas some “near-point” ACS risk models are often based on a combination of a retrospective final diagnosis and data gathered over a period of some time (“far-point” data), the model proposed by Brieger et al is generated from a cohort with NSTEACS using variables that may be collected within 24 h of admission. Even so, the …

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