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Clinical decision making in opthalmology
  1. J van der Meulen1,
  2. J Rahi2
  1. 1Health Services Research Unit, London School of Hygiene and Tropical Medicine and Clinical Effectiveness Unit, Royal College fo Surgeons of England, London, Uk
  2. 2Center for Paediatric Epidemiology and Biostatistics and Department of Opthalmology, Institute of Child Health/Great Ormond Street Hospital, London, UK
  1. Correspondence to: Jan van der Meulen, Health Services Research Unit, London School of Hygiene and Tropical Medicine, Keppel Street, London WCIE 7HT, UK; Jan.vanderMeulen{at}lshtm.oc.uk

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The importance of prognosis and treatment effect

Decisions based on clinical examination are critical to the practice of ophthalmology. Although quite different disease processes can produce the same structural and functional outcomes, treatment decisions are often directly based on the observation of a complex of signs and symptoms. Thus, presented with a patient with sudden visual loss and/or ocular pain due to posterior uveitis, the ophthalmologist will rely on the clinical examination, in particular ophthalmoscopy, to answer three basic questions: what is wrong (diagnosis), what can we expect in the future (prognosis), and what can we do about it (effect of treatment)? But how reliable and accurate are ophthalmoscopic observations and how useful is ophthalmoscopy to support therapeutic decisions?

Stanford and co-workers, in a study published in this issue of the BJO (636), have tried to address some of these questions. They estimated the sensitivity and specificity of uveitis experts' interpretation of retinal photographs for the diagnosis of toxoplasma retinochoroiditis. Five experts were asked to classify the retinal photographs of 96 patients into four categories without any additional information (definitely, probably, possibly, or not toxoplasma retinochoroiditis). This is an important study as it is the first time that the diagnostic accuracy of these ophthalmoscopic findings has been investigated. A major problem the investigators had to overcome was that it is not possible to diagnose or exclude the disease with certainty, and a statistical model was therefore used to estimate …

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