PURPOSE: To assess the diagnostic accuracy of the Edinburgh Red Eye Algorithm. METHODS: This was a prospective study. A questionnaire was designed and made available to clinicians referring patients to the acute ophthalmology service within Edinburgh. The questionnaire involved them using the algorithm to reach a diagnosis in patients presenting with red eye(s). Patients were then referred to the emergency eye clinic and the questionnaire faxed to the clinic or sent with the patients. Patients were then examined by an experienced ophthalmologist (not blinded) to reach a 'gold standard' diagnosis. The concordance between the 'algorithm assisted' diagnosis and the 'gold standard' was then assessed. RESULTS: All patients presenting with red eye(s) were eligible for inclusion. Forty-one questionnaires were completed, two were excluded. The algorithm assisted diagnosis was correct 72% (28/39) of the time. It correctly diagnosed: acute angle closure glaucoma in 100% of cases (4/4); iritis in 82% (9/11); stromal keratitis in 63% (5/8); epithelial keratitis in 70% (7/10); and infective conjunctivitis in 50% (3/6). DISCUSSION: The diagnostic accuracy of The Edinburgh Red Eye Diagnostic Algorithm is 72, rising to 76% when only the most serious red eye(s) causes are included. The diagnostic accuracy of non-ophthalmologists when assessing patients presenting with red eye(s) is greater when the algorithm is used. We hope that the use of this algorithm will prevent delayed presentations of certain serious eye conditions and reduce the morbidity from delayed treatment.
PURPOSE: To assess the diagnostic accuracy of the Edinburgh Red Eye Algorithm. METHODS: This was a prospective study. A questionnaire was designed and made available to clinicians referring patients to the acute ophthalmology service within Edinburgh. The questionnaire involved them using the algorithm to reach a diagnosis in patients presenting with red eye(s). Patients were then referred to the emergency eye clinic and the questionnaire faxed to the clinic or sent with the patients. Patients were then examined by an experienced ophthalmologist (not blinded) to reach a 'gold standard' diagnosis. The concordance between the 'algorithm assisted' diagnosis and the 'gold standard' was then assessed. RESULTS: All patients presenting with red eye(s) were eligible for inclusion. Forty-one questionnaires were completed, two were excluded. The algorithm assisted diagnosis was correct 72% (28/39) of the time. It correctly diagnosed: acute angle closure glaucoma in 100% of cases (4/4); iritis in 82% (9/11); stromal keratitis in 63% (5/8); epithelial keratitis in 70% (7/10); and infective conjunctivitis in 50% (3/6). DISCUSSION: The diagnostic accuracy of The Edinburgh Red Eye Diagnostic Algorithm is 72, rising to 76% when only the most serious red eye(s) causes are included. The diagnostic accuracy of non-ophthalmologists when assessing patients presenting with red eye(s) is greater when the algorithm is used. We hope that the use of this algorithm will prevent delayed presentations of certain serious eye conditions and reduce the morbidity from delayed treatment.
Authors: Ranjan Duara; David A Loewenstein; Maria Greig; Amarilis Acevedo; Elizabeth Potter; Jason Appel; Ashok Raj; John Schinka; Elizabeth Schofield; Warren Barker; Yougui Wu; Huntington Potter Journal: Am J Geriatr Psychiatry Date: 2010-04 Impact factor: 4.105
Authors: J C Buchan; B Barnes; A Cassels-Brown; B Y Chang; J Harcourt; R F Pilling; D Shickle; A F Spencer; S A Vernon; C MacEwen Journal: Eye (Lond) Date: 2017-06-16 Impact factor: 3.775
Authors: Hillary Rono; Andrew Bastawrous; David Macleod; Emmanuel Wanjala; Stephen Gichuhi; Matthew Burton Journal: Trials Date: 2019-08-14 Impact factor: 2.279