Timlin H, Butler L, Wright M
Princess Alexandra Eye Pavilion, Edinburgh, UK.
Eye (Lond). 2015 May;29(5):619-24. doi: 10.1038/eye.2015.9. Epub 2015 Feb 20.
To assess the diagnostic accuracy of the Edinburgh Red Eye Algorithm.
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.
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).
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.
评估爱丁堡红眼病诊断算法的诊断准确性。
这是一项前瞻性研究。设计了一份问卷,并提供给将患者转诊至爱丁堡急性眼科服务的临床医生。问卷要求他们使用该算法对出现红眼症状的患者进行诊断。然后将患者转诊至急诊眼科诊所,并将问卷传真至诊所或随患者一同送去。随后由一位经验丰富的眼科医生(未设盲)对患者进行检查,以得出“金标准”诊断。然后评估“算法辅助”诊断与“金标准”之间的一致性。
所有出现红眼症状的患者均符合纳入标准。共完成41份问卷,排除2份。算法辅助诊断在72%(28/39)的情况下是正确的。它正确诊断出:急性闭角型青光眼的准确率为100%(4/4);虹膜炎为82%(9/11);基质性角膜炎为63%(5/8);上皮性角膜炎为70%(7/10);感染性结膜炎为50%(3/6)。
爱丁堡红眼病诊断算法的诊断准确率为72%,若仅纳入最严重的红眼病因,准确率可升至76%。在评估出现红眼症状的患者时,非眼科医生使用该算法时的诊断准确率更高。我们希望使用此算法能够避免某些严重眼部疾病的就诊延迟,并降低延迟治疗带来的发病率。