贝叶斯在预测专科验光师对慢性开角型青光眼转诊决策中的应用。
Application of Bayes' to the prediction of referral decisions made by specialist optometrists in relation to chronic open angle glaucoma.
机构信息
Community Ophthalmology Team, West Kent CCG, Aylesford, UK.
Ophthalmic Research Group, Optometry School, Aston University, Birmingham, UK.
出版信息
Eye (Lond). 2018 Jun;32(6):1074-1078. doi: 10.1038/s41433-018-0023-5. Epub 2018 Feb 9.
PURPOSE
To determine the accuracy of a Bayesian learning scheme (Bayes') applied to the prediction of clinical decisions made by specialist optometrists in relation to the referral refinement of chronic open angle glaucoma.
METHODS
This cross-sectional observational study involved collection of data from the worst affected or right eyes of a consecutive sample of cases (n = 1,006) referred into the West Kent Clinical Commissioning Group Community Ophthalmology Team (COT) by high street optometrists. Multilevel classification of each case was based on race, sex, age, family history of chronic open angle glaucoma, reason for referral, Goldmann Applanation Tonometry (intraocular pressure and interocular asymmetry), optic nerve head assessment (vertical size, cup disc ratio and interocular asymmetry), central corneal thickness and visual field analysis (Hodapp-Parrish-Anderson classification). Randomised stratified tenfold cross-validation was applied to determine the accuracy of Bayes' by comparing its output to the clinical decisions of three COT specialist optometrists; namely, the decision to discharge, follow-up or refer each case.
RESULTS
Outcomes of cross-validation, expressed as means and standard deviations, showed that the accuracy of Bayes' was high (95%, 2.0%) but that it falsely discharged (3.4%, 1.6%) or referred (3.1%, 1.5%) some cases.
CONCLUSIONS
The results indicate that Bayes' has the potential to augment the decisions of specialist optometrists.
目的
确定贝叶斯学习方案（贝叶斯）在预测专科视光师对慢性开角型青光眼转诊细化的临床决策方面的准确性。
方法
本横断面观察性研究涉及收集由高街视光师转诊至西肯特临床委托组社区眼科团队（COT）的连续病例样本（n=1006）中最差受影响或右眼的数据。根据种族、性别、年龄、慢性开角型青光眼家族史、转诊原因、Goldmann 压平眼压计（眼压和眼间不对称）、视神经头评估（垂直大小、杯盘比和眼间不对称）、中央角膜厚度和视野分析（Hodapp-Parrish-Anderson 分类）对每个病例进行多层次分类。通过将贝叶斯的输出与三位 COT 专科视光师的临床决策进行比较，应用随机分层十折交叉验证来确定贝叶斯的准确性；即，决定每个病例的出院、随访或转诊。
结果
交叉验证的结果（表示为平均值和标准差）表明贝叶斯的准确性很高（95%，2.0%），但它错误地释放（3.4%，1.6%）或转诊（3.1%，1.5%）了一些病例。
结论
结果表明，贝叶斯有可能增强专科视光师的决策。
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