Hitzl Wolfgang, Lenzhofer Markus, Hohensinn Melchior, Reitsamer Herbert Anton
Department of Ophthalmology and Optometry, Paracelsus Medical University, University Hospital Salzburg, Muellner Hauptstrasse 48, 5020 Salzburg, Austria.
Research Program Experimental Ophthalmology and Glaucoma Research, Paracelsus Medical University, Muellner Hauptstrasse 48, 5020 Salzburg, Austria.
J Pers Med. 2025 Aug 7;15(8):361. doi: 10.3390/jpm15080361.
: In glaucoma screening programs, a large proportion of patients remain free of open-angle glaucoma (OAG) or have no need of intraocular eye pressure (IOP)-lowering therapy within 10 years of follow-up. Is it possible to identify a large proportion of patients already at the initial examination and, thus, to safely exclude them already at this point? : A total of 6889 subjects received a complete ophthalmological examination, including objective optic nerve head and quantitative disc measurements at the initial examination, and after an average follow-up period of 11.1 years, complete data were available of 585 individuals. Two neural network models were trained and extensively tested. To allow the models to refuse to make a prediction in doubtful cases, a reject option was included. : A prediction for the first endpoint, 'remaining OAG-free and no IOP-lowering therapy within 10 years', was rejected in 57% of cases, and in the remaining cases (43%), 253/253 (=100%) received a correct prediction. The second prediction model for the second endpoint 'remaining OAG-free within 10 years' refused to make a prediction for 46.4% of all subjects. In the remaining cases (53.6%), 271/271 (=100%) were correctly predicted. : Most importantly, no eye was predicted false-negatively or false-positively. Overall, 43% all eyes can safely be excluded from a glaucoma screening program for up to 10 years to be certain that the eye remains OAG-free and will not need IOP-lowering therapy. The corresponding model significantly reduces the screening performed by and work load of ophthalmologists. In the future, better predictors and models may increase the number of patients with a safe prediction, further economizing time and healthcare budgets in glaucoma screening.
在青光眼筛查项目中，很大一部分患者在随访的10年内未患开角型青光眼（OAG）或无需降低眼压（IOP）治疗。是否有可能在初次检查时就识别出很大一部分患者，从而在此时就安全地将他们排除在外呢？
共有6889名受试者接受了全面的眼科检查，包括初次检查时的客观视神经乳头和定量视盘测量，在平均11.1年的随访期后，获得了585名个体的完整数据。训练并广泛测试了两个神经网络模型。为了让模型在可疑情况下拒绝做出预测，纳入了拒绝选项。
对于第一个终点“10年内未患OAG且无需降低眼压治疗”的预测，在57%的病例中被拒绝，在其余病例（43%）中，253/253（=100%）得到了正确预测。第二个终点“10年内未患OAG”的第二个预测模型对所有受试者中的46.4%拒绝做出预测。在其余病例（53.6%）中，271/271（=100%）被正确预测。
最重要的是，没有眼睛被预测为假阴性或假阳性。总体而言，43%的眼睛可以安全地从青光眼筛查项目中排除长达10年，以确定眼睛仍未患OAG且不需要降低眼压治疗。相应的模型显著减少了眼科医生进行的筛查和工作量。未来，更好的预测指标和模型可能会增加能够安全预测的患者数量，进一步节省青光眼筛查中的时间和医疗保健预算。
