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Abstract：
Background and Objectives: Glaucoma is a major cause of irreversible visual impairment and blindness, so its timely detection is crucial. Retinal images from diabetic retinopathy screening programmes (DRSP) provide an opportunity to detect undiagnosed glaucoma. Our aim was to find out which retinal image indicators are most suitable for referring DRSP patients for glaucoma assessment and to determine the glaucoma detection potential of Slovenian DRSP. Materials and Methods: We reviewed retinal images of patients from the DRSP at the University Medical Centre Ljubljana (November 2019-January 2020, May-August 2020). Patients with at least one indicator and some randomly selected patients without indicators were invited for an eye examination. Suspect glaucoma and glaucoma patients were considered accurately referred. Logistic regression (LOGIT) with patients as statistical units and generalised estimating equation with logistic regression (GEE) with eyes as statistical units were used to determine the referral accuracy of indicators. Results: Of the 2230 patients reviewed, 209 patients (10.1%) had at least one indicator on a retinal image of either one eye or both eyes. A total of 149 (129 with at least one indicator and 20 without) attended the eye exam. Seventy-nine (53.0%) were glaucoma negative, 54 (36.2%) suspect glaucoma, and 16 (10.7%) glaucoma positive. Seven glaucoma patients were newly detected. Neuroretinal rim notch predicted glaucoma in all cases. The cup-to-disc ratio was the most important indicator for accurate referral (odds ratio 7.59 (95% CI 3.98-14.47; p < 0.001) and remained statistically significant multivariably. Family history of glaucoma also showed an impact (odds ratio 3.06 (95% CI 1.02-9.19; p = 0.046) but remained statistically significant only in the LOGIT multivariable model. Other indicators and confounders were not statistically significant in the multivariable models. Conclusions: Our results suggest that the neuroretinal rim notch and cup-to-disc ratio are the most important for accurate glaucoma referral from retinal images in DRSP. Approximately half of the glaucoma cases in DRSPs may be undiagnosed.
摘要：
背景与目的:青光眼是导致不可逆性视力损害和失明的主要原因,所以它的及时发现是至关重要的。来自糖尿病性视网膜病变筛查计划（DRSP）的视网膜图像为检测未诊断的青光眼提供了机会。我们的目的是找出哪些视网膜图像指标最适合推荐DRSP患者进行青光眼评估，并确定斯洛文尼亚DRSP的青光眼检测潜力。材料和方法：我们回顾了卢布尔雅那大学医学中心DRSP患者的视网膜图像（2019年11月至2020年1月，2020年5月至8月）。邀请具有至少一个指标的患者和一些随机选择的没有指标的患者进行眼部检查。怀疑青光眼和青光眼患者被认为是准确的。使用以患者为统计单位的逻辑回归（LOGIT）和以眼睛为统计单位的逻辑回归（GEE）的广义估计方程来确定指标的转诊准确性。结果：在检查的2230例患者中，209名患者（10.1％）在一只眼睛或两只眼睛的视网膜图像上至少有一个指标。共有149人（129人至少有一个指标，20人没有）参加了眼科检查。79例（53.0%）青光眼阴性，54（36.2％）怀疑青光眼，16例（10.7%）青光眼阳性。新发现7例青光眼患者。神经视网膜边缘切迹可预测所有病例的青光眼。杯盘比率是准确转诊的最重要指标（比值比7.59（95％CI3.98-14.47；p<0.001），并且在多变量方面保持统计学意义。青光眼家族史也显示了影响（比值比3.06（95％CI1.02-9.19；p=0.046），但仅在LOGIT多变量模型中仍具有统计学意义。其他指标和混杂因素在多变量模型中没有统计学意义。结论：我们的结果表明，神经视网膜边缘凹口和杯盘比对于从DRSP中的视网膜图像准确转诊青光眼最重要。DRSP中约有一半的青光眼病例可能未被诊断。
