METHODS: Cohort study.
METHODS: Patients diagnosed with open-angle glaucoma (OAG) at a tertiary care institution. All eyes had glaucomatous visual field defects at baseline. Sociodemographic and ocular data were extracted from the EHR, including age, gender, self-reported race and ethnicity, insurance status, OAG type, prior glaucoma laser or surgery, baseline disease severity using Hodapp-Anderson-Parrish criteria, mean intraocular pressure (IOP) during follow-up, and central corneal thickness. Social vulnerability index (SVIndex) data at the census tract level were obtained using geocoded patient residences. Mixed-effects Cox proportional hazard models were completed to assess for the development of severe visual impairment or blindness during follow-up, defined as BCVA ≤ 20/200 at least at the last two clinic visits or standard automated perimetry (SAP) mean deviation (MD) ≤ -22dB confirmed on two tests.
RESULTS: A total of 4,046 eyes from 2,826 patients met inclusion criteria and were followed for an average of 4.3 ± 2.2 years. Severe visual impairment or blindness developed in 79 eyes (2.0%) from 76 patients (2.7%) after an average of 3.4 ± 1.8 years, leading to an incidence rate of severe visual impairment or blindness of 0.5% per year. Older age (adjusted hazards ratio [HR] 1.36 per decade, P = .007), residence in areas with higher SVIndex (HR 1.56 per 25% increase, P < .001), higher IOP during follow-up (HR 3.01 per 5 mmHg increase, P < .001), and moderate or severe glaucoma at baseline (HR 7.31 and 26.87, P < .001) were risk factors for developing severe visual impairment or blindness. Concordance index of the model was 0.88. Socioeconomic, minority status/language, and housing type/transportation SVIndex themes were key contributors to developing severe visual impairment or blindness.
CONCLUSIONS: Risk factors for developing glaucoma-related severe visual impairment or blindness included older age, elevated IOP during follow-up, moderate or severe disease at baseline, and residence in areas associated with greater social vulnerability. In addition to ocular risk factors, geocoded EHR data regarding social risk factors could help identify patients at high risk of developing glaucoma-related visual impairment.
方法:队列研究。
方法:在三级护理机构诊断为开角型青光眼(OAG)的患者。所有眼睛在基线时都有青光眼视野缺损。从EHR中提取社会人口统计学和眼部数据,包括年龄,性别,自我报告的种族和种族,保险状况,OAG类型,既往青光眼激光或手术,使用Hodapp-Anderson-Parrish标准的基线疾病严重程度,随访期间的平均眼内压(IOP),和中央角膜厚度。使用地理编码的患者住宅获得了人口普查区级别的社会脆弱性指数(SVIndex)数据。完成了混合效应Cox比例风险模型,以评估随访期间严重视力障碍或失明的发展。定义为最近两次临床就诊时的BCVA≤20/200,或在两次测试中确认的标准自动视野检查(SAP)平均偏差(MD)≤-22dB。
结果:来自2,826例患者的4,046只眼符合纳入标准,平均随访4.3±2.2年。平均3.4±1.8年后,76例患者(2.7%)的79眼(2.0%)出现严重的视力障碍或失明,导致每年0.5%的严重视力障碍或失明的发病率。年龄较大(调整后的危险比(HR)每十年1.36,p=0.007),居住在SVIndex较高的地区(每增加25%HR1.56,p<0.001),随访期间眼压较高(每增加5mmHgHR3.01,p<0.001),基线时的中度或重度青光眼(HR7.31和26.87,p<0.001)是发生重度视力障碍或失明的危险因素.模型的一致性指数为0.87。社会经济,少数民族地位/语言,住房类型/交通SVIndex主题是导致严重视力障碍或失明的关键因素。
结论:发生青光眼相关严重视力障碍或失明的危险因素包括年龄较大,随访期间IOP升高,基线时的中度或重度疾病,和居住在与更大的社会脆弱性相关的地区。除了眼部危险因素,有关社会危险因素的经地理编码的EHR数据可以帮助识别发生青光眼相关视力障碍的高危患者.