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Purpose: Diabetic macular edema (DME), a leading cause of visual impairment, can occur regardless of diabetic retinopathy (DR) stage. Poor metabolic control is hypothesized to contribute to DME development, although large-scale studies have yet to identify such an association. This study aims to determine whether measurable markers of dysmetabolism are associated with DME development in persons with diabetes. Design: Retrospective cohort study. Participants: Using data from the Sight Outcomes Research Collaborative (SOURCE) repository, patients with diabetes mellitus and no preexisting DME were identified and followed over time to see what factors associated with DME development. Methods: Cox proportional hazard modeling was used to assess the relationship between demographic variables, diabetes type, smoking history, baseline DR status, blood pressure (BP), lipid profile, body mass index (BMI), hemoglobin A1C (HbA1C), and new onset of DME. Main Outcome Measures: Adjusted hazard ratio (HR) of developing DME with 95% confidence intervals (CIs). Results: Of 47 509 eligible patients from 10 SOURCE sites (mean age 63 ± 12 years, 58% female sex, 48% White race), 3633 (7.6%) developed DME in the study period. The mean ± standard deviation time to DME was 875 ± 684 days (â¼2.4 years) with those with baseline nonproliferative DR (HR 3.67, 95% CI: 3.41-3.95) and proliferative DR (HR 5.19, 95% CI: 4.61-5.85) more likely to develop DME. There was no difference in DME risk between type 1 and type 2 patients; however, Black race was associated with a 40% increase in DME risk (HR 1.40, 95% CI: 1.30-1.51). Every 1 unit increase in HbA1C had a 15% increased risk of DME (HR 1.15, 95% CI: 1.13-1.17), and each 10 mmHg increase in systolic BP was associated with a 6% increased DME risk (HR 1.06, 95% CI: 1.02-1.09). No association was identified between DME development and BMI, triglyceride levels, or high-density lipoprotein levels. Conclusions: These findings suggest that in patients with diabetes modifiable risk factors such as elevated HbA1C and BP confer a higher risk of DME development; however, other modifiable systemic markers of dysmetabolism such as obesity and dyslipidemia did not. Further work is needed to identify the underlying contributions of race in DME. Financial Disclosures: Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.
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PURPOSE: There is a longstanding belief that prostaglandin analogs (PGAs) may predispose patients with glaucoma to develop acute cystoid macular edema (CME). However, there is little solid evidence supporting this notion. The purpose of this study is to compare CME incidence rates among patients initiating treatment with different glaucoma medication classes. DESIGN: Database study. PARTICIPANTS: 39948 patients who were newly prescribed glaucoma medications METHODS: Using data from 10 health systems contributing data to the Sight Outcomes Research Collaborative (SOURCE) Ophthalmology Data Repository, we identified all adults with glaucoma who had been newly started on a topical glaucoma medication. Patients with pre-existing documentation of macular edema were excluded. We assessed the incidence of CME among patients with glaucoma who were newly started on PGAs, topical beta blockers (BBs), alpha agonists (AAs), and carbonic anhydrase inhibitors (CAIs). Using multivariable logistic regression, and adjusting for sociodemographic factors, we assessed the odds of developing CME among patients prescribed each of the 4 glaucoma medication classes. We also performed a subset regression analysis including lens status as a co-variate. MAIN OUTCOME MEASURES: Incidence of CME within 3 months of initiating therapy with different topical glaucoma medications. RESULTS: Among the 39,948 patients were newly treated with a topical glaucoma medication, 139 (0.35%) developed CME. The incidence of CME was 0.13%, 0.65%, 0.55%, 1.76% for users of PGAs, BBs, alpha agonists (AAs) and carbonic anhydrase inhibitors (CAIs), respectively. After adjusting for sociodemographic factors, users of topical BBs, AAs and CAIs had substantially higher odds of developing CME compared with PGA users (P<0.001 for all comparisons). The subset analysis also showed higher odds ratio of the non-PGA medication classes in association with CME. CONCLUSIONS: Clinicians should reconsider the notion that PGAs carry a higher risk of CME versus other glaucoma medication classes. If additional studies support the findings of these analyses, clinicians may feel more comfortable prescribing PGAs to patients with glaucoma without fear they will predispose patients to CME.