Association of Postoperative Topical Prostaglandin Analog or Beta-Blocker Use and Incidence of Pseudophakic Cystoid Macular Edema
Bibliographic record
Abstract
PURPOSE: The purpose of this article is to determine the association of postoperative topical prostaglandin analog (PGA) or topical beta-blocker use and the incidence of pseudophakic cystoid macular edema (CME). METHODS: This was a nested case-control study. All adult patients who underwent cataract surgery between January 1, 2006 and December 31, 2016 and who were enrolled in the PharMetrics Plus database were eligible for inclusion. The association between postoperative topical PGAs (bimatoprost, latanoprost, and travoprost/travoprost-z) or beta-blocker (betaxolol, levobunolol, and timolol) use and the incidence of pseudophakic CME was assessed by conditional logistic regression. RESULTS: Five hundred eight cases and 5080 controls were included in the analyses. Incidence of pseudophakic CME was found to be statistically significantly associated with the current postoperative use of both topical PGAs [relative risk (RR), 1.86; 95% confidence interval (CI), 1.04-3.32] and topical beta-blockers (RR, 2.64; 95% CI, 1.08-6.49). Postoperative use of each of bimatoprost (RR, 2.73; 95% CI, 1.35%-5.53%) and travoprost/travoprost-z (RR, 3.16; 95% CI, 1.42-7.03) in the year before diagnosis was demonstrated to be statistically significantly associated with the incidence of pseudophakic CME. This association was not observed to be statistically significant with the postoperative use of latanoprost (RR, 1.55; 95% CI, 0.84-2.88). CONCLUSIONS: To the best of our knowledge this is the largest study that has investigated the association between postoperative topical PGA or topical beta-blocker use and the incidence of pseudophakic CME. Postoperative use of both topical PGAs and topical beta-blockers was found to be associated with the incidence of pseudophakic CME.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".