Viscodilation of Schlemm’s canal for the reduction of IOP via an ab-interno approach
Bibliographic record
Abstract
Purpose: The aim of this study was to compare the 1-year efficacy and safety profile of ab-interno canaloplasty (ABiC) when performed as a stand-alone procedure or as an adjunct to cataract extraction in reducing IOP and glaucoma medication dependence. Patients and methods: This retrospective, comparative, consecutive case series included patients with uncontrolled primary open-angle glaucoma (POAG) who underwent ABiC as a stand-alone procedure or in conjunction with cataract extraction. Data were collected over a 12-month period. Primary outcome measures were mean lower IOP and mean number of glaucoma medications. Secondary endpoints included surgical and postsurgical complications and secondary interventions. Results: The study included 75 eyes of 68 patients (mean age: 73.7±9.9 years) with a mean baseline IOP of 20.4±4.7 mmHg on 2.8±0.9 medications, which reduced to 13.3±1.9 mmHg (n=73) on 1.1±1.1 medications at 12 months postoperative (both P <0.0001). At 12 months, 40% of eyes were medication free. In the ABiC/phacoemulsification subgroup (n=34 eyes), the mean IOP and medication use decreased from 19.4±3.7 mmHg on 2.6±1.0 medications preoperatively to 13.0±1.8 mmHg on 0.8±0.2 medications at 12 months (both P <0.001). In the stand-alone ABiC subgroup (n=41), the mean IOP and medication use decreased from 21.2±5.3 mmHg on 3.0±0.7 medications preoperatively to 13.7±1.9 mmHg on 1.3±1.1 medications at 12 months ( P =0.001 and <0.001, respectively). No serious adverse events were recorded. Conclusion: These data demonstrate that ABiC was effective at reducing IOP and medication use in eyes with uncontrolled POAG with or without cataract surgery. Keywords: IOP, primary open-angle glaucoma, ab-interno canaloplasty, glaucoma medication
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".