Preliminary Surgical Outcomes of a Trimmed-Plate Aurolab Aqueous Drainage Implant (AADI) in Eyes at High Risk of Hypotony
Bibliographic record
Abstract
Purpose: We describe the technique of trimming the 350 mm 2 AADI glaucoma shunt plate and report preliminary results that test the hypothesis that the IOP-lowering efficacy of the trimmed AADI glaucoma shunt is comparable to the Baerveldt 250 mm 2 glaucoma drainage implant with a comparable safety profile to the standard AADI implant. Methods: Consecutive patients who had received the modified trimmed-plate AADI, standard AADI and Baerveldt 250 mm 2 were included in the study. This included patients with refractory or primary or secondary glaucoma of all ages and eyes with and without previous glaucoma surgery. The decision for trimming the AADI plate was made according to the surgeon’s perceived risk of hypotony. Pre-operative, intraoperative and post-operative data were collected from the hospital electronic medical record system. Surgical success was defined as IOP ≥ 5 mmHg and ≤ 21 mmHg on two consecutive visits after 3 months, whilst maintaining at least LP vision and avoiding re-operation for glaucoma. Results: The sample consisted of 69 eyes (19 with trimmed-plate AADI implant; 36 eyes with the standard AADI implant and 14 eyes who received a BGI-250). The mean IOP reduction at 1 year was 15 mmHg for the Baerveldt-250, 10 mmHg for the AADI and 13 mmHg for the trimmed-plate AADI. The surgical success rate of the implants over 1 year was 85.7% (95% CI, 53.9– 96.2%) for BGI-250, 81.5% (62.6– 91.5%) for standard AADI and 78.2% (51.7– 91.3%) for the trimmed AADI. Conclusion: Trimming the plate of the AADI manually may provide a safe and low-cost method of obtaining a successful surgical outcome in eyes at high risk of hypotony. Keywords: refractory glaucoma, non-valved glaucoma drainage device, AADI, trimmed-plate implant, hypotony
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| 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".