Bibliographic record
Abstract
PURPOSE OF REVIEW: As glaucoma surgeons continue to search for an improvement over trabeculectomy, the ExPRESS miniature glaucoma shunt has gained interest as a possible contender. Peer-reviewed literature on ExPRESS is beginning to accumulate allowing an evidence-based review to assess the potential benefits and limitations compared to trabeculectomy. RECENT FINDINGS: The current surgical procedure for ExPRESS implantation will be described followed by results of studies comparing ExPRESS to trabeculectomy, focusing on the following outcomes: success, intraocular pressure, and complications. Case reports of late complications specific to the ExPRESS device will be summarized. Finally, an economic analysis comparing ExPRESS to trabeculectomy will be provided as additional evidence to contribute to the decision matrix on deciding which filtration procedure to recommend. SUMMARY: Despite a large number of ExPRESS implant procedures worldwide, there is a paucity of high-quality studies comparing ExPRESS to trabeculectomy. From the available literature to date the outcomes (success and early complications) of ExPRESS are similar to trabeculectomy. Reports of late complications related to device extrusion and malposition are beginning to be published; however, the significantly increased cost for ExPRESS surgery is likely to be the main limitation to widespread adoption of this procedure.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".