Systematic Occlusion of Shunts
Bibliographic record
Abstract
OBJECTIVE: Evaluation of a protocol of total intraluminal occlusion of Baerveldt shunts and its effects on early postoperative intraocular pressure (IOP) control and hypotony-related complications. DESIGN: This was a noncomparative, prospective, and interventional study. PARTICIPANTS: Glaucoma patients were recruited to undergo Baerveldt shunt surgery. A total of 116 eyes of 112 patients were enrolled. INTERVENTION: During shunt implantation, aqueous outflow was restricted using an intraluminal occluding stent inserted through the entire tube length, with and without external ligation, to halt aqueous flow. Postoperatively, eyes underwent ligature laser suture lysis and partial or complete stent removals, at predetermined time intervals. MAIN OUTCOME MEASURE: Loss of postoperative IOP control was categorized as transient or persistent hypotony (IOP≤5 mm Hg) or hypertony (IOP>21 mm Hg). Patients were followed up for 1 year. RESULTS: Preoperatively median IOP was 23 mm Hg (mean 26 mm Hg, SD 12 mm Hg), median number of glaucoma medications was 3.0 (mean 3.0, SD 1.2). During year 1, laser suture lysis was performed in 30 eyes (26%) and stent removal in 93 eyes (80%) (23 partial; 70 complete). There was 1 case of transient hypotony, no cases of persistent hypotony, 10 of transient hypertony, and 3 of persistent hypertony. Nine eyes had IOP≤5 mm Hg at ≥1 time points and hypotony-related complications occurred in 8 eyes (7%). At 1 year, median IOP was 12 mm Hg (mean 13 mm Hg, SD 4 mm Hg) with a median of 1.0 glaucoma medications (mean 1.1, SD 1.3). The cumulative probability of failure during the first 12 months follow-up was 6% (n=7). Overall postoperative complications occurred in 11 eyes (9%). CONCLUSIONS: The surgical and postoperative protocol resulted in controlled, step-wise reductions of IOP with low rates of hypotony and related complications.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".