Rates of glaucomatous visual field change after trabeculectomy
Bibliographic record
Abstract
BACKGROUND: Trabeculectomy is frequently performed in patients with glaucoma who are deteriorating, although its effects on rates of visual field (VF) progression are not fully understood. We studied the rate of VF progression post trabeculectomy comparing with medically treated patients matched for VF loss. METHODS: Medical records of patients who underwent trabeculectomy alone or combined with cataract extraction were reviewed. Patients with 5 or more 24-2 VF examinations post trabeculectomy were selected. The rate of mean deviation (MD) change after surgery was calculated for each patient. These patients were pairwise matched based on baseline MD with patients with glaucoma who were treated medically and had at least 5 VF tests. RESULTS: 180 surgical patients were identified and matched with 180 medically treated patients (baseline MD of -8.72 (5.24) dB and -8.71 (5.22) dB, respectively). Surgically and medically treated patients were followed for 7.4 (2.9) and 6.8 (3.1) years respectively. The MD slopes were -0.22 (0.55) dB/year and -0.08 (1.10) dB/year in the surgically and medically treated patients, respectively, and not statistically different (p=0.13, 95% CI -0.31 to 0.04). More patients in the surgical group had fast progression (rates worse than -1 dB/year) than in the medical group (17 and 7 patients, respectively, p=0.05). CONCLUSIONS: Our findings suggest that most patients who undergo trabeculectomy demonstrate relatively slow rates of VF progression postoperatively, similar to patients treated medically, although some patients can continue to progress despite adequate surgical control of intraocular pressure.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 teacher head, 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".