PREDICTIVE FACTORS OF SPONTANEOUS RELEASE OF VITREOMACULAR TRACTION
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Bibliographic record
Abstract
Purpose: To review predictive factors of spontaneous vitreomacular traction (VMT) release. Methods: A systematic literature search was performed on Ovid MEDLINE, Embase, and Cochrane Library. Studies comparing spontaneously released VMT to persistent VMT were included. A meta-analysis was performed using a random effects model, and weighted mean difference, risk ratio (RR), and 95% confidence intervals (95% CI) were reported as appropriate. Results: Of a search of 258 studies, 12 studies were included, from which 272 of 934 eyes (29%) underwent spontaneous release. Mean age was 70.0 years, 37.2% of patients were men, and mean follow-up was 22.0 months. Significant predictive factors for spontaneous release were smaller VMT diameter (n = 177; weighted mean difference = −212.48 µ m, 95% CI = [−417.36, −7.60], P = 0.04), epiretinal membrane absence (n = 162; RR = 2.17, 95% CI = [1.18, 3.97], P = 0.01), and right eye involvement (n = 76; RR = 2.10, 95% CI = [1.14, 3.88], P = 0.02). Nonsignificant factors were age, initial best-corrected visual acuity, sex, ocular comorbidity, fellow-eye posterior vitreous detachment, previous intravitreal injection, and VMT classification with focal defined as ≤400 µ m. Mean release time was 15.3 months (n = 212). Mean best-corrected visual acuity improved from 0.34 ± 0.21 (Snellen 20/44) to 0.20 ± 0.58 logMAR (Snellen 20/32) postrelease (n = 121). Conclusion: Smaller VMT diameter, epiretinal membrane absence, and right eye involvement may support spontaneous VMT release. If patients have tolerable symptoms, clinicians may consider observation in patients with these predictive factors.
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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) | 0.002 | 0.001 |
| 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 | 0.001 |
| 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 it