OUTCOMES OF VITRECTOMY IN TERSON SYNDROME
Bibliographic record
Abstract
PURPOSE: To characterize the presentation of Terson syndrome, the occurrence of a vitreous hemorrhage in association with intracranial hemorrhage, and report on the outcomes of vitrectomy at two major centers in Canada. METHODS: Retrospective chart review of consecutive patients with Terson syndrome undergoing vitrectomy by retina specialists over the last 10 years. Primary outcome was the change in best-corrected visual acuity (BCVA) at 3 months from baseline. Secondary outcomes included the association between baseline BCVA and final BCVA, and the association between final BCVA and timing of surgery (early vs. later than 90 days). RESULTS: A total of 14 eyes of 11 patients were included. The mean time between observation of intraocular hemorrhage and vitrectomy was 160 days. Baseline preoperative BCVA was logarithm of the minimum angle of resolution 1.57 ± 1.03 (Snellen 20/740), which improved to logarithm of the minimum angle of resolution 0.53 ± 0.82 (Snellen 20/70) at the final postoperative follow-up, P = 0.01. Baseline BCVA was not significantly correlated with final BCVA, Spearman's rho = 0.016, P = 0.957. Final BCVA did not significantly differ between those who had surgery before 90 days compared with after 90 days, P = 0.087. CONCLUSION: Vitrectomy is safe and effective and should be considered for nonclearing vitreal bleeding due to Terson syndrome. Ocular hemorrhaging in Terson syndrome can be observed conservatively for spontaneous improvement without the risk of reduced visual potential. Ophthalmic evaluation should be considered promptly after intracranial hemorrhage.
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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 | 0.000 | 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".