Two-year outcomes of different subretinal fluid drainage techniques during vitrectomy for fovea-off rhegmatogenous retinal detachments: ELLIPSOID-2 study
Bibliographic record
Abstract
BACKGROUND: The purpose of the study is to compare visual acuity, complications and outer retinal integrity following subretinal fluid (SRF) drainage from the peripheral retinal breaks (PRBs) versus posterior retinotomy (PR) versus perfluorocarbon liquid (PFCL) for macula-off rhegmatogenous retinal detachments (RRDs) at 2 years post-surgery. METHODS: Retrospective analysis of 300 consecutive patients with primary RRD undergoing 23-gauge pars plana vitrectomy with SRF drainage through (1) PRB (n=100), (2) PR (n=100) or (3) with PFCL (n=100). Primary outcomes were visual acuity (best-corrected visual acuity (BCVA)) and complications (cystoid macular oedema (CMO) and epiretinal membrane (ERM)). Secondary outcomes were discontinuity of the external limiting membrane (ELM), ellipsoid zone (EZ) and interdigitation zone (IDZ) at 2 years post-surgery. RESULTS: Mean (±SD) logMAR BCVA at 24 months was better in the PRB compared with PR and PFCL, with PFCL having the worst BCVA (PRB 0.5±0.6; PR 0.7±0.5; PFCL 0.9±0.7, p=0.001). CMO was higher with PFCL (PRB 29.7%; PR 30.2%; PFCL 45.9%, p=0.0015) and ERM formation was higher in PR (PRB 62.6%; PR 93.0%; PFCL 68.9%, p=0.002). There were no differences in ELM or EZ discontinuity. However, IDZ discontinuity was higher in PFCL (PRB 34%; PR 27%; PFCL 46%, p=0.002) at 2 years. CONCLUSIONS: Visual acuity was worse and discontinuity of the IDZ and CMO was greater in eyes with PFCL-assisted drainage compared with PRB or PR. Drainage technique may impact long-term visual acuity and photoreceptor integrity.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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 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".