International consensuses and guidelines on rhegmatogenous retinal detachment (RRD) surgery by the Asia-Pacific Vitreo-retina Society (APVRS), the Academy of Asia-Pacific Professors of Ophthalmology (AAPPO) and the Academia Retina Internationalis (ARI)
Bibliographic record
Abstract
PURPOSE: To establish expert consensus on the contemporary surgical management of rhegmatogenous retinal detachment (RRD) using a structured Delphi approach. METHODS: A panel of experienced vitreoretinal surgeons participated in a multiround Delphi survey evaluating statements related to surgical approach, vitrectomy techniques, tamponade selection, anesthesia, postoperative care, special populations, and future technologies. Consensus was defined as ≥ 75 % agreement. Voting outcomes were analyzed to identify areas of agreement and topics requiring further discussion. RESULTS: Strong consensus emerged on tailoring surgical choice to patient age, lens status, and retinal break characteristics. Scleral buckle (SB) was preferred in younger, phakic patients, while pars plana vitrectomy (PPV) was favored in pseudophakic eyes and complex detachments. Pneumatic retinopexy was supported for limited superior breaks. Small-gauge vitrectomy (23-27 gauge, G), meticulous peripheral vitreous management, and judicious use of perfluorocarbon liquids were widely endorsed. Postoperative positioning, careful intraocular pressure monitoring, and early intervention for macula-on detachments were emphasized. Moreover, macula-off retinal detachment (RD) may carry good prognosis especially in young patients. Areas of ongoing debate included the comparative benefit of PPV versus SB depending on lens status, the default use of silicone oil in complex detachments, and adoption of 27 G+ instruments in pediatric cases. Emerging technologies, including widefield imaging, intraoperative optical coherence tomography, artificial intelligence-assisted analysis, and pharmacologic adjuvants, were recognized as promising but require further validation. CONCLUSIONS: This Delphi study provides structured guidance on RRD management while identifying areas of ongoing debate. Consistently, individualized surgical strategy, meticulous vitreous management, and careful postoperative care remain central to optimizing anatomical and functional outcomes, highlighting the importance of clinical judgment in evolving surgical practice.
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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 | 0.126 | 0.113 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.009 | 0.006 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.005 | 0.007 |
| Research integrity | 0.006 | 0.006 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".