Vitreoretinal instruments: vitrectomy cutters, endoillumination and wide-angle viewing systems
Bibliographic record
Abstract
There have been many advances in vitreoretinal surgery since Machemer introduced the concept of pars plana vitrectomy, in 1971. Of particular interest are the changes in the vitrectomy cutters, their fluidics interaction, the wide-angle viewing systems and the evolution of endoillumination through the past decade and notably in the last few years. The indications of 27-gauge surgery have expanded, including more complex cases. Cut rates of up to 16,000 cuts per minute are already available. New probe designs and pump technology have allowed duty cycle performances of near 100% and improved flow control. The smaller vitrectomy diameter can be positioned between narrow spaces, allowing membrane dissection and serving as a multifunctional instrument. Enhanced endoillumination safety can be achieved by changing the light source, adding light filters, increasing the working distance and understanding the potential interactions between light and vital dyes commonly used to stain the retina. Wide-angle viewing systems (contact, non-contact or a combination of both) provide a panoramic view of the retina. Non-contact systems are assistant-independent, while contact systems may be associated with better image resolution. This review will cover some current aspects on vitrectomy procedures, mainly assessing vitrectomy cutters, as well as the importance of endoillumination and the use of wide-angle viewing systems.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.003 |
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".