Bimanual microincisional phacoemulsification: the future of cataract surgery?
Bibliographic record
Abstract
PURPOSE OF REVIEW: Bimanual microincisional cataract surgery has recently become a procedure of interest among cataract surgeons, and a number of trials have shown its potential as a minimally invasive cataract surgery. The purpose of this review is to examine the studies that have been published to date and to evaluate the potential of bimanual phacoemulsification as a method of cataract extraction. RECENT FINDINGS: Recent studies have reinforced the safety of bimanual phacoemulsification. In particular, recently published studies have focused on evaluating various phacoemulsification technologies and their safety when used in bimanual phacoemulsification. Newly developed rollable hydrophilic acrylic ThinOptX lenses have been shown to be implantable in 2.2-mm incisions safely with good visual outcomes. SUMMARY: Bimanual phacoemulsification has been a potential technique for a number of years, but only recently have the technology, software, and technique advanced sufficiently to make bimanual phacoemulsification a feasible method of cataract extraction. Although the main disadvantage to bimanual phacoemulsification remains the lack of intraocular lenses that can fit through microincisions, necessitating the enlargement of corneal wounds for intraocular lens implantation, bimanual phacoemulsification has a number of advantages over traditional small-incision phacoemulsification. Theses advantages have been a source of interest for cataract surgeons and surgical companies who are now developing technologies that will permit the performance of truly microincisional cataract surgery.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".