Microinterventional endocapsular nucleus disassembly: novel technique and results of first-in-human randomised controlled study
Bibliographic record
Abstract
AIM: To assess the safety and efficacy of microinterventional endocapsular nuclear fragmentation in moderate to severe cataracts. METHODS: This was a prospective single-masked multisurgeon interventional randomised controlled trial (ClinicalTrials.gov NCT02843594) where 101 eyes of 101 subjects with grade 3‒4+ nuclear cataracts were randomised to torsional phacoemulsification alone (controls) or torsional phacoemulsification with adjunctive endocapsular nuclear fragmentation using a manual microinterventional nitinol filament loop device (miLOOP group). Outcome measures were phacoemulsification efficiency as measured by ultrasound energy (cumulative dispersed energy (CDE) units) and fluidics requirements (total irrigation fluid used) as well as incidence of intraoperative and postoperative complications. RESULTS: Only high-grade advanced cataracts were enrolled with more than 85% of eyes with baseline best corrected visual acuity (BCVA) of 20/200 or worse in either group. Mean CDE was 53% higher in controls (32.8±24.9 vs 21.4±13.1 with miLOOP assistance) (p=0.004). Endothelial cell loss after surgery was low and similar between groups (7‒8%, p=0.561) One-month BCVA averaged 20/27 Snellen in miLOOP eyes and 20/24 in controls. No direct complications were caused by the miLOOP. In two cases, capsular tears occurred during IOL implantation and in all remaining cases during phacoemulsification, with none occurring during the miLOOP nucleus disassembly part of the procedure. CONCLUSIONS: Microinterventional endocapsular fragmentation with the manual, disposable miLOOP device achieved consistent, ultrasound-free, full-thickness nucleus disassembly and significantly improved overall phaco efficiency in advanced cataracts. TRIAL REGISTRATION NUMBER: NCT02843594.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 teacher head, 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".