Comparison of changes in corneal endothelial cell density and central corneal thickness between conventional and femtosecond laser-assisted cataract surgery: a randomised, controlled clinical trial
Bibliographic record
Abstract
Background/Aim To identify changes in endothelial cell density (ECD) and central corneal thickness (CCT) in eyes undergoing femtosecond laser-assisted cataract surgery (FLACS) compared with conventional phacoemulsification surgery (CPS). Methods This is an intraindividual randomised, controlled clinical trial. One eye was randomised to receive FLACS, while the contralateral eye of the same patient received CPS. The femtosecond laser pretreatment included creating main and side-port corneal incisions, capsulotomy and lens fragmentation. Non-contact endothelial cell microscopy and pachymetry were performed preoperatively and at postoperative day 1, week 1, month 1 and month 3. Results A total of 134 paired eyes from 67 patients were included in the analysis. ECD was not significantly different between the two groups at either postoperative month 1 (2370±580 cells/mm2and 2467±564 cells/mm2in FLACS and CPS groups, respectively; p=0.18) or at postoperative month 3 (2374±527 cells/mm2and 2433±526 cells/mm2in FLACS and CPS groups, respectively; p=0.19). No significant difference was observed in the mean CCT values between the two groups over the follow-up period (p>0.05). Conclusion Postoperative corneal ECD and CCT were comparable between FLACS and CPS during the 3 months’ follow-up period.
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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 | 0.006 | 0.007 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".