Reply: Outcomes of femtosecond laser–assisted cataract and refractive lens surgery in patients with prior radial keratotomy
Bibliographic record
Abstract
We thank Dick and Schultz for their kind comments on our article and welcome further exploration into this fascinating area of study. The incidence of incomplete anterior capsular tears in our series of patients with radial keratotomy was more commonly encountered with our laser settings than reported with Dick's laser setting series in 2016. We welcome the suggested refinements on alternative femtosecond laser settings, which may overcome some of the complications experienced with the settings used at our center. Larger numbers are required to ascertain its safety and efficacy using these proposed settings. We also agree that a perfectly centered and round anterior capsulotomy is a vital ingredient for handling these potentially surgically challenging cases and would allow for a better chance of optic capture should the posterior capsule integrity be compromised. The use of trypan blue was not routinely performed in our series but would likely provide for a clearer assessment of anterior capsulotomy integrity intraoperatively, thereby allowing the surgeon to proceed with more caution where necessary. Although every case in our series underwent a complete slitlamp evaluation for scar density, we did not enlarge the capsulotomy size, which may have bypassed the scar if the scars were not present in the periphery. We look forward to modifying our practice to encompass this change and assessing the effectivity of this modification. In summary, femtosecond laser surgery in patients with radial keratotomy should be approached with caution, particularly where the clinical assessment finds radial keratotomy incisional scars or opacity, especially those with epithelial inclusions. These are potential sources of incomplete laser penetrance, and further research into laser setting modifications should be undertaken to ascertain safety and efficacy.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.006 |
| Insufficient payload (model declined to judge) | 0.001 | 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".