Retrospective analysis of actual LASIK flap diameter compared with microkeratome ring size performed by different surgeons
Bibliographic record
Abstract
PURPOSE: To evaluate the difference in the diameter between microkeratome ring and actual laser in situ keratomileusis (LASIK) flap size by 4 different surgeons using 3 different microkeratomes in comparison to preoperative keratometry. SETTING: Gimbel Eye Centre, Calgary, Alberta, Canada. METHODS: A retrospective analysis of 6667 consecutive LASIK surgeries performed at the Gimbel Eye Centre between 1998 and 2002 was conducted. The study compared the difference in the actual LASIK flap diameter and microkeratome ring size for 3 Hansatome microkeratomes indicated by serial numbers 2230, 3048, and 3084 in comparison to the preoperative keratometry. The surgeries were performed by 4 surgeons from the Centre. RESULTS: A statistically significant correlation was found between the actual flap size and the microkeratome ring size. The deviation increased with corneal steepness (#2230: r = 0.45, P<.001; #3048: r = 0.28, P<.001; #3084: r = 0.23, P<.001). The mean difference between actual flap size and the microkeratome ring size was 0.647 mm, 0.808 mm, and 0.916 mm for Hansatome microkeratome #2230, #3048, and #3084, respectively. The actual flap was larger than the microkeratome ring size in 92.8%, 93.8%, and 97.4% of eyes, respectively. The mean difference between microkeratome ring size and measured LASIK flap size was consistently significantly different (P<.0001) per surgeon for all microkeratomes. CONCLUSIONS: Estimation of the flap size is an important issue while selecting ring size and planning the treatment zone. In this study, the actual flap size was larger than the ring size for all surgeons and all 3 Hansatome microkeratomes. Higher preoperative keratometry values achieved larger flaps than those with lower keratometry values.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".