Clinical outcomes and higher order aberrations of wavefront‐guided <scp>LASIK</scp> versus <scp>SMILE</scp> for correction of myopia: A systemic review and meta‐analysis
Bibliographic record
Abstract
To systematically evaluate the clinical effect of wavefront-guided laser in situ keratomileusis (WFG-LASIK) and small incision lenticule extraction (SMILE) in terms of refractive errors and high-order aberrations. A systematic literature search of PubMed, EMBASE, the Cochrane Library, Web of Science and China National Knowledge Internet was performed to identify studies evaluating the clinical outcomes of SMILE and WFG-LASIK ended in May 2022. Meta-analyses were performed according to the PRISMA guidelines. The risk of bias of the RCTs was evaluated using the Cochrane Handbook criteria, and the quality of the non-randomised controlled studies was assessed using the Newcastle-Ottawa Scale. In total, 1385 eyes (SMILE group, 750 eyes; WFG-LASIK group, 635 eyes) from 12 studies were included. The meta-analysis demonstrated that spherical aberration was smaller in the SMILE group than in the WFG-LASIK group (standardised mean difference [SMD]: -0.34, 95% confidence interval [CI]: -0.47, -0.22; p < 0.00001), and that the postoperative values of vertical coma (SMD: 0.83; 95% CI: 0.63, 1.03; p < 0.00001) and trefoil (SMD: 0.37; 95% CI: 0.02, 0.72; p = 0.04) were higher in the SMILE group compared to the WFG LASIK group. There were no significant differences in the clinical outcomes and the values of induced total higher order aberrations between the WFG-LASIK and SMILE groups (SMD: 0.05; 95% CI: -0.09, 0.19; p = 0.47). Both SMILE and WFG-LASIK were found to be safe, effective, and predictable. SMILE may induce more vertical coma and trefoil, whereas WFG LASIK may induce more spherical aberrations, but no significant differences were found in the total higher order aberrations between SMILE and WFG-LASIK.
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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 | 0.008 | 0.015 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.016 | 0.032 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".