Transepithelial versus epithelium-off corneal collagen cross-linking for corneal ectasia: protocol for a systematic review, meta-analysis and trial sequential analysis of randomised controlled trials
Bibliographic record
Abstract
INTRODUCTION: Corneal ectasias are progressive, degenerative ocular diseases defined by abnormal structural changes in the cornea, leading to distortion of vision and substantial reduction in quality of life. Corneal collagen cross-linking (CXL) increases the biomechanical rigidity of the cornea and has been shown to halt ectatic processes. The established CXL protocol requires removal of the corneal epithelium. However, some surgeons have proposed transepithelial approaches to enhance patient recovery and minimise adverse events. Whether novel transepithelial approaches are as effective in arresting ectasia as the established epithelium-off protocol remains unclear. This study will systematically review the evidence on transepithelial CXL approaches and compare it to the epithelium-off protocol. METHODS AND ANALYSIS: We will include randomised controlled trials (RCTs) comparing transepithelial and epithelium-off CXL for any corneal ectasia. We will search 16 electronic databases including MEDLINE and Embase, as well as the grey literature. Two reviewers will independently screen search results to identify eligible studies, complete data abstraction and conduct quality assessment. We will assess the quality of individual RCTs using the Cochrane risk of bias assessment tool. Our primary outcome will be the change in maximal keratometry at 12 months after treatment, and we will examine 11 additional outcomes. We will summarise our analyses by measures of association (relative risk or odds ratio) and corresponding 95% confidence intervals (CIs) for dichotomous outcomes and weighted mean differences with 95% CIs for continuous outcomes. Prespecified subgroup analyses will be conducted to explore heterogeneity. The overall quality of evidence will be rated using the Grading of Recommendations Assessment, Development and Evaluation approach. ETHICS AND DISSEMINATION: Ethics approval is not required for this systematic review as it draws from previously published data. Results of the study will be submitted to a peer-reviewed journal for publication and discussed at conferences and seminars. PROSPERO REGISTRATION NUMBER: CRD42018102069.
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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 | 0.061 | 0.115 |
| Meta-epidemiology (narrow) | 0.008 | 0.005 |
| Meta-epidemiology (broad) | 0.044 | 0.034 |
| Bibliometrics | 0.011 | 0.011 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.010 | 0.009 |
| Open science | 0.006 | 0.005 |
| Research integrity | 0.009 | 0.007 |
| Insufficient payload (model declined to judge) | 0.047 | 0.005 |
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".