The Efficacy of Combination Therapy Using Atropine and Orthokeratology in Limiting Myopia Progression in Comparison to Atropine and Orthokeratology Monotherapy—A Systematic Review
Bibliographic record
Abstract
Myopia a growing global public health issue, particularly amongst children and adolescents raised the issues of addressing not only the diseases up-going trend but also its management effectiveness. This review article is meant to evaluate the efficacy of combination therapy using atropine and orthokeratology in limiting myopia progression in comparison to atropine and orthokeratology monotherapy. In this study, we accessed PubMed, Web of Science and other databases to search for the articles address the effectiveness of combined therapy in myopia management rather than its monotherapy. Data was collected systematically from 8 studies on combination therapy, 6 on Orthokeratology alone, and 6 on Atropine monotherapy focusing changes in axial length of the individuals underwent the prescribed therapies. Statistical analysis was done using Python, Pandas Scikit Learn, SciPy & MatPlotLib for data visualization, accuracy and efficiency to get valid test results. This review article study revealed that combination therapy resulted in a mean reduction in axial length of 0.10 mm to 0.28 mm, significantly outperforming Atropine monotherapy (0.02 mm to 0.87 mm) and Orthokeratology alone (0.19 mm to 0.36 mm). The combination therapy demonstrated large effect sizes (Cohen’s d of 1.59 and 1.95) compared to individual treatments indicating a synergistic effect. However, variability in study designs and the limited availability of long-term data reinforces the need for further research. This review highlights the potential of combination therapy as a superior approach to myopia management, advocating for its consideration in clinical practice to mitigate the growing burden of myopia Keywords: Myopia Management, Atropine, Orthokeratology, Combination Therapy, Review
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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 | 0.004 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.008 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".