Myopia Controlling using Low Dose Atropine Eye Drop
Bibliographic record
Abstract
Purpose: To determine myopic progression, axial length elongation, best-corrected visual acuity (BCVA), pupil dilation, and accommodation amplitude following 24 months of Atropine 0.01% usage among progressive myopic patients. Methods: Fifty-one progressive myopic patients (age range, 3.5-17 years) were included in the present study. Fifteen patients were excluded due to loss to follow-up (eight patients) and Atropine complications (seven patients) and 36 patients continued therapy. Myopic progression, axial length, far and near BCVA, pupil diameter, and accommodation amplitude were measured at baseline examination and repeated every 6 months up to 2 years. All patients were recommended to instill one drop of Atropine 0.01% in each eye every night. Absolute success of therapy was defined as myopic progression ≤0.50 diopter (D) and axial length growth ≤0.2 mm per year. Results: Mean myopic progression was 0.16 and 1.28 D and mean axial length change was 0.05 and 0.69 mm at months 12 and 24, respectively. Pupil dilation was 1.26 and 1.84 mm and accommodation reduction was 3.38 and 3.37 D at the same follow-ups, while BCVA was not changed. Absolute success rate for myopic progression control was 56.8% at 12 months and 70.8% at 24 months follow-up. In addition, the success rate in respect to axial length changes was 44.4% and 58.3% at the same time points. Conclusions: Atropine 0.01% can slow myopic progression and axial length elongation at least in 50% of myopic cases at 12- and 24-month follow-up with no significant complications. Therefore, Atropine therapy is recommended in cases of progressive myopia in children and teenagers.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| 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".