Factors Affecting the Efficacy of Botulinum Toxin Injection in the Treatment of Infantile and Partially Accommodative Esotropia
Bibliographic record
Abstract
Abstract PURPOSE: We aimed to investigate the effect of botulinum toxin (BT) injection on the treatment of infantile and partially accommodative esotropia (PAET). METHODS: This retrospective cohort study included patients who received BT injections for infantile and PAET between January 2015 and December 2018. Treatment was considered successful if orthotropia, consecutive exotropia, or esotropia within 10 prism diopters (PD) was achieved. RESULTS: The overall success rate was 47.4%, with a mean follow-up period of 27.8 months in 403 children. BT treatment was considered successful in 37.1% of cases of infantile esotropia and 53.1% of cases of partially accommodative esotropia. The average deviation angle before starting treatment was 35.5 ± 13.9 PD. Side effects 1 week after BT injections included transient overcorrection (63.8%) and transient ptosis (41.7%). There were no significant differences in the success rates between the different doses of BT ( P = 0.69). The angle of deviation at presentation was significantly associated with the success rate of BT injection (failed group, mean: 38.1 ± 15.3 PD vs. success group, mean: 32.6 ± 11.6 PD; P < 0.001). Other factors associated with higher success rates were overcorrection at 1 week and PAET, while multivariate logistic regression analysis showed that a smaller angle of deviation and overcorrection (1 week after injection) were associated with a higher success rate. CONCLUSION: A smaller angle of deviation and transient overcorrection were associated with a higher success rate, and no significant difference was observed in the success rates of different BT doses.
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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 | 0.005 |
| 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".