Visual and Ocular Characteristics of Anisometropic Children
Bibliographic record
Abstract
Purpose: To compare the demographic and ocular characteristics of patients with low and high levels of anisometropia compared with non-anisometropic individuals. Methods: This cross-sectional study was conducted on 1803 individuals (age range, 1 to 30 years) examined at strabismus clinics between January 2019 and December 2020. Of these, 203 subjects had anisometropia (11.2%); 66 cases were excluded due to the history of prior ocular surgery except from strabismus surgery. Finally, data from 137 subjects were analyzed. Spherical or cylindrical differences of 1.50 or 3.00D between the two eyes were defined as low or high anisometropia, respectively, and isometropic subjects (n = 1600) served as controls. Results: No significant difference was observed between cases and controls regarding age (10.25 ± 8.41 vs. 9.2 ± 1.7 years; P = 0.133) and sex (P = 0.051). History of ocular surgery was present in 33% of anisometropic patients versus 0.8 % of isometropic cases. The rate of amblyopia was 83% and 2.3% in anisometropic and non-anisometropic groups, respectively. Best corrected visual acuity (BCVA) was comparable in amblyopic eyes in both study groups, while BCVA of nonamblyopic eyes of non-anisometropic subjects was better (non-anisometropic: 0.01 ± 0.01 vs. anisometropic: 0.06 ± 0.17 LogMAR; P = 0.001). Eye deviation was significantly more prevalent among anisometropic patients (36.5% vs. 3.25%, P < 0.001) and exotropia was the common type of deviation. Anisohyperopia and anisomyopia were the most common refractive errors under low and high anisometropia categories, respectively. Simultaneous manifestation of amblyopia and strabismus were observed in 30.6% of anisometropic cases, while only 0.7% of subjects with isometropia had a similar status (P < 0.001). Conclusion: High rates of amblyopia and strabismus in anisometropic subjects, especially with higher degrees of anomaly, indicate the necessity of early visual acuity and refractive error screening to improve detection and enhance the outcomes of treatment.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.002 | 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".