Ocular Biometric and Optical Coherence Tomography Parameters in Former Preterm Children: A Cohort Study
Bibliographic record
Abstract
Purpose. To compare biometric and optical coherence tomography parameters as well as refractive status in preterm children aged 4–8 years with or without retinopathy of prematurity (ROP), and evaluate their correlations with age and gender‐matched full‐term children. Methods. Retrospective comparative cohort study of four groups of children. Children with a history of preterm birth, including ROP who received intravitreal bevacizumab (IVB) treatment, children with a history of ROP that regressed without treatment and those with no history of ROP were compared to age and gender‐matched full‐term children as a control group. Best corrected visual acuity (BCVA), spherical equivalent of refraction (SE), macular and choroidal thickness, as well as biometric parameters was measured. Results. A total of 120 eyes of 120 children (30 children in each group) were included. There was no significant difference in BCVA, SE, and subjective cylinder between groups (p = 0.05, p = 0.3, p = 0.6, respectively). Axial length was significantly shorter, and the cornea was steeper in both ROP groups than in other groups (p = 0.001, p < 0.001, respectively). The central macular thickness was significantly thicker in the treated, regressed ROP and preterm groups than in full‐term children (p < 0.001). The gestational age was negatively correlated with macular thickness in both treated and regressed ROP groups (r = −0.517; p = 0.003, r = − 0.490; p = 0.006, respectively). Conclusions. Children with a history of ROP had a shorter axial length, steeper cornea, and thicker macula that correlated with lower gestational age.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".