Ophthalmologic abnormalities in institutionalized Congolese children with cognitive impairment
Bibliographic record
Abstract
OBJECTIVES: To determine the frequency and types of ophthalmologic anomalies in children with cognitive impairment, identify the causes of visual impairment in these children, and assess the relationship between the severity of cognitive impairment and ophthalmologic anomalies. METHODS: A cross-sectional study was carried out between October 2023 and June 2024 on 80 children 7 to 17 years old with cognitive impairment and institutionalized in two centers in Kinshasa. Participants underwent a complete ophthalmologic examination and cognitive assessment using the Montreal Cognitive Assessment (MoCA) test. RESULTS: The median (interquartile range) age of the children was 14 (11-16) years. 55% were boys. Cognitive impairment was mild in 41.2%, moderate in 33.8%, and severe in 25% of the children. Overall, 74 (92.5%) children had at least one ophthalmologic abnormality, and 43.8% had multiple ophthalmologic abnormalities. Refractive errors (82.5%), stereoscopic disorders (22.5%) and strabismus (12.6%) were the most frequent disorders. Twenty-seven (33.7%) children had vision impairment. The causes of vision impairment were refractive errors (46.7%), strabismus amblyopia (20%), and cataract (13.3%). There was a significant association between the severity of cognitive impairment and both visual impairment and defective stereopsis (p = 0.035). CONCLUSIONS: Ophthalmologic manifestations are frequent in children with cognitive deficits. They are dominated by ametropia. A substantial proportion of these children are visually impaired. Periodic ophthalmologic screening of these children via conventional pediatric health system or school health services is recommended.
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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 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".