Ocular and adnexal anomalies in craniofacial microsomia: Type and prevalence in a multicentre cohort study
Bibliographic record
Abstract
The aim of this multicentre retrospective cohort study was to describe and categorize the types of ocular and adnexal anomalies seen in patients with craniofacial microsomia (CFM) and to determine their prevalence. In addition, the relationship between the OMENS-Plus and Pruzansky-Kaban classification for each patient and the presence of ocular anomalies was investigated. A total of 881 patients with CFM from four different craniofacial centres were included. Data on ocular anomalies were gathered from the patient charts. Ocular anomalies were present in 33.9% of patients. Four subgroups of ocular and adnexal anomalies were identified. Type I ocular anomalies were present in 22.2%, type II in 19.0%, type III in 18.4%, and type IV in 14.5%. Several potentially preventable and treatable ocular anomalies were identified. Higher OMENS-Plus classification orbit and soft tissue scores and Pruzansky-Kaban classification mandible scores were associated with an increased risk of ocular anomalies. Based on these results and the clinical implications ocular anomalies may have, we underline the importance of targeted ophthalmological screening in CFM. Healthcare professionals should be aware of the possibility of ocular anomalies in these patients, especially during the critical period for visual development.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".