Patterned cutaneous hypopigmentation phenotype characterization: A retrospective study in 106 children
Bibliographic record
Abstract
BACKGROUND: Cutaneous patterned hypopigmentation's phenotype is highly variable and may be associated with extracutaneous anomalies. OBJECTIVE: We evaluated the phenotypic and clinical characteristics of patients with cutaneous patterned hypopigmentation to determine whether certain patterns were more likely to be associated with underlying anomalies. METHODS: The charts of 106 children with cutaneous patterned hypopigmentation were reviewed retrospectively (2007-2018) at Sainte-Justine University Hospital Centre, in Montreal, Canada. Retrieved information included sex, age at diagnosis, phototype, pattern, and distribution of the cutaneous lesions and the presence of extracutaneous findings. Data were recorded on a software tool which collects and analyzes phenotypic information. RESULTS: The predominant types of cutaneous patterned hypopigmentation were along Blaschko's lines in narrow (38.7%) and broad bands (53.8%). Mixed patterns were observed in 22.5% of children. The anterior trunk and posterior trunk were most frequently affected (69% and 56%, respectively). Extracutaneous involvement, especially neurological and developmental, was present in 28.3% of patients and was significantly associated with ≥ 4 involved body sites. CONCLUSION: Distribution and types of cutaneous patterned hypopigmentation were not predictive of extracutaneous findings, with the exception of multiple sites involvement and possibly centrofacial location and blocklike lesions. Follow-up until school entry should help identify subtler associated extracutaneous anomalies.
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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 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| 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".