Defining vascular anomaly phenotypes in children based on a systematic literature search: A critical step in developing a single severity score for interventional clinical trials
Bibliographic record
Abstract
INTRODUCTION: Genetically targeted drugs in vascular anomalies (VA) are used despite the absence of a validated severity score. The aim of this study was to evaluate the feasibility of grouping phenotypic VA clinical characteristics into a single severity score. METHODS: A systematic literature review including children treated with sirolimus accompanied by a detailed description of phenotype and management was conducted. Demographic data and clinical features were extracted to define distinct categories of phenotypes. RESULTS: Children with VA display two main phenotypes regardless of VA subtype, which may overlap. A systemic phenotype results from direct invasion and compression of vital structures generally leading to hospitalization and aggressive management in infancy. A functional phenotype is associated with chronic pain and disability manifesting mainly during early adolescence and managed in the outpatient setting. CONCLUSION: The two distinct phenotypes described could be the basis for developing a unified scoring system for VA severity assessment.
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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 | 0.025 | 0.058 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.006 |
| Bibliometrics | 0.014 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".