Vascular Anomalies Classification: Recommendations From the International Society for the Study of Vascular Anomalies
Bibliographic record
Abstract
Vascular anomalies represent a spectrum of disorders from a simple "birthmark" to life- threatening entities. Incorrect nomenclature and misdiagnoses are commonly experienced by patients with these anomalies. Accurate diagnosis is crucial for appropriate evaluation and management, often requiring multidisciplinary specialists. Classification schemes provide a consistent terminology and serve as a guide for pathologists, clinicians, and researchers. One of the goals of the International Society for the Study of Vascular Anomalies (ISSVA) is to achieve a uniform classification. The last classification (1997) stratified vascular lesions into vascular malformations and proliferative vascular lesions (tumors). However, additional disease entities have since been identified that are complex and less easily classified by generic headings, such as capillary malformation, venous malformation, lymphatic malformation, etc. We hereby present the updated official ISSVA classification of vascular anomalies. The general biological scheme of the classification is retained. The section on tumors has been expanded and lists the main recognized vascular tumors, classified as benign, locally aggressive or borderline, and malignant. A list of well-defined diseases is included under each generic heading in the "Simple Vascular Malformations" section. A short definition is added for eponyms. Two new sections were created: one dealing with the malformations of individually named vessels (previously referred to as "truncular" malformations); the second groups lesions of uncertain or debated nature (tumor versus malformation). The known genetic defects underlying vascular anomalies are included in an appendix. This classification is meant to be a framework, acknowledging that it will require modification as new scientific information becomes available.
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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 | 0.012 | 0.035 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.019 | 0.013 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.005 | 0.003 |
| Research integrity | 0.004 | 0.008 |
| Insufficient payload (model declined to judge) | 0.017 | 0.019 |
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".