American College of Rheumatology Guidance Statement for Diagnosis and Management of <scp>VEXAS</scp> Developed by the International <scp>VEXAS</scp> Working Group Expert Panel
Bibliographic record
Abstract
OBJECTIVE: Vacuoles E1 enzyme X-linked autoinflammatory somatic syndrome (VEXAS) is a recently identified rare genetic disorder associated with somatic mutations in the UBA1 gene. VEXAS presents with a combination of inflammatory and hematologic manifestations, leading to increased morbidity and mortality. METHODS: Given the variability in disease presentation and the limited number of studies to date, no clinical documents currently exist to provide guidance to health care providers about the management of VEXAS. To address this gap, we formed an international multidisciplinary panel of VEXAS experts. RESULTS: Through formalized meetings and a voting process, the group developed consensus clinical guidance considerations for the management of VEXAS. These considerations offer practical advice on several key topics: (1) clinical features of VEXAS, (2) UBA1 screening methods, (3) the diagnosis of myelodysplastic syndromes (MDSs) in patients with VEXAS, and (4) prognosis and management. The aim is to provide expert guidance on which patients to test, how to test for VEXAS, how to approach MDS in the context of VEXAS, and considerations for management. CONCLUSION: This work marks the first formal international consensus guidance for VEXAS and is intended to be used as a resource for clinicians seeking to understand the disease and its management.
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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 | 0.016 | 0.046 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.008 | 0.011 |
| Insufficient payload (model declined to judge) | 0.011 | 0.009 |
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".