Unmet needs in hereditary angioedema: an international survey of physicians
Bibliographic record
Abstract
BACKGROUND: Hereditary angioedema (HAE) is a rare and potentially life-threatening genetic disorder characterized by unpredictable attacks of angioedema. MENTALIST (UnMEt Needs in herediTAry angioedema-a gLobal physIcian perSpecTive) is the first international survey uncovering unmet needs and identifying barriers to optimal management in HAE following the latest update of the World Allergy Organization (WAO)/European Academy of Allergy and Clinical Immunology (EAACI) HAE guidelines. METHODS: This web-based survey comprised 24 questions on HAE management and unmet needs. HAE-expert physicians from the Angioedema Centers of Reference and Excellence network ranked unmet needs according to their own perspectives and their patients' perspectives, using a 10-point Likert scale ranging from 0 (not a challenge/unmet need at all) to 10 (huge challenge/unmet need). RESULTS: Of 64 respondents from 32 countries, most (91%) had > 5 years of experience in managing HAE. Overall, 48% of respondents (n = 31/64) reported that < 50% of their patients had achieved the WAO/EAACI HAE treatment goals of total disease control and "normalization" of life at the time of the survey. Implementation of consensus recommendations was found to be inconsistent across regions. Gaps in non-HAE-expert physician knowledge, treatment costs, and reimbursement for long-term prophylaxis were the highest-priority challenges according to the respondents. Burden of disease remains a challenge among patients, as reported by their physicians. CONCLUSIONS: The MENTALIST findings highlight a need for removal of barriers to HAE treatment goals and propose a call to action to improve access to treatments, for greater provision of education for physicians and patients, critical collaboration with patient organizations and industry stakeholders and ultimately to optimize HAE care.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".