Reductions in medical visits and hospitalizations following berotralstat initiation in patients with hereditary angioedema in the United States
Bibliographic record
Abstract
BACKGROUND: Hereditary angioedema (HAE) is a rare disease characterized by unpredictable recurrent, debilitating, and potentially fatal attacks of subcutaneous and submucosal tissue swelling. OBJECTIVE: To evaluate all-cause, angioedema-related, and HAE attack-related medical visits and hospitalizations before and after initiation of berotralstat long-term prophylaxis (LTP) for patients with HAE in the United States. METHODS: values from generalized estimating equation Poisson regression models with robust SEs. Study limitations included the inability to distinguish HAE types and the uncertainty of whether a dispensed medication was consumed or taken as prescribed. RESULTS: = 0.002). Results were similar among subgroups of patients defined by HAE treatment history, including patients who were LTP-experienced (n = 126) and LTP-naive but on-demand treatment-experienced (n = 67). CONCLUSIONS: Prophylactic treatment of HAE with berotralstat was associated with significant reductions in all-cause HRU, including decreases to angioedema-related and HAE attack-related medical visits, hospitalizations, and administration of on-demand treatment.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".