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Record W4390113708 · doi:10.2217/frd-2023-0022

Garadacimab for the prevention of hereditary angioedema attacks: a plain language summary of the VANGUARD study

2023· article· en· W4390113708 on OpenAlexaff
Timothy Craig, Avner Reshef, H. Henry Li, Joshua Jacobs, Jonathan A. Bernstein, Henriette Farkas, William H. Yang, Erik S.G. Stroes, Isao Ohsawa, Raffi Tachdjian, Michael Manning, William R. Lumry, Inmaculada Martinez Saguer, Emel Aygören‐Pürsün, Bruce Ritchie, Gordon Sussman, John Anderson, Kimito Kawahata, Yusuke Suzuki, Petra Staubach, Regina Treudler, Henrike Feuersenger, Lolis Wieman, Iris Jacobs, Markus Magerl

Bibliographic record

VenueFuture Rare Diseases · 2023
Typearticle
Languageen
FieldMedicine
TopicCoagulation, Bradykinin, Polyphosphates, and Angioedema
Canadian institutionsSt. Michael's HospitalUniversity of AlbertaOttawa Allergy Research CorporationUniversity of Ottawa
Fundersnot available
KeywordsHereditary angioedemaVanguardPlaceboMedicineC1-inhibitorAngioedemaSurgeryInternal medicineDermatologyAlternative medicinePathology

Abstract

fetched live from OpenAlex

What is this summary about? This summarizes an article about the clinical study ‘VANGUARD’ that was published in The Lancet journal in February 2023. Hereditary angioedema (HAE) is a rare genetic disease that causes swellings throughout the body (called HAE attacks). HAE attacks in the upper airways (including the tongue and vocal cords) can be life threatening by making breathing difficult. HAE attacks may occur frequently and without warning, and people with HAE have a lower quality of life than other people. In the VANGUARD study, researchers tested the safety of a new medicine called garadacimab and whether it could prevent HAE attacks. Garadacimab was injected subcutaneously (just under the skin) with a needle once a month. What were the results? In the VANGUARD study, patients took garadacimab or placebo (an identical-looking dummy substance with no medical effect, used for comparison). The aim was to see if garadacimab could prevent HAE attacks better than placebo. Patients taking garadacimab had very few or no HAE attacks, but those taking placebo carried on having attacks. Garadacimab gave protection from HAE attacks shortly after it was first used, and this carried on for the 6 months of treatment. Most patients taking garadacimab (62%) had no HAE attacks throughout the 6 months of treatment (were attack free), but 100% of patients taking placebo had HAE attacks throughout the study. More patients taking garadacimab (82%) than placebo (33%) had a ‘good’ or ‘excellent’ experience living with HAE. Patients taking garadacimab and placebo had similar rates of side effects. Only 5% (2 out of 39) of patients taking garadacimab had discomfort or skin changes at the place of injection compared with 12% (3 out of 25) taking placebo. What do the results mean? Taking garadacimab once a month helps prevent HAE attacks from happening, with most patients being attack free throughout the 6 months of treatment. Garadacimab had very few and mostly mild or moderate side effects. Overall, garadacimab is a beneficial treatment for preventing HAE attacks.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.377
Threshold uncertainty score0.390

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.016
GPT teacher head0.299
Teacher spread0.283 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2023
Admission routes1
Has abstractyes

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