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Record W2971686951 · doi:10.1056/nejmoa1902678

Safety and Efficacy of Mitapivat in Pyruvate Kinase Deficiency

2019· article· en· W2971686951 on OpenAlexaff
Rachael F. Grace, Christian Rosé, D. Mark Layton, F. Galactéros, Wilma Barcellini, D. Holmes Morton, Eduard J. van Beers, Hassan M. Yaish, Yaddanapudi Ravindranath, Kevin H.M. Kuo, Sujit Sheth, Janet L. Kwiatkowski, Ann Barbier, Susan Bodie, Bruce A. Silver, Lei Hua, Charles Kung, Peter Hawkins, Marie-Hélène Jouvin, Chris Bowden, Bertil Glader

Bibliographic record

VenueNew England Journal of Medicine · 2019
Typearticle
Languageen
FieldMedicine
TopicErythrocyte Function and Pathophysiology
Canadian institutionsUniversity of Toronto
FundersAgios Pharmaceuticals
KeywordsMedicinePyruvate kinase deficiencyPyruvate kinaseInternal medicineGlycolysisMetabolism

Abstract

fetched live from OpenAlex

BACKGROUND: and leads to congenital hemolytic anemia. Mitapivat is an oral, small-molecule allosteric activator of pyruvate kinase in red cells. METHODS: In this uncontrolled, phase 2 study, we evaluated the safety and efficacy of mitapivat in 52 adults with pyruvate kinase deficiency who were not receiving red-cell transfusions. The patients were randomly assigned to receive either 50 mg or 300 mg of mitapivat twice daily for a 24-week core period; eligible patients could continue treatment in an ongoing extension phase. RESULTS: mutation and were associated with the red-cell pyruvate kinase protein level at baseline. CONCLUSIONS: The administration of mitapivat was associated with a rapid increase in the hemoglobin level in 50% of adults with pyruvate kinase deficiency, with a sustained response during a median follow-up of 29 months during the extension phase. Adverse effects were mainly low-grade and transient. (Funded by Agios Pharmaceuticals; ClinicalTrials.gov number, NCT02476916.).

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.014
GPT teacher head0.264
Teacher spread0.250 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNon-randomized trial
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

Citations159
Published2019
Admission routes1
Has abstractyes

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