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Record W1966569531 · doi:10.1182/blood-2012-03-378927

Clotting factor concentrate switching and inhibitor development in hemophilia A

2012· article· en· W1966569531 on OpenAlexaff
Alfonso Iorio, Paolo Puccetti

Bibliographic record

VenueBlood · 2012
Typearticle
Languageen
FieldMedicine
TopicHemophilia Treatment and Research
Canadian institutionsMcMaster University
Fundersnot available
KeywordsClotting factorMedicinePostmarketing surveillanceImmunogenicityTissue factor pathway inhibitorRisk factorInternal medicineAdverse effectPediatricsIntensive care medicineCoagulationImmunologyAntibodyTissue factor

Abstract

fetched live from OpenAlex

The development of alloantibodies or inhibitors is the most serious complication a patient with severe hemophilia can experience from treatment with clotting factor concentrates. Although common in previously untreated patients, inhibitor development is rare in multiply exposed, well-tolerized patients. There has been a nonevidence-based reluctance to change concentrate because of a perceived greater inhibitor risk after the switch, even though most patients are now likely to be using a concentrate on which they did not begin. Inhibitors in previously treated patients are observed in approximately 2 per 1000 patient/years, which makes it difficult to study and compare rates among different products. Because the baseline inhibitor risk in previously treated patients may vary over time, it is important to compare the risk in patients switching to a new product with that in a parallel control group of nonswitching patients or within a case-controlled study. The study designs imposed by regulators are suboptimal in detecting immunogenicity signals. The issue of immunogenicity of new products is likely to gain more relevance in the near future, with a call for effective postmarketing surveillance studies for all of the new engineered factor VIII concentrates with prolonged half-lives that are likely to enter clinical practice.

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 score0.246
Threshold uncertainty score0.325

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 head0.032
GPT teacher head0.295
Teacher spread0.263 · 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

Citations49
Published2012
Admission routes1
Has abstractyes

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