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Record W2135299409 · doi:10.1155/2013/901975

Risk Factors for High-Titer Inhibitor Development in Children with Hemophilia A: Results of a Cohort Study

2013· article· en· W2135299409 on OpenAlexaff
Susan Halimeh, Christoph Bidlingmaier, Christine Heller, Sven Gutsche, Susanne Holzhauer, Gili Kenet, Karin Kurnik, Daniela Manner, Alfonso Iorio, Ulrike Nowak‐Göttl

Bibliographic record

VenueBioMed Research International · 2013
Typearticle
Languageen
FieldMedicine
TopicHemophilia Treatment and Research
Canadian institutionsMcMaster University
FundersWestfälische Wilhelms-Universität Münster
KeywordsMedicineHazard ratioTiterInternal medicineConfidence intervalCohortPediatricsImmunologyAntibody

Abstract

fetched live from OpenAlex

Among the discussed risk factors for high-titre inhibitor (HRI) development in patients with hemophilia A (HA) are high dose FVIII replacement therapy and use of recombinant FVIII concentrates (rFVIII). The aim of this study was to evaluate the aforementioned risk factors for HRI development in children with hemophilia A ≤2%. About 288 ascertained PUPs (Israel and Germany) were followed after initial HA diagnosis over 200 exposure days. Inhibitor-free survival, hazard ratios (HR), and 95% confidence intervals (CIs) were calculated. Adjustment was performed for factor VIII concentrates, median single dose over the first three months of treatment, first FVIII administration before the age of three months, presence of risk HA gene mutations, "intensive treatment moments" and "year of birth" (proxy for different treatment periods). HRI occurred in 71/288 children (24.7%). In multivariate analysis adjusted for "year of birth", underlying risk gene mutations (HR/CI: 2.37/1.40-3.99), FVIII dose, measured per one IU increase per kgbw (HR/CI: 1.05/1.04-1.07), and first FVIII administration before the age of three months showed a significant impact on HR development. The risk of HRI development was similar for recombinant or plasmatic FVIII products. Children at risk should be treated with carefully calculated lower dose regimens, adapted to individual bleeding situations.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.015
Threshold uncertainty score0.396

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.043
GPT teacher head0.358
Teacher spread0.315 · 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

Citations10
Published2013
Admission routes1
Has abstractyes

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