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Record W2956450005 · doi:10.1177/1076029619862052

Joint Bleeding Tendencies in Adult Patients With Hemophilia: It’s Not All Pharmacokinetics

2019· article· en· W2956450005 on OpenAlexaff
Jenny Y. Zhou, R. F. W. Barnes, Gary Foster, Alfonso Iorio, Thomas J. Cramer, Annette von Drygalski

Bibliographic record

VenueClinical and Applied Thrombosis/Hemostasis · 2019
Typearticle
Languageen
FieldMedicine
TopicHemophilia Treatment and Research
Canadian institutionsMcMaster UniversityImpact
Fundersnot available
KeywordsMedicineClotting factorDosingPharmacokineticsHaemophiliaSynovitisArthropathyVascularitySurgeryArthritisInternal medicineOsteoarthritisPathology

Abstract

fetched live from OpenAlex

Hemophilic arthropathy from joint bleeding remains a complication with major morbidity in the increasingly aging patients with hemophilia. Prophylactic clotting factor infusions, based on pharmacokinetic dosing to reduce bleeding rates, are being explored more and more. However, there is little evidence on the benefits of pharmacokinetic dosing in direct association with bleeding events. Here, we prospectively followed a cohort of adult patients with hemophilia A and B (n = 26) and arthropathic joints on various clotting factor products over a period of 2 years with clinical and radiographic joint health assessments, frequent joint ultrasound, and pharmacokinetic studies. Joint bleeds and synovitis with synovial vascularity changes were objectively diagnosed by musculoskeletal ultrasound and power Doppler and analyzed in relation to pharmacokinetic, joint- and patient-specific parameters. Results revealed that, contrary to common beliefs, bleeding episodes were not readily explained by pharmacokinetic features, as they were not associated with more time spent below certain clotting factor thresholds. Joint bleeding was found to be associated with prominent vascularity changes, suggesting that vascular remodeling and leakiness may contribute to joint bleeding that cannot be prevented by clotting factor replacement alone.

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 score0.020
Threshold uncertainty score0.923

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0000.000

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 head0.091
GPT teacher head0.365
Teacher spread0.274 · 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

Citations17
Published2019
Admission routes1
Has abstractyes

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