MétaCan
Menu
Back to cohort
Record W4406748935 · doi:10.1016/j.rpth.2025.102689

Measurement of factor XIII for the diagnosis and management of deficiencies: insights from a retrospective review of 10 years of data on consecutive samples and patients

2025· review· en· W4406748935 on OpenAlexafffund
Mohammed Sharif, Natalie Mathews, Subia Tasneem, Karen A. Moffat, Stephen A. Carlino, Siraj Mithoowani, Catherine P.M. Hayward

Bibliographic record

VenueResearch and Practice in Thrombosis and Haemostasis · 2025
Typereview
Languageen
FieldMedicine
TopicBlood properties and coagulation
Canadian institutionsHamilton Regional Laboratory Medicine ProgramCentre Hospitalier Universitaire Sainte-JustineMcMaster University
FundersCentre hospitalier universitaire Sainte-JustinePrincess Nourah Bint Abdulrahman UniversityDepartment of Haematology, Christian Medical College, VelloreMcMaster UniversityKing Abdulaziz University Hospital
KeywordsRetrospective cohort studyFactor (programming language)MedicinePediatricsComputer scienceInternal medicine

Abstract

fetched live from OpenAlex

Background: Factor XIII (FXIII) deficiency is a challenge in the diagnosis of rare bleeding disorders with inherited and acquired causes. Objectives: We evaluated consecutive cases tested for FXIII deficiency for insights on diagnosis. Methods: With ethics approval, we retrospectively reviewed FXIII tests performed between 2013 and 2023 and local patient records for insights into causes and presentations of FXIII deficiency. Results: < .05). Most FXIII deficiencies were acquired (92%), and although several were autoimmune, most were from consumption, major bleeds, or severe infections or had uncertain significance, with bleeding sometimes attributable to other causes. Conclusion: Congenital and acquired FXIII deficiency are associated with bleeding. Local practices were changed to ensure that FXIII:Act is used to screen for FXIII deficiency and that deficient patients have FXIII:Act and FXIII-A:Ag quantified and compared.

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)0.002
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.877
Threshold uncertainty score0.411

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.003
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 integrity0.0000.000
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 head0.519
GPT teacher head0.492
Teacher spread0.027 · 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 designOther design
Domainnot available
GenreReview

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

Citations6
Published2025
Admission routes2
Has abstractyes

Explore more

Same venueResearch and Practice in Thrombosis and HaemostasisSame topicBlood properties and coagulationFrench-language works237,207