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Record W2025687097 · doi:10.1097/mph.0000000000000333

ABO Group as a Thrombotic Risk Factor in Children With Acute Lymphoblastic Leukemia

2015· article· en· W2025687097 on OpenAlexaff
Terry Mizrahi, Jean‐Marie Leclerc, Michéle David, Thiérry Ducruet, Nancy Robitaille

Bibliographic record

VenueJournal of Pediatric Hematology/Oncology · 2015
Typearticle
Languageen
FieldMedicine
TopicBlood groups and transfusion
Canadian institutionsCentre Hospitalier Universitaire Sainte-JustineUniversité de MontréalPediatric Oncology Group
Fundersnot available
KeywordsMedicineABO blood group systemInternal medicineRisk factorThrombophiliaLeukemiaCohortRetrospective cohort studyMalignancyCancerThrombosisGastroenterologyOncology

Abstract

fetched live from OpenAlex

Children with acute lymphoblastic leukemia (ALL) are at high risk of thrombotic complications, resulting from multiple risk factors (malignancy, chemotherapy, central venous access devices, and inherent host characteristics). Non-O blood groups have been associated with an increased risk of venous thromboembolism (VTE) in adults, with a compounding effect in the presence of thrombophilia or cancer. We hypothesized that among children with ALL receiving a standardized protocol, there would be an increased risk of thrombotic events in non-O compared with O blood group patients. In a retrospective study of 523 children with ALL from June 1995 to April 2013, there were 56 (10.7%) thromboembolic events. Patients with VTE were compared with the whole cohort, based on blood group, age, sex, leukemia phenotype, and clinical risk category. Among children with VTE, 42 (75%) had non-O and 14 (25%) had O blood group, compared with 302 (57.7%) non-O and 221 (42.3%) O blood groups in the cohort. Non-O blood group was confirmed as an independent risk factor for VTE in multivariate analysis. This is the first study to report a significant association between non-O blood groups and VTE in children with cancer.

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)0.000
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 score0.143
Threshold uncertainty score0.829

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.013
GPT teacher head0.281
Teacher spread0.267 · 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

Citations27
Published2015
Admission routes1
Has abstractyes

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