MétaCan
Menu
Back to cohort
Record W4386945474 · doi:10.1111/bjh.19073

Paediatric‐onset Evans syndrome: Breaking away from refractory immune thrombocytopenia

2023· review· en· W4386945474 on OpenAlexaff
Nathalie Aladjidi, Thomas Pincez, Frédéric Rieux‐Laucat, Diane J. Nugent

Bibliographic record

VenueBritish Journal of Haematology · 2023
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBlood disorders and treatments
Canadian institutionsUniversité de MontréalCentre Hospitalier Universitaire Sainte-Justine
FundersFondation pour la Recherche MédicaleInstitut National de la Santé et de la Recherche MédicaleAgence Nationale de la Recherche
KeywordsEvans syndromeSplenectomyMedicineImmune systemImmunologyImmune thrombocytopeniaNeutropeniaSpleenInternal medicineAutoimmune hemolytic anemiaAntibodyChemotherapy

Abstract

fetched live from OpenAlex

Since its first description by Evans in 1951, this syndrome has been linked to chronic immune thrombocytopenia with the concurrent or delayed onset of autoimmune haemolytic anaemia or neutropenia. For decades, the evolution of Evans syndrome (ES) has carried a poor prognosis and often resulted in chronic steroid exposure, multiple immune suppressing medications directed against T or B lymphocytes, and splenectomy. This paper presents a new view of ES based on recent advances in genomics which begin to classify patients based on their underlying molecular variants in previously described primary immune disorders. This has opened up new avenues of targeted therapy or bone marrow transplant at rather than broad long-term immune suppression or splenectomy. Importantly, recent studies of the full lifespan of ES suggest that at least 80% of those paediatric patients will progress to various clinical or biological immunopathological manifestations with age despite the resolution of their cytopenias. Those patients merit long-term follow-up and monitoring in dedicated transition programs to improve outcome at the adult age.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.883
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.026
GPT teacher head0.308
Teacher spread0.282 · 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.

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

Citations15
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueBritish Journal of HaematologySame topicBlood disorders and treatmentsFrench-language works237,207