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Record W2611480026 · doi:10.4084/mjhid.2017.034

Acquired von Willebrand Syndrome associated to secondary IgM MGUS emerging after Autologous Stem Cell Transplantation for AL Amyloidosis

2017· article· en· W2611480026 on OpenAlexaff
Víctor H. Jiménez‐Zepeda, Hina Qamar, Adrienne Lee, Karen Valentine, Leslie Skeith

Bibliographic record

VenueMediterranean Journal of Hematology and Infectious Diseases · 2017
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAmyloidosis: Diagnosis, Treatment, Outcomes
Canadian institutionsCanadian Blood ServicesUniversity of AlbertaBaker Hughes (Canada)
Fundersnot available
KeywordsAutologous stem-cell transplantationBortezomibMedicineTransplantationOncologyStem cellInternal medicineConditioning regimenRegimenMultiple myelomaHematopoietic stem cell transplantation

Abstract

fetched live from OpenAlex

Acquired von Willebrand syndrome (AVWS) is a rare hemorrhagic disorder that occurs in patients with no prior personal or family history of bleeding. Here, we describe a case of AVWS occurring after autologous stem cell transplantation (ASCT). Interestingly, AVWS developed after bortezomib-based induction and conditioning regimens. Recent evidence suggests that the proximity of the bortezomib therapy to the collection of stem cells with consequent depletion of regulatory T cells after the conditioning regimen could explain some of the unusual autoimmune complications reported in patients receiving bortezomib prior to ASCT. In addition, this patient developed a secondary MGUS post-ASCT, which may have also contributed to the AVWS. To the best of our knowledge, this is the first case of post-ASCT AVWS reported. Prospective data is needed to better elucidate the mechanisms by which these unusual complications occur in patients receiving bortezomib prior to ASCT.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.009
GPT teacher head0.259
Teacher spread0.250 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designCase report
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

Citations5
Published2017
Admission routes1
Has abstractyes

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Same venueMediterranean Journal of Hematology and Infectious DiseasesSame topicAmyloidosis: Diagnosis, Treatment, OutcomesFrench-language works237,207