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Record W4396514564 · doi:10.7759/cureus.59354

Gelatinous Transformation of Bone Marrow Following Lymphoma and a Novel, Potential Treatment

2024· article· en· W4396514564 on OpenAlexaff
Logan Hahn, Emina Torlakovic, Mark Bosch

Bibliographic record

VenueCureus · 2024
Typearticle
Languageen
FieldMedicine
TopicMedical Imaging and Pathology Studies
Canadian institutionsSaskatchewan Cancer AgencyUniversity of Saskatchewan
Fundersnot available
KeywordsBone marrowTransformation (genetics)LymphomaMedicinePathologyCancer researchBiologyGenetics

Abstract

fetched live from OpenAlex

Gelatinous transformation of bone marrow (GTBM) is a rare hematologic condition in which hematopoietic cells in the bone marrow are replaced by extracellular gelatinous substances, often resulting in cytopenias. The true incidence of this condition is presently unknown, as the current body of literature primarily consists of case reports. However, an analysis of a large bone marrow registry suggests that this is a highly rare entity even among a population requiring bone marrow biopsy. We present a case of a 24-year-old man with a history of diffuse large B cell lymphoma and an associated 45-kilogram weight loss, who was later found to have GTBM. The extent of his cytopenias resulted in a prolonged hospitalization with numerous complications, eventually leading to experimental treatment with allogeneic stem cell transplantation (ASCT). To our knowledge, this is the first reported case of GTBM in which ASCT was employed as a potential treatment modality. While our patient did have clinical improvement following ASCT, the permanence of these results is presently unclear. Furthermore, it is uncertain if the ASCT was truly causative of the stabilization of the patient. Given this, we are currently unable to advocate for ASCT as a treatment for GTBM. We report this case to raise awareness of this rare entity in the context of refractory cytopenias.

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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.699
Threshold uncertainty score0.219

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.022
GPT teacher head0.291
Teacher spread0.269 · 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
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

Citations0
Published2024
Admission routes1
Has abstractyes

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