Gelatinous Transformation of Bone Marrow Following Lymphoma and a Novel, Potential Treatment
Bibliographic record
Abstract
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 machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".