Cryocrystalglobulinemia Leading to Multi-Organ Failure in Chronic Lymphocytic Leukemia Achieving Complete Renal Recovery
Bibliographic record
Abstract
Cryocrystalglobulinemia (CCG) is a rare and fatal subset of type I cryoglobulinemia that is classically associated with an underlying monoclonal gammopathy. Cryocrystalglobulins are created when immunoglobulins self-assemble into extracellular crystal arrays, which often leads to severe systemic hypoperfusion and occlusive vasculopathy that culminates in multi-organ failure. Most commonly, the resultant ischemia manifests as cutaneous lesions and renal insufficiency, which can progress to fulminant kidney failure requiring renal replacement therapy. CCG is commonly associated with lymphoproliferative disorders and is most frequently reported in the literature in context of plasma cell dyscrasias with minimal cases describing CCG secondary to other types of lymphoid neoplasms, especially those that attain complete organ recovery. We report a unique case of a patient who presented with multi-organ failure, including cryoglobulinemic glomerulonephritis (CryoGN) consistent with monoclonal gammopathy of renal significance (MGRS), who was found to have type I IgG kappa CCG due to chronic lymphocytic leukemia (CLL). With the assistance of plasmapheresis, hemodialysis, and clone-directed therapy, the patient achieved complete renal recovery. We highlight this uncommon entity to emphasize the clinical importance of early diagnosis and timely treatment given CCG's significant morbidity and mortality.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".