Uncommon Presentation of Undiagnosed B-Cell Lymphoproliferative Disorder as Nodular Pulmonary Amyloidosis
Bibliographic record
Abstract
B-cell lymphoproliferative disorders are characterized by the accumulation of mature B lymphocytes in the bone marrow, lymphoid tissues, and/or peripheral blood. They can cause amyloid deposits in the lungs. In rare cases, lung nodules can be the first sign of this disorder. We present the case of an 89-year-old woman with stable shortness of breath and lung nodules on imaging. A positron emission tomography-computed tomography (PET-CT) scan showed the most intense hypermetabolic nodule in the patient's lung, which was 1.5 × 1.4 cm. A biopsy of this nodule showed amyloid material with trapped plasma cell infiltrate on microscopy. Congo red stain under polarizing microscopy showed apple-green birefringence, which is diagnostic for amyloidosis. Immunohistochemistry showed a mixture of kappa-positive and lambda-positive cells. B-cell gene rearrangement-clonal gene rearrangements were detected in the immunoglobulin heavy chain (IgH) gene and the kappa light chain (IGK). These findings suggest a B-cell lymphoproliferative disorder, such as a plasmacytoma or a marginal cell lymphoma with plasma cell differentiation. The patient was diagnosed with a B-cell lymphoproliferative disorder and pulmonary amyloidosis. Isolated amyloidosis in the lungs usually has a good prognosis, but it can be a sign of autoimmune diseases or B-cell lymphoproliferative disorders, as in this case. Early diagnosis of B-cell lymphoproliferative disorder can lead to successful treatment and prevents complications.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".