Bing-Neel Syndrome: Presentation of Three Unusual Patients (P7.264)
Bibliographic record
Abstract
OBJECTIVE: To contribute to the description of Bing-Neel syndrome. BACKGROUND: Waldenström macroglobulinemia can cause neurological symptoms by infiltration of the central nervous system, a condition often called Bing-Neel syndrome. A recent review of the literature (Fintelmann et al., 2009) identified 50 cases. DESIGN/METHODS: We report three cases seen at our institution since 2011. RESULTS: Patient 1, a 75-year-old female, complained of acute paraparesis. She had been diagnosed with Waldenström macroglobulinemia six years before. MRI showed signal abnormalities over most of the spinal cord, with enlargement. Lumbar puncture allowed identification of lymphoplasmocytoid cells in the CSF. Treatment with corticosteroids lead initially to symptoms improvement, but the patient died despite IV and IT therapy. Patient 2, a 65-year-old female, presented with headaches. She had been diagnosed with Waldenström macroglobulinemia eight years before and had received autologous stem cell transplant. Lumbar puncture revealed an elevated intracranial pressure and lymphoplasmacytoid cells were found in the CSF. MRI showed enhancement of optic chiasm and of third, fifth, sixth, seventh and eights cranial nerves. Despite IV and IT chemotherapy, the patient’s condition deteriorated and she died one year after presentation. Patient 3, a 71-year-old male, was known for sarcoidosis and Waldenström macroglobulinemia. He was evaluated for cognitive deterioration over one year. MRI showed white matter confluent lesions and enhancing nodular lesions. He was initially diagnosed with neurosarcoidosis and treated with corticosteroids, but lack of improvement led the other lumbar punctures. Lymphoplasmocytoid cells were found in the CSF. CONCLUSIONS: All three patients had strikingly abnormal, but non specific, imaging findings. Examination of CSF after centrifugation and use of flow cytometry allowed reaching a diagnosis. Despite treatment, our patients’ outcome was poor. Study Supported by:
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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) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".