Clinical Spectrum, Treatment, and Outcome of Patients with Type II Mixed Cryoglobulinemia without Evidence of Hepatitis C Infection
Bibliographic record
Abstract
OBJECTIVE: The clinical spectrum, etiologies, and best therapeutic approaches of type II mixed cryoglobulinemia (MC) not associated with hepatitis C virus (HCV) infection have been poorly described to date. We studied the clinical presentation and outcome of patients with type II MC with no evidence of HCV. METHODS: This was a multicenter retrospective study on the clinical presentation and outcome of patients with type II MC without evidence of HCV infection. Only patients with symptomatic MC were included. RESULTS: Thirty-three patients were included (median followup 67.2 mo). Extensive investigations for associated diseases were performed at presentation. MC was related to an autoimmune disease in 14 patients, to a lymphoid malignancy in 4 patients, and to an infectious disease in 2 patients, while MC was classified as essential (primary) in 13. Essential MC tended to be more severe than secondary disease with, in particular, more frequent renal and peripheral nerve involvement. Most patients were treated with steroid with or without immunosuppressive agents, mainly cyclophosphamide. These treatments were unable to induce sustained remission. One patient was successfully treated with lenalidomide. Seven patients with nonmalignant MC were treated with rituximab; 2 had a sustained complete remission, 3 improved greatly but relapsed within 5 months, and 2 experienced a disease flare. CONCLUSION: An important proportion of non HCV-related type II MC remains essential. Efforts should be made to find other etiologies than HCV, because treatments with steroid and immunosuppressants are not satisfactory, especially in severe forms. In these situations anti-CD20 therapy may present the best option but should be used with caution. New agents such as lenalidomide remain to be evaluated.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".