Monoclonal gammopathy in systemic lupus erythematosus
Bibliographic record
Abstract
We studied the prevalence, type and associated features of monoclonal gammopathy in patients with systemic lupus erythematosus (SLE). Patients included in the University of Toronto Lupus Database with an abnormal band on serum electropheresis were identified. Monoclonal gammopathy patients were matched with two controls each from the same database by age at SLE diagnosis, sex and disease duration. Of 1083 patients followed at the Lupus Clinic 59 (5.4%) were identified with monoclonal gammopathy. The gammopathies included 32 with IgG, 14 IgM and 12 IgA, one undefined. Nine (15.3%) malignancies were detected in monoclonal gammopathy and 12 (10.1%) in the controls during the entire course of their disease (P = 0.13). None had multiple myeloma. There was no difference between patients with monoclonal gammopathy and their controls with respect to disease activity, damage, or dose of steroids. The mean ESR and gammaglobulin levels in the monoclonal gammopathy patients were higher than the controls at last visit. We conclude that monoclonal gammopathy is more frequent in SLE patients than in the general population and has a benign course in patients with SLE. There were no differences in disease manifestations, treatment approaches, or malignancies between SLE patients with and those without monoclonal gammopathy.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".