Monoclonal gammopathy of renal significance: when MGUS is no longer undetermined or insignificant
Bibliographic record
Abstract
Multiple myeloma is the most frequent monoclonal gammopathy to involve the kidney; however, a growing number of kidney diseases associated with other monoclonal gammopathies are being recognized. Although many histopathologic patterns exist, they are all distinguished by the monoclonal immunoglobulin (or component) deposits. The hematologic disorder in these patients is more consistent with monoclonal gammopathy of undetermined significance (MGUS) than with multiple myeloma. Unfortunately, due to the limitations of the current diagnostic schema, they are frequently diagnosed as MGUS. Because treatment is not recommended for MGUS, appropriate therapy is commonly withheld. In addition to end-stage renal disease, the persistence of the monoclonal gammopathy is associated with high rates of recurrence after kidney transplantation. Preservation and restoration of kidney function are possible with successful treatment targeting the responsible clone. Achievement of hematologic complete response has been shown to prevent recurrence after kidney transplantation. There is a need for a term that properly conveys the pathologic nature of these diseases. We think the term monoclonal gammopathy of renal significance is most helpful to indicate a causal relationship between the monoclonal gammopathy and the renal damage and because the significance of the monoclonal gammopathy is no longer undetermined.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".