Familial Mediterranean Fever (FMF) with Proteinuria: Clinical Features, Histology, Predictors, and Prognosis in a Cohort of 25 Patients
Bibliographic record
Abstract
OBJECTIVE: Reactive (AA) amyloidosis may complicate familial Mediterranean fever (FMF), the prototype of autoinflammatory diseases. Thus, proteinuria in FMF is commonly viewed as resulting from amyloidosis, and kidney biopsy is deemed superfluous. However, nephropathy other than amyloidosis has been described in FMF, but its rate and distinctive characteristics are unknown. Our aim was to determine the rate and underlying pathology of FMF-related nonamyloidotic proteinuria and compare its clinical course, demographic, and genetic features to those of FMF-amyloid nephropathy. METHODS: This study is a retrospective analysis of data from patients with FMF undergoing kidney biopsy for proteinuria above 0.5 g/24 h, over 10 years (2001-2011). Clinical, laboratory, genetic, and pathology data were abstracted from patient files. Biopsies were viewed by an experienced pathologist, as necessary. RESULTS: Of the 25 patients referred for kidney biopsy, only 15 (60%) were diagnosed with amyloid kidney disease (AKD), and 10 were diagnosed with another nephropathy. The AKD and nonamyloid kidney disease (NAKD) groups were comparable on most variables, but showed distinct characteristics with regard to the degree of proteinuria (6.45 ± 4.3 g vs 2.14 ± 1.6 g, p = 0.006), rate of severe FMF (14 vs 5 patients, p = 0.022), and rate of development of end stage renal disease (73.3% vs 20%, p = 0.015), respectively. CONCLUSION: NAKD is common in FMF and, compared to amyloidosis, it is featured with milder course and better prognosis. Contrary to common practice, it is highly recommended to obtain a kidney biopsy from patients with FMF and proteinuria more than 0.5 g/24 h.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".