Cardiovascular disease risk assessment in patients with familial Mediterranean fever related renal amyloidosis
Bibliographic record
Abstract
Chronic inflammation and proteinuria is a risk factor for cardiovascular disease (CVD) in patients with chronic kidney diseases and rheumatologic disorders. Our aim was to investigate the CVD events (CVDEs) and survival between the patients with FMF-related AA amyloidosis and glomerulonephropathies (GN) to define possible predictors for CVDEs. A prospective follow-up study with FMF-amyloidosis and glomerulonephropathy (GN) was performed and patients were followed for CVDEs. Flow-mediated dilatation (FMD), FGF-23, serum lipid, hsCRP levels, BMI and HOMA were assessed. A Cox regression analysis was performed to evaluate the risk factors for CVDEs. There were 107 patients in the FMF-amyloidosis group and 126 patients with GN group. Forty-seven CVDEs were observed during the 4.2-years follow up; all 28 patients in the FMF-amyloidosis group and 14/19 patients with GN developed CVDEs before the age of 40 (p = 0.002). CVD mortality was 2.8 times higher (95% CI 1.02-7.76) in patients with FMF-amyloidosis. Across both groups, FMD and FGF23 (p < 0.001) levels were independently associated with the risk of CVDEs. Patients with FMF-amyloidosis are at increased risk of early CVDEs with premature mortality age. FGF 23, FMD and hsCRP can stratify the risk of early CVD in patients with FMF-related AA amyloidosis.
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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) | 0.000 | 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".