Familial Mediterranean Fever in Siblings
Bibliographic record
Abstract
OBJECTIVE: Genetic and environmental factors have been implicated in disease severity and development of amyloidosis in familial Mediterranean fever (FMF). We investigated similarities in clinical characteristics, disease severity, and treatment response within siblings with FMF. METHODS: The study group consisted of 2 or more siblings who were followed in our center with the diagnosis of FMF. Siblings were evaluated for demographic data, clinical and laboratory disease features, genetic analysis of MEFV mutations, and disease severity score. The intraclass correlation coefficient (ICC), which can be interpreted as the expected correlation between 2 siblings, was used to reflect within-family similarity. RESULTS: The study included 67 pediatric patients from 31 different families. When we investigated the similarity of siblings after adjusting for genetic effects, we found very low ICC with p > 0.05 in the majority of clinical features, disease severity, and colchicine dosages. However, age at disease onset, age at onset of therapy, attack-free acute-phase reactant levels, and presence of amyloidosis were found to be similar within siblings (relatively high ICC with p < 0.05). CONCLUSION: Siblings with FMF had different clinical findings and disease severity. They had similar amyloidogenic potential, proven by both similar presence of amyloid and increased levels of acute-phase reactants between attacks. Our findings strongly support that genetic factors may be more dominant in the development of 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 | 0.000 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".