Use of Anakinra (Kineret) in the Treatment of Familial Cold Autoinflammatory Syndrome with a 16-Month Follow-Up
Bibliographic record
Abstract
BACKGROUND: The susceptibility gene for familial cold autoinflammatory syndrome (FCAS) has been mapped to chromosome 1q44 and a point mutation determined to be present in all affected members of a large Canadian kindred. Anakinra (Kineret) is known to block IL-1 receptor and in the few patients with FCAS in whom it has been used, it has been shown to provide relief for this lifelong disability. OBJECTIVE: To demonstrate the efficacy and safety of anakinra (Kineret) in FCAS. METHODS: Eight affected family members aged 29 to 77 years received anakinra 100 mg subcutaneously daily for 4 weeks preceded and followed by a 2-week control period. RESULTS: The treatment was rapidly effective paralleled by the immediate fall of the C-reactive protein and serum amyloid A protein. The only significant side effect was an injection-site reaction in 50%, which declined in the follow-up period. The effect was sustained in all who continued to use the treatment at 4 and 16 months of follow-up. CONCLUSION: This is the first treatment of FCAS that is completely effective while it is used.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".