Consensus protocols for the diagnosis and management of the hereditary autoinflammatory syndromes CAPS, TRAPS and MKD/HIDS: a German PRO-KIND initiative
Bibliographic record
Abstract
BACKGROUND: Rare autoinflammatory diseases (AIDs) including Cryopyrin-Associated Periodic Syndrome (CAPS), Tumor Necrosis Receptor-Associated Periodic Syndrome (TRAPS) and Mevalonate Kinase Deficiency Syndrome (MKD)/ Hyper-IgD Syndrome (HIDS) are genetically defined and characterized by recurrent fever episodes and inflammatory organ manifestations. Early diagnosis and early start of effective therapies control the inflammation and prevent organ damage. The PRO-KIND initiative of the German Society of Pediatric Rheumatology (GKJR) aims to harmonize the diagnosis and management of children with rheumatic diseases nationally. The task of the PRO-KIND CAPS/TRAPS/MKD/HIDS working group was to develop evidence-based, consensus diagnosis and management protocols including the first AID treat-to-target strategies. METHODS: The national CAPS/TRAPS/MKD/HIDS expert working group was established, defined its aims and conducted a comprehensive literature review synthesising the recent (2013 to 2018) published evidence including all available recommendations for diagnosis and management. General and disease-specific statements were anchored in the 2015 SHARE recommendations. An iterative expert review process discussed, adapted and refined these statements. Ultimately the GKJR membership vetted the proposed consensus statements, agreement of 80% was mandatory for inclusion. The approved statements were integrated into three disease specific consensus treatment plans (CTPs). These were developed to enable the implementation of evidence-based, standardized care into clinical practice. RESULTS: The CAPS/TRAPS/MKD/HIDS expert working group of 12 German and Austrian paediatric rheumatologists completed the evidence synthesis and modified a total of 38 statements based on the SHARE recommendation framework. In iterative reviews 36 reached the mandatory agreement threshold of 80% in the final GKJR member survey. These included 9 overarching principles and 27 disease-specific statements (7 for CAPS, 11 TRAPS, 9 MKD/HIDS). A diagnostic algorithm was established based on the synthesized evidence. Statements were integrated into diagnosis- and disease activity specific treat-to-target CTPs for CAPS, TRAPS and MKD/HIDS. CONCLUSIONS: The PRO-KIND CAPS/TRAPS/MKD/HIDS working group established the first evidence-based, actionable treat-to-target consensus treatment plans for three rare hereditary autoinflammatory diseases. These provide a path to a rapid evaluation, effective control of disease activity and tailored adjustment of therapies. Their implementation will decrease variation in care and optimize health outcomes for children with AID.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.159 | 0.138 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.006 |
| Bibliometrics | 0.011 | 0.008 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.007 | 0.009 |
| Research integrity | 0.007 | 0.006 |
| Insufficient payload (model declined to judge) | 0.005 | 0.004 |
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".