Number of Episodes Can Be Used as a Disease Activity Measure in Familial Mediterranean Fever
Bibliographic record
Abstract
Objective To evaluate the number of episodes in the past 12 months as an indicator of the overall disease activity status in Familial Mediterranean fever (FMF). Methods In this cross-sectional study, patients were recruited from tertiary pediatric hospitals. Demographic data, main clinical symptoms of the episodes, treatment modalities, and genetic mutations were recorded. The patients were grouped as no episodes (Group 1), 1–4 episodes (Group 2), and more than 4 episodes (Group 3) according to the number of episodes in the past 12 months. The Pediatric Quality Life Inventory (PedsQL), the Children’s Depression Inventory (CDI), and the Wong-Baker FACES Pain Rating Scale (FACES) scores were compared between groups. Concurrent validity between the number of episodes and the patient-reported outcome measures (PROMs) was assessed using Spearman’s rank correlation coefficient (ρ). Results A total of 239 patients were included. There were 74 patients (31%) in Group 1, 99 (41.4%) in Group 2, and 66 (27.6%) in Group 3. Groups were similar according to age, age at diagnosis, gender, consanguinity, family history, history of amyloidosis, clinical symptoms, and in terms of allele frequency (p > 0.05). According to PROMs completed by parents, moderate correlations were found between the number of episodes and the PedsQL score (ρ = −0.48; 95% CI = −0.58 to −0.35, p < 0.001) and between the number of episodes and the Wong-Baker FACES score (ρ = 0.47, 95% CI = 0.35–0.57, p < 0.001). Conclusion The number of episodes was positively and moderately correlated with patient- and parent-reported outcomes in our cohort. The number of episodes in patients with FMF can be used as a single measure to assess disease activity.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".