Preliminary criteria for global flares in childhood‐onset systemic lupus erythematosus
Bibliographic record
Abstract
OBJECTIVE: To develop widely acceptable preliminary criteria of global flare for childhood-onset systemic lupus erythematosus (cSLE). METHODS: Pediatric rheumatologists (n = 138) rated a total of 358 unique patient profiles with information about the cSLE flare descriptors from 2 consecutive visits: patient global assessment of well-being, physician global assessment of disease activity (MD-global), health-related quality of life, anti-double-stranded DNA antibodies, disease activity index scores, protein:creatinine (P:C) ratio, complement levels, and erythrocyte sedimentation rate (ESR). Based on 2,996 rater responses about the course of cSLE (baseline versus followup), the accuracy (sensitivity, specificity, and area under the receiver operating characteristic curve) of candidate flare criteria was assessed. An international consensus conference was held to rank these candidate flare criteria as per the American College of Rheumatology recommendations for the development and validation of criteria sets. RESULTS: The highest-ranked candidate criteria considered absolute changes (Δ) of the Systemic Lupus Erythematosus Disease Activity Index (SLEDAI) or British Isles Lupus Assessment Group (BILAG), MD-global, P:C ratio, and ESR; flare scores can be calculated (0.5 × ΔSLEDAI + 0.45 × ΔP:C ratio + 0.5 × ΔMD-global + 0.02 × ΔESR), where values of ≥1.04 are reflective of a flare. Similarly, BILAG-based flare scores (0.4 × ΔBILAG + 0.65 × ΔP:C ratio + 0.5 × ΔMD-global + 0.02 × ΔESR) of ≥1.15 were diagnostic of a flare. Flare scores increased with flare severity. CONCLUSION: Consensus has been reached on preliminary criteria for global flares in cSLE. Further validation studies are needed to confirm the usefulness of the cSLE flare criteria in research and for clinical care.
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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 | 0.015 | 0.033 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".