Review: Measuring permanent damage in pediatric systemic lupus erythematosus
Bibliographic record
Abstract
The survival rates in pediatric systemic lupus erythematosus (pSLE) have improved greatly over recent decades. Increased life expectancy has meant that more children are growing up with the consequences of chronic disease and prolonged therapy. Assessing complications of disease and its therapy becomes an important outcome measure by which to evaluate our therapeutic interventions and appraise quality of life. In this paper we review the development of the Systemic Lupus International Collaborative Clinics (SLICC)/American College of Rheumatology (ACR) Damage Index (SDI) and its application to the pSLE population. We examine the profile of damage in pSLE as identified by the SDI. However we also critically appraise its application and identify potential limitations in the SDI as a measure of permanent disease damage in children. In this paper we put forth suggestions for additional domains addressing pediatric specific issues such as decreased final height and delayed puberty. We also suggest modifications to domains of gonadal failure, diabetes mellitus, cognitive impairment and osteonecrosis in the SDI to make it more reflective of the damage phenomenon observed in pediatrics.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.005 | 0.008 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".