Hyperferritinemia Wins Again: Defining Macrophage Activation Syndrome in Pediatric Systemic Lupus Erythematosus
Bibliographic record
Abstract
Macrophage activation syndrome (MAS) is a potentially life-threatening condition of hyperinflammation that can be secondary to an underlying chronic rheumatic condition, commonly systemic juvenile idiopathic arthritis (sJIA) but also childhood-onset systemic lupus erythematosus (cSLE). MAS is characterized by excessive activation of T lymphocytes and macrophages that lead to overproduction of cytokines and results in cytopenia, liver dysfunction, and coagulopathy1. It is critical to recognize MAS early in order to initiate the appropriate treatment quickly and prevent morbidity and mortality. However, in MAS secondary to rheumatic conditions, it can be difficult to distinguish MAS from active disease due to overlapping inflammatory features. Criteria to diagnose MAS in children with sJIA have been developed and initially validated2,3. Guidelines to diagnose MAS in children with SLE have been previously proposed though not further validated4. In the current issue of The Journal of Rheumatology , Gerstein and colleagues present novel criteria to discriminate MAS from active disease in patients with newly diagnosed cSLE, especially in those who are hospitalized, and compare the performance of their developed criteria to existing criteria5. In this report, the authors retrospectively reviewed hospitalizations of patients newly diagnosed with cSLE at a single center and divided patients into 2 cohorts from 2003–2007 and 2008–2013. They selected patients who were febrile, with no prior corticosteroid exposure, and with no evidence of infection. These criteria identified 34 patients in the 2003–2007 cohort and 41 patients in the 2008–2013 cohort. … Address correspondence to Dr. E.A. Smitherman, The Children’s Hospital, CPP N G10, 1600 7th Ave S, Birmingham, AL 35223-1711, USA. Email: Emily.Smitherman{at}peds.uab.edu.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".