Features, Treatment, and Outcomes of Macrophage Activation Syndrome in Childhood‐Onset Systemic Lupus Erythematosus
Bibliographic record
Abstract
OBJECTIVE: To describe the features and treatment of macrophage activation syndrome (MAS) in a single-center cohort of patients with childhood-onset systemic lupus erythematosus (SLE), and to compare childhood-onset SLE manifestations and outcomes between those with and those without MAS. METHODS: We included all patients with childhood-onset SLE followed up at The Hospital for Sick Children from 2002 to 2012, and identified those also diagnosed as having MAS. Demographic, clinical, and laboratory features of MAS and SLE, medication use, hospital and pediatric intensive care unit (PICU) admissions, as well as damage indices and mortality data were extracted from the Lupus database. Student's t-tests and Fisher's exact tests were used to compare continuous and categorical variables, respectively. We calculated incidence rate ratios of hospital and PICU admissions comparing patients with and those without MAS, using Poisson models. Kaplan-Meier survival analysis was used to examine the time to disease damage accrual. RESULTS: Of the 403 patients with childhood-onset SLE, 38 (9%) had MAS. The majority (68%) had concomitant MAS and SLE diagnoses. Fever was the most common MAS clinical feature. The frequency of renal and central nervous system disease, hospital admissions, the average daily dose of steroids, and time to disease damage were similar between those with and those without MAS. We observed a higher mortality rate among those with MAS (5%) than those without MAS (0.2%) (P = 0.02). CONCLUSION: MAS was most likely to develop concomitantly with childhood-onset SLE diagnosis. The majority of the MAS patients were successfully treated with corticosteroids with no MAS relapses. Although the numbers were small, there was a higher risk of death associated with MAS compared to SLE without MAS.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".