A15: Predicting Macrophage Activation Syndrome in Pediatric Systemic Lupus Erythematosus Patients at Diagnosis
Bibliographic record
Abstract
Background/Purpose: Macrophage activation syndrome (MAS), a life‐threatening inflammatory emergency of children with rheumatic diseases, is increasingly recognized in pediatric systemic lupus erythematosus (pSLE). The challenge is to differentiate active pSLE from MAS in order to make correct treatment decisions. The purpose of this study is to generate a decision tree for the recognition of MAS in newly diagnosed pSLE and test the performance of these proposed criteria in an independent pSLE cohort. Methods: A retrospective cohort study of consecutive patients requiring admission to SickKids Hospital with newly diagnosed, active pSLE between January 2002 and July 2007 (training cohort) was performed. All patients met ≥4/11 ACR criteria. Data collection on: 1) Clinical features including fever, CNS dysfunction, splenomegaly, hepatomegaly and hemorrhage; 2) laboratory parameters; CBC, ESR, CRP, C3, C4, ferritin, AST, ALT, LDH, albumin, bilirubin, triglycerides, LDL, HDL, urea, creatinine, sodium, coagulation parameters including INR, PTT, fibrinogen and D‐Dimer, and soluble IL‐2 receptor (sIL‐2R) and CD163. Patients were assigned to one of 2 cohorts exclusively (MAS/non‐MAS). Putative predictor variables were compared between cohorts. A decision tree analysis for diagnosis of MAS in pSLE was constructed using recursive partitioning, and decision rules were subsequently applied to an independent cohort of newly diagnosed, active pSLE diagnosed and admitted to SickKids between July 2007 and July 2013 (testing cohort) to determine the sensitivity and specificity of the proposed criteria. Results: The training cohort consisted of 56 pSLE patients: 9 (16%) diagnosed with MAS and 47 non‐MAS patients. Splenomegaly was more common in the non‐MAS cohort, with no other differences in clinical characteristics between cohorts. Of all the available laboratory data, ALT ≥ 45 units/L, neutrophils < 1.65 × 10 3 /mm 3 and ferritin < 836 µg/L identified 56% of the patients with MAS (R 2 = 0.75) with 100% specificity. The testing cohort consisted of 9 (20%) MAS and 37 non‐MAS pSLE patients. The proposed thresholds for ALT, neutrophil count and ferritin demonstrated a sensitivity of 11% and specificity of 97%. Conclusion: MAS is a life threatening complication of pSLE. Early recognition is challenging yet critical for appropriate therapy. PSLE patient with and without MAS have many similar clinical and laboratory features. Using statistical modeling, the initial criteria developed maintained excellent specificity but poor sensitivity for distinguishing MAS from active SLE at diagnosis in the testing cohort. Hence, new validated models are required for the early recognition of MAS among pSLE patients. Future analyses are planned to address these issues.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".