Variation in Treatment and Outcomes of Children With Acute Disseminated Encephalomyelitis
Bibliographic record
Abstract
OBJECTIVES: To characterize variation in treatments and outcomes of pediatric patients admitted to children’s hospitals with acute disseminated encephalomyelitis (ADEM). METHODS: In this retrospective cohort study, we used data from the Pediatric Health Information System. Children >30 days old who were hospitalized from 2010 to 2015 with ADEM were included. Variables analyzed were treatments and admission to an ICU. Primary outcomes were discharge disposition and readmissions for relapses (ADEM readmissions) or for continued comorbidities (non-ADEM readmissions). RESULTS: A total of 954 patients with ADEM had 1117 admissions. Treatments included steroids (80%), immunoglobulin (22%), and plasmapheresis (6.6%); 15% of admissions included none of these treatments. Treatments varied by center (P < .001). Thirty-four percent of admissions included ICU admission, which was associated with an increased number and duration of treatments (P < .01). The discharge disposition was home in 85% of admissions; home with health services, rehab facility, or other in 13.6%; and mortality in 1.4%. Twelve percent (117 of 954) of patients had >1 admission for ADEM. Treatment choice and ICU stay were not associated with ADEM readmissions. Sixteen percent (181 of 1101) of ADEM admissions had a non-ADEM readmission within 90 days. Prolonged ICU hospitalization was associated with non-ADEM readmission (adjusted odds ratio 1.9; P = .017) and decreased likelihood of discharge from the hospital to home (adjusted odds ratio 0.1; P < .001). After adjusting for ICU duration, treatment choice and duration were not associated with non-ADEM readmission or hospital disposition. CONCLUSIONS: Significant variation in ADEM treatment exists across centers. Admission to an ICU for ADEM was associated with increased immunotherapy, additional health services at discharge, and readmission for diagnoses other than ADEM.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".