Abstract 15011: Intravenous Immunoglobulin for Acute Myocarditis is Associated With Increased Resource Utilization but Equivalent Survival: An Outcome Analysis Amongst U.S. Children’s Hospitals
Bibliographic record
Abstract
Introduction: Intravenous immunoglobulin (IVIg) is frequently utilized in the treatment of pediatric acute myocarditis (AM) though the data surrounding the efficacy of intravenous immunoglobulin (IVIg) are equivocal. Hypothesis: IVIg utilization does not improve survival in pediatric AM but is associated with increased resource utilization. Methods: A retrospective review of the Pediatric Health Information System database was performed for children <18 years hospitalized with AM between 2004 and 2014. A 1:1 propensity matched case control design was used to compare children who received IVIg (IVIg-group) to those who did not receive IVIg (no IVIg-group). The propensity score was based on a model including treatment with mechanical ventilation (MV), inotropes, or mechanical circulatory support (MCS). High- and low-use hospitals were defined by quartiles of percent usage of IVIg. Results: A total of 1802 children with AM were identified (median age 8y [IQR 1 - 15]; 60% male, 60% IVIg given, 65% inotrope use, 46% MV use, 16% MCS use). After matching, 552 children were included in both the IVIg-group and no IVIg-group. Overall median follow-up of the matched cohort was 1.4y [IQR 0.4-3.4]. Unadjusted in-patient mortality was similar between groups (6% vs. 9%, p=0.09). On multivariable Cox regression, there was no association between IVIg and follow-up mortality (OR 1.0, 95%CI 0.3- 2.9). Although in-patient cardiac transplantation occurred more frequently in the IVIg-group (2% vs. 0%, p<0.001), there was no association between IVIg and cardiac transplantation during the follow up period (OR 0.5, 95%CI 0.2-1.1). Mortality was similar between high- and low-use centers (6% vs. 8%, p=0.316) as was length of stay (7d [IQR 8-18] vs. 7d [4-18], p=0.771). Total charges, as well as pharmacy charges, were significantly higher in the IVIg-group ($125k vs. $77k, $32k vs. $2.8k; p<0.001 for both) and high-use centers ($125k vs. $112k, p=0.025; $27k vs. $5.1k, p<0.001). Conclusions: IVIg is frequently utilized in children for the treatment of AM. Overall survival was similar in patients treated and not treated with IVIg, though resource utilization was significantly increased. Further study is needed to assess the most optimal, cost-effective treatment for AM in children.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".