ACTION-ARC Pediatric and Adult Congenital Heart Disease Ventricular Assist Device Adverse Event Definitions-2023
Bibliographic record
Abstract
Adverse events (AEs) experienced by children and adults with congenital heart disease (CHD) on ventricular assist devices (VADs) are sometimes unique to these populations. The Advanced Cardiac Therapies Improving Outcomes Network (ACTION) and the Academic Research Consortium (ARC) aimed to harmonize definitions of pediatric and CHD AEs for use in clinical trials, registries, and regulatory evaluation. Data from the ACTION registry and adjudication committee were used to adapt general mechanical circulatory support ARC definitions. This ACTION-ARC international expert panel of trialists, clinicians, patients, families, statisticians, biomedical engineers, device developers, and regulatory agencies drafted and iterated definitions harmonized to ACTION data and existing literature during sessions conducted between December 2022 and May 2023, followed by dissemination across clinical/research audiences and professional organizations and further revision. Both email-linked, internet-based surveys and in-person discussions were used as a modified Delphi process. Nineteen AE types were identified and defined, including seven new event types and six event types that were deleted and will no longer be collected, achieving consensus. ACTION-ARC paired rigorous development with methodical stakeholder involvement and dissemination to define pediatric VAD AEs to facilitate assimilation of data across future clinical trials and evaluation of devices for VAD-supported children and adults with CHD.
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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 | 0.084 | 0.096 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.007 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.004 | 0.005 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.014 | 0.007 |
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".