Scientific Priorities Related to the Use of Double Sequential External Defibrillation in Patients With Refractory Cardiac Arrest: Report From a Multistakeholder Thinktank
Bibliographic record
Abstract
Ventricular fibrillation (VF) is common among patients with out-of-hospital cardiac arrest. Cardiac arrest with VF has a more favorable prognosis than those with other rhythms, but about 25% of patients with VF are still fibrillating after 3 attempts at defibrillation. Use of 2 defibrillators close together in time, "double sequential external defibrillation" (DSED), has been proposed to treat patients who remain in VF. The DOSE VF (Defibrillation Strategies for Refractory Ventricular Fibrillation) trial enrolled patients with out-of-hospital cardiac arrest with refractory VF to compare DSED versus vector change defibrillation versus standard defibrillation. This trial reported a significant increase in survival with DSED and vector change. DSED was also associated with a significant increase in favorable neurologic outcome. No manual or automated defibrillator is approved for use for DSED. Clinicians can choose to use defibrillators to apply DSED off label at their discretion. But in the absence of recommendations from evidence-based guidelines, Food and Drug Administration, manufacturers, and clinicians face uncertainty about the effectiveness of DSED, its potential disruption of cardiopulmonary resuscitation interruption or use of other effective therapies, as well as potential adverse effects on patients to whom it is applied, and damage to the defibrillator. A collaborative, precompetitive thinktank including academic clinicians and researchers, regulators, and device manufacturers participated in a daylong meeting coconvened by the American Heart Association, the Cardiac Safety Research Consortium and the Food and Drug Administration. We summarize the discussion that sought to advance the understanding of the benefits and risks associated with DSED in patients who remain in VF.
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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 | 0.070 | 0.161 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.021 | 0.023 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".