The impact of alternate defibrillation strategies on time in ventricular fibrillation
Bibliographic record
Abstract
BACKGROUND: Time in ventricular fibrillation (VF) is associated with survival after out-of-hospital cardiac arrest (OHCA). The impact of vector change defibrillation (VC) and double sequential external defibrillation (DSED) on VF duration has not been explored. OBJECTIVE: To compare the effects of VC and DSED on VF duration and defibrillation outcomes. METHODS: We conducted a secondary analysis of patients enrolled in the Double Sequential External Defibrillation for Refractory VF RCT. We assessed the ECG after each shock, calculating VF time (median, IQR) and shock outcomes. The Kruskal-Wallis test was used to compare VF duration across groups, with post-hoc pairwise comparisons using Dunn's test and Bonferroni correction. Chi-square tests compared shock outcomes. RESULTS: Among 342 patients, 1842 shocks were analyzed (834 after three failed standard shocks: 429 standard, 218 VC, 187 DSED). Median VF time was significantly shorter for DSED (83 [0, 120] s) and VC (98 [0, 120] s) compared to standard shocks (108 [38, 120] s) (P = 0.003). The proportion of shocks leading to return of spontaneous circulation (ROSC) and survival to hospital discharge respectively was higher for DSED (17.6%, 10.2% p < 0.001 ROSC, p = 0.002 survival) and VC (14.2%, 7.3% p < 0.002 ROSC, p = 0.049 survival) than for standard shocks (5.3%, 3.5%) The proportion of shocks in which VF was not terminated was significantly lower for DSED shocks (29.9%) than standard shocks (40.6%) (P = 0.013). CONCLUSIONS: DSED and VC reduced VF duration and increased the likelihood of ROSC and survival compared to standard shocks. These findings may contribute to the improved survival noted in the trial.
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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 | 0.002 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".