Enhancing Patient Safety in Refractory Ventricular Fibrillation: A Systematic Review of Double Sequential and Vector Change Defibrillation Barriers
Bibliographic record
Abstract
Background/Objectives: Ventricular fibrillation (VF) is the most common shockable rhythm in cardiac arrest, yet refractory VF (RVF), defined as persistent VF after ≥three failed defibrillation attempts, poses a significant challenge. Two alternative strategies, double sequential external defibrillation (DSED) and vector change (VC) defibrillation, aim to enhance defibrillation success where conventional methods fail. This review evaluates the clinical feasibility, safety, and implementation barriers of DSED and VC in RVF cases. Methods: A systematic review was conducted following PRISMA 2020 guidelines. PubMed, Scopus, and CINAHL databases were searched for studies published between January 2015 and August 2025. Eligible studies included adult RVF patients treated with DSED or VC. Outcomes assessed included implementation barriers, safety concerns, and methodological limitations. Study quality was evaluated using the Newcastle–Ottawa Scale and the Cochrane RoB 2 tool. Results: Sixteen studies met the inclusion criteria. Identified barriers were grouped into practical and methodological categories. Practical barriers included the need for dual defibrillators and pads, delays in shock coordination, inconsistent protocols, equipment compatibility issues, and dependence on trained personnel. Methodological barriers included small sample sizes, retrospective designs, inconsistent RVF definitions, and incomplete reporting of neurological outcomes. Conclusions: DSED and VC defibrillation may offer potential benefits in managing RVF, but their use is hindered by significant practical and methodological barriers. Due to the limited number of randomized trials, further high-quality studies with standardized definitions and safety endpoints are needed to clarify their clinical utility and inform implementation.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".