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Record W4415982332 · doi:10.1097/mcc.0000000000001323

Double sequential defibrillation: is it ready for prime time?

2025· review· en· W4415982332 on OpenAlexaff
Bertram Lahn Kirkegaard, Sheldon Cheskes, Lars W. Andersen, Ian R. Drennan

Bibliographic record

VenueCurrent Opinion in Critical Care · 2025
Typereview
Languageen
FieldMedicine
TopicCardiac Arrest and Resuscitation
Canadian institutionsUniversity of TorontoSunnybrook Health Science CentreSt. Michael's Hospital
Fundersnot available
KeywordsPrime (order theory)Key (lock)MEDLINELife savingStandard of care

Abstract

fetched live from OpenAlex

PURPOSE OF REVIEW: Refractory ventricular fibrillation, which fails to respond to defibrillation, is associated with poor survival. Despite this, there are no treatments that are proven effective beyond standard defibrillation and cardiopulmonary resuscitation. Double sequential external defibrillation (DSED) has been proposed as an alternative defibrillation strategy for this patient population. In this review, we will discuss key evidence surrounding DSED, as we present two opposing arguments, 'pro' that DSED is ready for clinical practice and 'con' that more research is needed prior to implementation of this technique. RECENT FINDINGS: The Double Sequential External Defibrillation for Refractory Ventricular Fibrillation (DOSE VF) randomized clinical trial demonstrated improved patient outcomes for patients with refractory ventricular fibrillation who did not respond to standard defibrillation attempts. There remain unanswered questions with respect to the mechanism by which DSED may improve outcomes and the logistics of implementation into clinical practice. SUMMARY: This article discusses some of the key controversies surrounding DSED and whether this novel defibrillation strategy is ready for integration into standard practice. Further research is ongoing that may help to answer further questions related to the utility of DSED.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gptno category
Domain: not available · Genre: Review
About the Canadian research system: no · About a Canadian topic: no
Other designhigh
grokno category
Domain: not available · Genre: Review
About the Canadian research system: no · About a Canadian topic: no
Other designhigh
opusno category
Domain: not available · Genre: Review
About the Canadian research system: no · About a Canadian topic: no
Other designhigh
models agreeAgreement compares identical category sets and study designs across arms.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.883
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.305
GPT teacher head0.538
Teacher spread0.233 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Labeled directly by 3 models reading the full record.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
Domainnot available
GenreReview

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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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