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Record W4406480908 · doi:10.1177/02676591241313167

Considering veno-venous extracorporeal membrane oxygenation as a first-line strategy for rewarming in accidental hypothermia complicated by cardiac arrest - a case series

2025· article· en· W4406480908 on OpenAlex
Hossein Shayan, Derek Gunning, Michelle Mozel, Kamen Valchanov

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenuePerfusion · 2025
Typearticle
Languageen
FieldMedicine
TopicCardiac Arrest and Resuscitation
Canadian institutionsFraser HealthUniversity of British Columbia
Fundersnot available
KeywordsMedicineExtracorporeal membrane oxygenationHypothermiaAnesthesiaCardiology

Abstract

fetched live from OpenAlex

Severe accidental hypothermia can lead to cardiac arrest. The most efficient method of resuscitating and warming is by ECMO (Extracorporeal Membrane Oxygenation). While the convention is to use VA ECMO (Veno Arterial ECMO), using VV ECMO (Veno Venous ECMO) in which the blood is returned directly into the right ventricle could be an alternative and lead to conversion to life sustaining cardiac rhythm. In this article we present our case series of ECMO for resuscitation of accidental hypothermia complicated by cardiac arrest. We used VV ECMO for 4 patients; in 3 of them ROSC (Return of Spontaneous Circulation) was successfully achieved. We also discuss the potential advantages of VV ECMO and VA ECMO in this setting and present our algorithm for management.

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.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.400
Threshold uncertainty score0.718

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.020
GPT teacher head0.298
Teacher spread0.279 · 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