MétaCan
Menu
Back to cohort
Record W2060090908 · doi:10.1186/1756-0500-7-782

Successful cardiac resuscitation with extracorporeal membrane oxygenation in the setting of persistent ventricular fibrillation: a case report

2014· article· en· W2060090908 on OpenAlexaff
Mehrdad Golian, Darren H. Freed, Davinder S. Jassal, Amir Ravandi

Bibliographic record

VenueBMC Research Notes · 2014
Typearticle
Languageen
FieldEngineering
TopicMechanical Circulatory Support Devices
Canadian institutionsSt. Boniface HospitalUniversity of Manitoba
Fundersnot available
KeywordsMedicineVentricular fibrillationDefibrillationExtracorporeal membrane oxygenationCardiologyConventional PCIInternal medicineMyocardial infarctionCardiopulmonary resuscitationPercutaneous coronary interventionAcute coronary syndromeCardiogenic shockResuscitationAnesthesia

Abstract

fetched live from OpenAlex

BACKGROUND: Extracorporeal membrane oxygenation (ECMO) technology is a viable option for short-term support in the setting of acute cardiac ischemia. To supplement cardiopulmonary resuscitation (CPR) in select patients, ECMO is used successfully for witnessed in hospital cardiac arrest. In the setting of an acute myocardial infarction (MI), bridging to a revascularization procedure is important in improving overall survival. CASE PRESENTATION: We describe the first known case of a 56-year-old Caucasian male with an anterior ST elevation myocardial infarction (STEMI) who underwent percutaneous coronary intervention (PCI) in which the entire procedure was carried out with the patient being in persistent ventricular fibrillation (VF) resistant to defibrillation on ECMO support. Subsequent to revascularization, the patient's cardiac rhythm converted back to sinus rhythm with a single defibrillation shock with excellent neurologic recovery. CONCLUSION: Our case highlights the importance of early initiation of ECMO during PCI in achieving both improved cardiac and neurological outcomes during an acute coronary syndrome (ACS).

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

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)0.005
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.288
Threshold uncertainty score0.298

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.060
GPT teacher head0.315
Teacher spread0.255 · 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

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

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

Citations2
Published2014
Admission routes1
Has abstractyes

Explore more

Same venueBMC Research NotesSame topicMechanical Circulatory Support DevicesFrench-language works237,207