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Liberation From Venoarterial Extracorporeal Membrane Oxygenation: A Review

2021· review· en· W3182235733 on OpenAlexaff
Darshan H. Brahmbhatt, Andrea L. Daly, Adriana Luk, Eddy Fan, Filio Billia

Bibliographic record

VenueCirculation Heart Failure · 2021
Typereview
Languageen
FieldEngineering
TopicMechanical Circulatory Support Devices
Canadian institutionsUniversity of TorontoTed Rogers Centre for Heart ResearchUniversity Health Network
Fundersnot available
KeywordsExtracorporeal membrane oxygenationCardiogenic shockMedicineIntensive care medicineCannulaExtracorporealLife supportClinical trialHemodynamicsCardiologyInternal medicineSurgery

Abstract

fetched live from OpenAlex

Venoarterial extracorporeal membrane oxygenation may be used for circulatory support in cardiogenic shock as a bridge to recovery, a bridge to a ventricular assist device (VAD), or a bridge to transplant. While the determination of potential exit strategies is essential before cannulation, the final determination of a patient's options may change, in part, through their in-hospital clinical course. We propose that liberation from venoarterial extracorporeal membrane oxygenation should be conceptualized as a process of discovery in the assessment of a patient's underlying clinical status and a key driver of further clinical decision-making. A trial of liberation from support should be considered when the goals of the weaning trial are well-defined and, ideally, in the absence of potentially confounding clinical factors. In this review, we will discuss readiness to wean criteria from venoarterial extracorporeal membrane oxygenation, as well as specific clinical, biochemical, and echocardiographic parameters that may prove useful in determining weaning timing and revealing the patient's underlying hemodynamic status and prognosis. The role of various cannula configurations, support devices, and pharmacological adjuncts will also be discussed. Finally, we highlight current gaps in evidence and suggest areas of future research.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.923
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.037
GPT teacher head0.282
Teacher spread0.245 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
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

Citations34
Published2021
Admission routes1
Has abstractyes

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