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Record W4386745273 · doi:10.12998/wjcc.v11.i27.6531

Left atrium veno-arterial extra corporeal membrane oxygenation as temporary mechanical support for cardiogenic shock: A case report

2023· article· en· W4386745273 on OpenAlexaff
Rossana Lamastra, David M. Abbott, Antonella Degani, Carlo Pellegrini, Roberto Veronesi, Stefano Pelenghi, Chiara Dezza, Giulia Gazzaniga, Mirko Belliato

Bibliographic record

VenueWorld Journal of Clinical Cases · 2023
Typearticle
Languageen
FieldEngineering
TopicMechanical Circulatory Support Devices
Canadian institutionsUniversity Hospital Foundation
Fundersnot available
KeywordsCardiogenic shockMedicineAmino acidColorectal cancerMetabolismMetabolomicsCancerShock (circulatory)Cancer cellCancer researchBiochemistryInternal medicinePathologyPhysiologyBioinformaticsBiology

Abstract

fetched live from OpenAlex

BACKGROUND: Veno-arterial extra corporeal membrane oxygenation (VA-ECMO) support is commonly complicated with left ventricle (LV) distension in patients with cardiogenic shock. We resolved this problem by transeptally converting VA-ECMO to left atrium veno-arterial (LAVA)-ECMO that functioned as a temporary paracorporeal left ventricular assist device to resolve LV distension. In our case LAVA-ECMO was also functioning as a bridge-to-transplant device, a technique that has been scarcely reported in the literature. CASE SUMMARY: LAVA-ECMO. Unfortunately, episodes of bleeding and sepsis complicated the clinical picture and the patient passed away 27 d after initiating VA-ECMO. CONCLUSION: in cases where less LV unloading is required and where a restrictive myocardium could cause LV suctioning. Left ventricular over-distention is a well-known complication of peripheral VA-ECMO in cardiogenic shock and LAVA ECMO through transeptal cannulation offers a novel and safe approach for treating LV overloading, without the need of an additional percutaneous access.

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)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.206
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.074
GPT teacher head0.347
Teacher spread0.273 · 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.

Study designCase report
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
Published2023
Admission routes1
Has abstractyes

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