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Record W2022257644 · doi:10.1177/0267659109346662

The use of a mini bypass circuit for minimally invasive mitral valve surgery

2009· article· en· W2022257644 on OpenAlexaff
Philip Fernandes, James MacDonald, A. Cleland, Richard Mayer, Stephanie A. Fox, Bob Kiaii

Bibliographic record

VenuePerfusion · 2009
Typearticle
Languageen
FieldMedicine
TopicCardiac and Coronary Surgery Techniques
Canadian institutionsLondon Health Sciences CentreWestern University
Fundersnot available
KeywordsMedicineCardiopulmonary bypassMitral valve repairMitral valveSurgeryInvasive surgeryCardiologyCardiac surgeryInternal medicine

Abstract

fetched live from OpenAlex

INTRODUCTION: The purpose of the study is to clinically evaluate minimally invasive mitral valve surgeries (MIMVS) using a mini bypass circuit. The challenge to perfusion is to keep pace with MIMVS, with demonstrated improvements in perfusion-related technologies. METHODS: From October 28, 2005 to September 10, 2008, we retrospectively evaluated thirty-four elective cases which used the mini-circuit (Medtronic Resting Heart System), with respect to safety, efficacy, cannulation technique, blood usage, resultant hemoglobin, length of ICU and hospital stay, and complications. CONCLUSION: The Medtronic Resting Heart System alleviates many factors, such as high shear stress, turbulence, air to blood interface and decreased oncotic pressure caused by hemodilution, providing more efficient perfusion to our MIMVS patients. We demonstrate, with minor circuit modifications and attention to venous air issues, that this mini-circuit can be used safely and effectively, while being associated with improvements in patient outcomes.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
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)0.0010.000

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 head0.053
GPT teacher head0.274
Teacher spread0.221 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations9
Published2009
Admission routes1
Has abstractyes

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