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Record W2088878818 · doi:10.1177/0267659110381664

Aortic arch replacement and elephant trunk procedure: an interdisciplinary approach to surgical reconstruction, perfusion strategies and blood management

2010· article· en· W2088878818 on OpenAlexaff
Christine A. McKay, Peter Allen, Philip M. Jones, Michael Chu

Bibliographic record

VenuePerfusion · 2010
Typearticle
Languageen
FieldMedicine
TopicCardiac and Coronary Surgery Techniques
Canadian institutionsWestern UniversityLondon Health Sciences Centre
Fundersnot available
KeywordsMedicineElephant trunksCardiopulmonary bypassAscending aortaSurgical teamDescending aortaPerfusionSurgeryAortic archPerioperativeAortaBlood managementBlood conservationCardiothoracic surgeryAnesthesiaCardiology

Abstract

fetched live from OpenAlex

Surgical treatment of patients who present with large aneurysms of the ascending aorta, transverse arch and descending aorta, including the thoracic and abdominal aorta typically consists of a two-staged elephant trunk procedure. Typically, these operations are lengthy, requiring long cardiopulmonary bypass times, deep hypothermic circulatory arrest and multiple anastamotic suture lines, which increases the risks for coagulopathic bleeding and the need for massive transfusions. The purpose of this report is to describe our approach, involving advanced surgical techniques and the innovative perfusion considerations as well as modified blood management strategies to minimize perioperative blood loss and the need for transfusions. All of the above will highlight critical cardiac team communications. An ever-evolving case requires forward thinking, revised judgments, open discussion and the continued involvement of all team members. In turn, this ensures evidence-based medical and perfusion practices that lead to achieving a positive peri-operative course, with optimal blood conservation.

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)0.002
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0020.001
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.010
GPT teacher head0.284
Teacher spread0.275 · 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 designNot applicable
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

Citations3
Published2010
Admission routes1
Has abstractyes

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