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Record W1979529849 · doi:10.1177/1538574410396589

Ascending-to-Descending Aortic Bypass and Aortic Valve Replacement for Concomitant Severe Aortic Coarctation and Aortic Stenosis

2011· article· en· W1979529849 on OpenAlexaff
Michael Chu, Corey Adams, Pedro Rosales Torres

Bibliographic record

VenueVascular and Endovascular Surgery · 2011
Typearticle
Languageen
FieldMedicine
TopicCongenital Heart Disease Studies
Canadian institutionsWestern University
Fundersnot available
KeywordsMedicineAortic valve replacementCardiologyStenosisConcomitantInternal medicineAsymptomaticAortic valveSurgery

Abstract

fetched live from OpenAlex

We present a 33-year-old male with severe, symptomatic aortic coarctation and aortic stenosis assessed on a humanitarian medical mission to a developing country. Contemplating limited time and available resources, we performed a simultaneous single-stage approach with ascending-to-descending aortic bypass with a reinforced gortex graft and concomitant aortic valve replacement through a median sternotomy. The patient had an uneventful postoperative convalescence and was discharged on postoperative day 5. At 1-year follow-up, he was asymptomatic and doing well with good blood pressure control and complete equalization of upper and lower limb blood pressure measurements. Computed tomography and transthoracic echocardiography demonstrated a widely patent ascending-to-descending aortic bypass graft and a normally functioning prosthetic aortic valve, respectively. In developing countries where health care resources are limited, a combined approach with an extra-anatomic, thoracic aortic bypass, and aortic valve replacement resulted in good early and 1-year outcomes. This procedure may represent the most effective surgical option for patients with concomitant aortic coarctation and aortic stenosis.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0000.001
Research integrity0.0010.001
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 head0.038
GPT teacher head0.268
Teacher spread0.230 · 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 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
Published2011
Admission routes1
Has abstractyes

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