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Interventions for Aortic Coarctation

2002· review· en· W1967269286 on OpenAlexaff
Timothy S. Hornung, Lee Benson, Peter R. McLaughlin

Bibliographic record

VenueCardiology in Review · 2002
Typereview
Languageen
FieldMedicine
TopicCongenital Heart Disease Studies
Canadian institutionsHospital for Sick Children
Fundersnot available
KeywordsMedicineCoarctation of the aortaAngioplastyRestenosisBalloonAneurysmStentSurgeryCatheterHypoplasiaBalloon catheterAortaCardiologyRadiology

Abstract

fetched live from OpenAlex

The standard treatment of coarctation of the aorta is surgical. In the last 2 decades, however, treatment by catheter intervention has become more widespread, using either balloon angioplasty or primary stent implantation. Balloon angioplasty was originally used for recurrent coarctation after surgical repair but has now been shown equally effective for unoperated coarctation. The procedure produces a satisfactory gradient reduction in approximately 80% of patients, with transverse arch hypoplasia the main predictor of poorer outcome. Rates of restenosis and aneurysm formation are less than 10%. Primary stent implantation has been suggested as an option potentially superior to angioplasty alone. Stent implantation limits elastic recoil and potentially reduces aneurysm formation by reducing the amount of balloon stretch required. The incidence of suboptimal gradient reduction is low, probably 5% or less, as is the rate of restenosis. Aneurysm formation, vascular complications, and stent migration also occur in less than 5%. Catheter interventions are now an established treatment strategy for coarctation, with a good success rate and safety profile. The outcome for native and recurrent coarctation appears similar. The authors believe that for most adult patients with coarctation of the aorta, catheter intervention should be offered as initial therapy.

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)0.001
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: Review · Consensus signal: Review
Teacher disagreement score0.006
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0040.003
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.003

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 head0.207
GPT teacher head0.477
Teacher spread0.269 · 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
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

Citations45
Published2002
Admission routes1
Has abstractyes

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