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Record W2787227514 · doi:10.14740/cr684w

Transcatheter Aortic Valve Replacement After Coronary Artery Bypass Graft Is Associated With Increased Pacemaker Implantation but Not Reduced Overall Survival

2018· article· en· W2787227514 on OpenAlexvenueno aff
Brent Klinkhammer

Bibliographic record

VenueCardiology Research · 2018
Typearticle
Languageen
FieldMedicine
TopicCardiac Valve Diseases and Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineValve replacementCardiologyInternal medicineStenosisArteryRetrospective cohort studyCohortAortic valve replacementCoronary artery diseaseAortic valveSurgery

Abstract

fetched live from OpenAlex

BACKGROUND: A history of coronary artery bypass graft (CABG) is a common compelling indication for transcatheter aortic valve replacement (TAVR). However, there is little data on how these patients compare to other TAVR patients. In this study, the short and long-term outcomes of these TAVR patients after CABG are defined. METHODS: A retrospective chart review case-control study of 337 consecutive patients who underwent a TAVR for severe aortic stenosis at Sanford Health in Fargo ND was performed to determine if a history of prior CABG was associated with worse outcomes after TAVR as compared to a TAVR cohort without a history of CABG. RESULTS: Despite higher predicted surgical risk, patients with a history of CABG had no significant difference overall survival at 1 month (98% vs. 93%, P = 0.112), 6 months (94% vs. 87%, P = 0.094), 1 year (85% vs. 77%, P = 0.206) or 2 years (70% vs. 57%, P = 0.135) post-TAVR. However, a history of CABG was associated with an increase in post-TAVR permanent pacemaker (PPM) implantation (15% vs. 6%, P = 0.015). CONCLUSIONS: This study gives evidence to suggest that patients with a history of prior CABG do not have any difference in overall survival as other TAVR patients, despite higher predicted surgical risk and differences in preprocedural comorbidities. Our study also confirms the safety of TAVR in this specific population in lower volume centers.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.027
Threshold uncertainty score0.893

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.042
GPT teacher head0.374
Teacher spread0.332 · 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.

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

Citations8
Published2018
Admission routes1
Has abstractyes

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