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Record W4412902355 · doi:10.1080/14796678.2025.2543184

Up-to-date review on concomitant mitral transcatheter edge-to-edge repair and left atrial appendage occlusion

2025· review· en· W4412902355 on OpenAlexaff
Graeme Prosperi-Porta, Abdullah Al‐Abcha, Trevor Simard, Benjamin Hibbert, Omar Abdel‐Razek

Bibliographic record

VenueFuture Cardiology · 2025
Typereview
Languageen
FieldMedicine
TopicAtrial Fibrillation Management and Outcomes
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsMedicineConcomitantLeft atrial appendage occlusionAppendageCardiologyInternal medicineAtrial fibrillationOcclusionAnatomyWarfarin

Abstract

fetched live from OpenAlex

In patients undergoing mitral valve transcatheter edge-to-edge repair (M-TEER), atrial fibrillation is a common comorbidity. While oral anticoagulation is the mainstay of stroke prevention therapy in most patients with atrial fibrillation, patients undergoing M-TEER might have a unique opportunity to undergo concomitant left atrial appendage occlusion (LAAO). LAAO is an alternative to oral anticoagulation that reduces the long-term risk of stroke and major bleeding, but it comes with upfront peri-procedural risk. M-TEER and LAAO share numerous procedural characteristics including large-bore venous access, transseptal puncture, general anesthesia, and real-time imaging of the left atrium with echocardiography. Therefore, performing concomitant LAAO at the time of M-TEER might be an attractive option for patients to lessen the cumulative peri-procedural risk, repeated anesthetic, and hospital visits from separate procedures. With rapidly evolving device technologies and an increasing evidence base for LAAO use, there is still limited data evaluating the safety and feasibility of concomitant M-TEER and LAAO. This up-to-date narrative review on concomitant M-TEER and LAAO aims to summarize the current body of literature, review practical procedural considerations, and review the unmet research questions limiting the widespread adoption of this concomitant intervention.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.732
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0050.005
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.050
GPT teacher head0.370
Teacher spread0.319 · 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.

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

Citations0
Published2025
Admission routes1
Has abstractyes

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