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Valvular surgery is associated with an increased risk of post-operative atrial fibrillation: secondary analysis of the SEARCH-AF CardioLink-1 randomized trial

2022· article· en· W4306321198 on OpenAlexaffabout
Makoto Hibino, S Verma, Arjun Pandey, Adrian Quan, Atul Verma, G Bisleri, C. David Mazer, Andrew C.T. Ha

Bibliographic record

VenueEuropean Heart Journal · 2022
Typearticle
Languageen
FieldMedicine
TopicCardiac, Anesthesia and Surgical Outcomes
Canadian institutionsUniversity of TorontoSouthlake Regional Health CenterSt. Michael's Hospital
Fundersnot available
KeywordsMedicineAtrial fibrillationAtrial flutterCardiologyInternal medicineEjection fractionStroke (engine)Randomized controlled trialValve replacementMyocardial infarctionSurgeryRandomizationCardiac surgeryStenosisHeart failure

Abstract

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Abstract Background Patients undergoing valve surgery have a higher risk of developing post-operative atrial fibrillation (POAF) relative to those undergoing isolated coronary artery bypass grafting (CABG). Whether this risk extends beyond hospital discharge is unknown. Purpose We examined the association between surgery type (isolated CABG vs. valve repair/replacement) on the incidence of post-operative atrial fibrillation (POAF) by conducting a secondary analysis of the Post-Surgical Enhanced Monitoring for Cardiac Arrhythmias and Atrial Fibrillation (SEARCH-AF) CardioLink-1 randomized trial. Methods In the SEARCH-AF trial, 336 patients with risk factors for stroke (CHA2DS2-VASc score ≥2) and no history of preoperative AF were randomized to usual care or continuous cardiac rhythm monitoring for 30 days after discharge from cardiac surgery with a wearable, patched-based device. The primary outcome was occurrence of cumulative atrial fibrillation/flutter (AF/AFL) lasting for ≥6 minutes detected by continuous monitoring or AF/AFL documented by a 12-lead ECG within 30 days of randomization. We compared the risk of POAF between patients who underwent CABG vs. valve repair/replacement. Patients who experienced post-operative AF during hospitalization were excluded from this analysis. Results The overall cohort consisted of 255, 39, and 42 patients who underwent isolated CABG, isolated valve replacement/repair, and CABG + valve repair/replacement, respectively. Baseline characteristics were similar among the groups except for younger age (p=0.0014), higher prevalence of preoperative myocardial infarction (p=0.002) and lower ejection fraction (p=0.025) in the isolated CABG group. Eighteen patients experienced post-operative AF during hospitalization. Patients who underwent CABG + valve surgery or isolated valve surgery were more likely to experience post-operative AF compared with those who underwent isolated CABG (Log-Rank ptrend=0.0096). Among patients who were randomized to continuous cardiac rhythm monitoring, the probability of post-operative AF among patients who underwent isolated CABG, valve surgery, and CABG + valve surgery was 15.8%, 29.4%, and 35.0%, respectively (Log-Rank ptrend=0.017). After multivariable adjustment, the risk of developing post-operative AF within 30 days after discharge remained higher among patients who underwent valve surgery compared with those who underwent isolated CABG (hazard ratio (HR) 2.22, 95% CI 1.01–4.87. Patients who underwent CABG + repair/replacement had the highest risk of experiencing post-operative AF when compared to patients who underwent isolated CABG (HR 2.78, 95% CI 1.12–6.86). Conclusion Patients undergoing valve repair or bioprosthetic valve replacement have a substantial risk of post-operative AF within 30 days after discharge from surgery. An aggressive cardiac rhythm monitoring strategy during this vulnerable period should be considered for this high-risk patient population. Funding Acknowledgement Type of funding sources: Other. Main funding source(s): Heart and Stroke Foundation of Canada

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)0.003
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0040.005
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0050.000

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 head0.025
GPT teacher head0.285
Teacher spread0.260 · 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 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".

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Citations0
Published2022
Admission routes2
Has abstractyes

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