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Record W4396925129 · doi:10.1016/j.eclinm.2024.102603

Permanent pacemaker reduction using temporary-permanent pacemaker as a 1-month bridge after transcatheter aortic valve replacement: a prospective, multicentre, single-arm, observational study

2024· article· en· W4396925129 on OpenAlexaff
Sanshuai Chang, Zhengming Jiang, Xinmin Liu, Yi‐Da Tang, Ming Bai, Jizhe Xu, Haiping Wang, Yuguo Chen, Chuanbao Li, Yundai Chen, Changfu Liu, Jianzeng Dong, Jianfang Luo, Jie Li, Guosheng Fu, Sheng Wang, Hui Huang, Yuewu Zhao, Xi-Jin Zhuang, Hasan Jilaihawi, Nicolò Piazza, Feicheng Yu, Thomas Modine, Guangyuan Song

Bibliographic record

VenueEClinicalMedicine · 2024
Typearticle
Languageen
FieldMedicine
TopicCardiac Valve Diseases and Treatments
Canadian institutionsMcGill University Health Centre
FundersBeijing Municipal Science and Technology CommissionEdwards LifesciencesMedtronic
KeywordsMedicineObservational studyPermanent pacemakerReduction (mathematics)CardiologyBridge (graph theory)Valve replacementSurgeryInternal medicineStenosis

Abstract

fetched live from OpenAlex

Background: The permanent pacemaker (PPM) implantation and pacemaker dependency rates after transcatheter aortic valve replacement (TAVR) are highly variable as some of the conduction disturbances are reversible. It remains poorly investigated how to optimise temporary pacing in these patients. This study aimed to explore the potential reduction in the PPM implantation rate using temporary-permanent pacemaker (TPPM) as a 1-month bridge. Methods: This is a prospective, multicentre, single-arm, observational study. Consecutive patients undergoing TAVR from March 1, 2022 to March 1, 2023 in 13 tertiary hospitals in China were screened. Patients who developed high-degree atrioventricular block, complete heart block, or first-degree atrioventricular block plus new onset left bundle branch block during the TAVR procedure or within 1 month after TAVR were included to receive TPPM. Patients with pre-existing PPM implantation or indications for PPM implantation before the TAVR procedure were excluded. Patients with TPPM were monitored to determine whether the conduction disturbances persisted or recovered. The primary endpoint was the rate of freedom from indications for PPM implantation 1 month after TAVR. This study is registered with ChiCTR, ChiCTR2200057931. Findings: Of 688 patients who have undergone TAVR, 71 developed conduction disturbance and met the inclusion criteria, 1 patient withdrew due to noncompliance, 70 patients received TPPM and completed follow-up. There were 41 (58.6%) men and 29 (41.4%) women in the study, with a mean age of 74.3 ± 7.3 years. At 1 month follow-up, 75.7% (53/70) of the patients with TPPM did not require PPM implantation. For 688 patients who have undergone TAVR, the rate of PPM implantation at 1 month was 2.47% (17/688, 95% CI 1.55%-3.92%), representing a significant reduction in self-comparison with the rate at 48 h after TPPM (2.47% vs. 8.28% [95% CI 6.45%-10.58%], P < 0.0001). Similar results were obtained in the subgroup analysis of patients with HAVB/CHB. Multivariate analysis revealed the baseline PR interval, difference between the membranous septum length and implantation depth, and timing of postprocedural conduction disturbance occurrence were independent predictors of freedom from indications for PPM implantation at 1 month after TAVR. Interpretation: Using TPPM as a 1-month bridge allows for a buffer period to distinguish whether conduction disturbances are reversible or persistent, resulting in a significant reduction in the PPM implantation rate after TAVR when compared with the current strategy. However, this is an observational study, the results need to be confirmed in a randomized trial. Funding: Beijing Science and Technology Plan 2022 from Beijing Municipal Science & Technology Commission.

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), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.083
GPT teacher head0.404
Teacher spread0.321 · 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 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

Citations13
Published2024
Admission routes1
Has abstractyes

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