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Record W4378233709 · doi:10.1093/europace/euad122.355

Left bundle brunch pacing versus conventional right ventricular pacing in patients with bradycardia and conduction system disorders: a systematic review and meta-analysis

2023· review· en· W4378233709 on OpenAlexaboutno aff
Christoforos K Travlos, Georgios Leventopoulos, Vasso Anagnostopoulou, Panagiotis Patrinos, Angelos Perperis, Rafail Koros, Angeliki Papageorgiou, Periklis Davlouros

Bibliographic record

VenueEP Europace · 2023
Typereview
Languageen
FieldMedicine
TopicCardiac pacing and defibrillation studies
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineMeta-analysisQRS complexConfidence intervalBradycardiaInternal medicineEjection fractionCardiologyRandomized controlled trialHazard ratioObservational studyRelative riskPublication biasHeart failureHeart rate

Abstract

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Abstract Funding Acknowledgements Type of funding sources: None. Background Right Ventricular Pacing (RVP) is well established as the widely accepted pacing method. However, its effects in ventricular function can be detrimental, causing electrical and mechanical dysynchrony and potential LVEF impairment. Left Bundle Branch Pacing (LBBP) is a new pacing strategy that appears to have better results preserving left ventricular function, by directly engaging the intrinsic conduction pathway of the heart. Purpose The aim of this systematic review and meta-analysis is to compare the safety and efficacy of the two pacing methods (LBBP and RVP) in patients suffering from bradyarrhythmia and conduction system disorders. Methods Medline, Embase and Pubmed databases were searched for studies comparing LBBP with RVP. Outcomes were QRSd (QRS duration), ventricular mechanical synchrony, LVEF changes, and Heart Failure Hospitalizations (HFH) to assess the efficacy, lead properties and complications to assess the safety. Two independent reviewers identified studies, extracted data, and assessed the risk of bias using the Cochrane Risk of Bias 2 tool for randomized clinical trials and the Newcastle-Ottawa-Scale for observational studies. Pairwise meta-analysis was conducted using random and fixed effects models. Risk Ratios (RRs) and weighted and standard mean difference (WMD, SMD) with 95% confidence intervals (CIs) were used to report dichotomous and continuous variables respectively. Heterogeneity was assessed with the I² statistic. Results 1318 articles were identified, and finally 25 trials with 4250 patients (2127 LBBP and 2123 RVP) were included in the analysis. Pooled analyses verified that QRSd is shorter in LBBP group both at implantation (WMD:-32.32, CI 95%:-35.18 to -29.45; I²=88%; P<.001) and at Follow Up (WMD: -32.20, CI 95%: -40.70 to -23.71; I²=92%; P<.001) and LBBP succeeded better interventricular mechanical synchrony (SMD:-2.04, CI 95%:-2.32 to -1.76; I²=21%; P<.001) than RVP. Intraventricular mechanical synchrony was also significantly better in LBBP vs RVP independently of the way of measurement in each study (SMD:-1.77, CI 95%:-2.45 to -1.09; I²=90%; P<.001) and in the subgroup analysis of the studies that implemented the same way of measurement (P<.001; I²=26%). LVEF alteration was not significant in the LBBP compared to native (P=.68; I²=52%), while in the RVP group showed a significant reduction (P<.001; I²=51%). LBBP showed, significantly better results in HFH (P<.001; I²=0%) and achieved similar pacing thresholds (P=.86) and higher R wave amplitudes (P<.05) than RVP while lead related complications had no difference between the two groups (LBBP=1.90% vs RVP=1.72%; P=0.71). Conclusions To our knowledge this is the first meta-analysis that assess the safety and efficacy of LBBP in such an important number of patients. LBBP preserves ventricular electrical and mechanical synchrony, shows a reduction in HFH compared to RVP and has excellent pacing parameters, without compromising safety.

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: Meta-analysis · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.808
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0080.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.058
GPT teacher head0.320
Teacher spread0.263 · 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 designMeta-analysis
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

Citations4
Published2023
Admission routes1
Has abstractyes

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