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Abstract 4138912: Clinical outcomes of cardiac synchronization with or without an implantable cardioverter defibrillator based on pooled data from 5 clinical trials: a patient-level meta-analysis

2024· article· en· W4404364008 on OpenAlexaff
Ilya Y. Shadrin, Lurdes Y. T. Inoue, Gillian Sanders Schmidler, Michael MacKenzie, Daniel J. Friedman, William T. Abraham, John Cleland, Anne B. Curtis, Michael R. Gold, V. Kutyifa, Cecilia Linde, James B. Young, Anthony Tang, Sana M. Al‐Khatib

Bibliographic record

VenueCirculation · 2024
Typearticle
Languageen
FieldMedicine
TopicNeurological disorders and treatments
Canadian institutionsWestern University
Fundersnot available
KeywordsMedicineMeta-analysisImplantable cardioverter-defibrillatorPatient dataClinical trialSudden cardiac deathCardiologyInternal medicinePooled analysisIntensive care medicine

Abstract

fetched live from OpenAlex

Background: Cardiac resynchronization therapy (CRT) is a well-established therapy for patients with heart failure with reduced ejection fraction (HFrEF) and wide QRS. Whether CRT-defibrillators (CRT-D) reduce mortality more than CRT-pacemakers (CRT-P) remains controversial. Aims: To compare the clinical outcomes of CRT-D vs CRT-P using data from 5 landmark CRT trials, both overall and stratified by etiology of cardiomyopathy (ischemic vs non-ischemic), sex (male vs female), age (≥ 70 y/o vs < 70 y/o), and QRS morphology (IVCD, LBBB, RBBB). Methods: We performed a meta-analysis of patient level data from 5 prospective CRT trials (MIRACLE, REVERSE, RAFT, COMPANION and MADIT-CRT). Inclusion criteria were CRT-P vs CRT-D status (randomized comparison only in COMPANION), age ≥ 18 y/o and LVEF ≤ 35%. Exclusion criteria included secondary prevention ICD, QRS < 120ms, pacemaker upgrade, ventricular pacing indication, or missing data. Primary outcome was composite of time to heart failure hospitalization (HFH) or all-cause death. Secondary outcomes were time to HFH and death. Outcomes were analyzed using a frequentist Cox Proportional Hazards mixed effects model adjusted for 17 variables. Results: A total of 3407 patients met inclusion criteria. Relative to patients with CRT-P (n=843), those with CRT-D (n=2564) were of similar age (66 y/o, p=0.5), less often female (24% vs 34%, p<0.001), and more often had ischemic cardiomyopathy (59.4% vs 52.4%, p<0.001), Fig 1A. Primary outcome was similar across groups (HR 0.902 [0.752, 1.081], p=0.26), but all-cause mortality was lower with CRT-D vs CRT-P (HR 0.77 [0.603, 0.983], p=0.036), Fig 1B. Interaction analyses suggested lower all-cause mortality with CRT-D vs CRT-P in patients with non-ischemic cardiomyopathy (HR 0.502 [0.346, 0.726], p=0.0003) and patients age ≥70 y/o (HR 0.679 [0.502, 0.919], p=0.012), with significance preserved after Bonferroni correction (Fig 1B). Conclusion: In patients receiving CRT for HFrEF, those with CRT-D had lower all-cause mortality than patients with CRT-P, driven mainly by a lower mortality with CRT-D in older patients and those with non-ischemic cardiomyopathy. No significant interactions were noted between ICD&sex or ICD&QRS morphology.

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)0.017
metaresearch head score (Gemma)0.026
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.017
Threshold uncertainty score0.088

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0170.026
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0160.055
Bibliometrics0.0040.005
Science and technology studies0.0000.001
Scholarly communication0.0040.002
Open science0.0020.002
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0050.001

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 head0.411
GPT teacher head0.462
Teacher spread0.051 · 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 designMeta-analysis
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

Citations0
Published2024
Admission routes1
Has abstractyes

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