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Record W4386466601 · doi:10.1002/ejhf.3029

Comorbidities and Clinical Response to Cardiac Resynchronization Therapy: Patient-Level Meta-Analysis from Eight Clinical Trials

2023· review· en· W4386466601 on OpenAlexaff
Marat Fudim, Frederik Dalgaard, Daniel J. Friedman, William T. Abraham, John G.F. Cleland, Anne B. Curtis, Michael R. Gold, Valentina Kutyifa, Cecilia Linde, Fatima Ali‐Ahmed, Anthony Tang, Antonio Olivas‐Martínez, Lurdes Y. T. Inoue, Sana M. Al‐Khatib, Gillian D Sanders

Bibliographic record

VenueEuropean Journal of Heart Failure · 2023
Typereview
Languageen
FieldMedicine
TopicCardiac pacing and defibrillation studies
Canadian institutionsWestern University
FundersBiosense WebsterNational Heart, Lung, and Blood InstituteRespicardiaIdorsia PharmaceuticalsBritish Heart FoundationMerit Medical SystemsJanssen PharmaceuticalsMyoKardiaBoston Scientific CorporationBristol-Myers SquibbAtriCureAmerican Heart AssociationSanofiServierAmgen
KeywordsMedicineComorbidityInternal medicineHeart failureCardiac resynchronization therapyHazard ratioAtrial fibrillationDiscontinuationCardiologyCoronary artery diseaseConfidence intervalRandomized controlled trialEjection fraction

Abstract

fetched live from OpenAlex

AIMS: Patients with heart failure usually have several other medical conditions that might alter the effects of interventions. We investigated whether the burden of comorbidity modified the clinical response to cardiac resynchronization therapy (CRT). METHODS AND RESULTS: Original patient-level data from eight randomized trials exploring the effects of CRT versus no CRT were pooled (BLOCK-HF, MIRACLE, MIRACLE-ICD, MIRACLE-ICD II, RAFT, COMPANION, MADIT-CRT and REVERSE). A prior history of the following comorbidities was considered: episodic or persistent atrial fibrillation (n = 920), coronary artery disease (n = 3732), diabetes (n = 2171), and hypertension (n = 3353). Patients were classified into three groups based on the number of comorbidities: 0, 1-2, or ≥3. The outcomes of interest were time to all-cause mortality and time to the composite outcome of heart failure hospitalization (HFH) or all-cause mortality. Outcomes were evaluated within each comorbidity group using a Bayesian hierarchical Weibull survival regression model. Of 6324 patients, 970 (15%) had no comorbidities, 4052 (64%) had 1-2 and 1302 (21%) had ≥3 comorbidities. The adjusted hazard ratio (aHR) for CRT versus no CRT for all-cause mortality in the overall cohort was 0.79 (95% credible interval [CI] 0.68-0.93) (p = 0.010); for no comorbidities the aHR was 0.54 (95% CI 0.34-0.86), for 1-2 comorbidities was 0.81 (95% CI 0.67-0.97) and for ≥3 comorbidities was 0.83 (95% CI 0.64-1.07) (no significant interaction between CRT and comorbidity burden: p = 0.13). For the endpoint of HFH or all-cause mortality, the aHR for the overall cohort was 0.74 (95% CI 0.65-0.84) (p = 0.001), for no comorbidities was 0.69 (95% CI 0.50-0.94), for 1-2 comorbidities was 0.77 (95% CI 0.66-0.90) and for ≥3 comorbidities was 0.68 (95% CI 0.55-0.82) (no significant interaction between CRT and comorbidity burden: p = 0.081). CONCLUSION: In a meta-analysis of patient-level data from eight major trials, the totality of evidence suggests that CRT reduces HFH and/or all-cause mortality even when several comorbid diseases are present. CLINICAL TRIAL REGISTRATION: NCT00271154, NCT00251251, NCT00267098, NCT00180271.

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)0.022
metaresearch head score (Gemma)0.035
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: Review · Consensus signal: Review
Teacher disagreement score0.022
Threshold uncertainty score0.117

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0220.035
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0130.043
Bibliometrics0.0030.005
Science and technology studies0.0010.001
Scholarly communication0.0030.001
Open science0.0020.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.567
GPT teacher head0.513
Teacher spread0.054 · 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
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

Citations6
Published2023
Admission routes1
Has abstractyes

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