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Record W2920986795 · doi:10.1016/j.cjco.2019.02.002

Mortality and Heart Failure After Upgrade to Cardiac Resynchronization Therapy

2019· article· en· W2920986795 on OpenAlexaff
Bogdan M. Beca, John L. Sapp, Martin J. Gardner, Christopher Gray, Amir AbdelWahab, Ciorsti MacIntyre, Steve Doucette, Ratika Parkash

Bibliographic record

VenueCJC Open · 2019
Typearticle
Languageen
FieldMedicine
TopicCardiac pacing and defibrillation studies
Canadian institutionsQueen Elizabeth II Health Sciences CentreDalhousie University
FundersSt. Jude MedicalDepartment of Health, Western Cape GovernmentMedtronic
KeywordsCardiac resynchronization therapyMedicineHazard ratioConfidence intervalInternal medicineEjection fractionHeart failureCohortRetrospective cohort studyCardiologyProportional hazards model

Abstract

fetched live from OpenAlex

BackgroundCardiac resynchronization therapy (CRT) is effective in treating advanced heart failure (HF), but data describing benefits and long-term outcomes for upgrades from a preexisting device are limited. This study sought to compare long-term outcomes in de novo CRT implants with those eligible for CRT with a prior device.MethodsThis is a retrospective cohort study using data from a provincial registry (2002-2015). Patients were included if they had mild-moderate HF, left ventricular ejection fraction ≤ 35%, and QRS duration ≥ 130 ms. Patients were classified as de novo CRT or upgraded to CRT from a prior device. Outcomes were mortality and composite mortality and HF hospitalization.ResultsThere were 342 patients included in the study. In a multivariate model, patients in the upgraded cohort (n = 233) had a higher 5-year mortality rate (adjusted hazard ratio, 2.86; 95% confidence interval, 1.59-5.15; P = 0.0005) compared with the de novo cohort (n = 109) and higher composite mortality and HF hospitalization (adjusted hazard ratio, 2.60; 95% confidence interval, 1.54-4.37; P = 0.0003).ConclusionsImplantation of de novo CRTs was associated with lower mortality and HF hospitalization compared with upgraded CRTs from preexisting devices. It is unknown whether these differences are due to the timing of CRT implementation or other clinical factors. Further work in this area may be helpful to determine how to improve outcomes for these patients.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.288
Threshold uncertainty score0.268

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0000.000

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 head0.029
GPT teacher head0.338
Teacher spread0.309 · 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.

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".

Quick stats

Citations7
Published2019
Admission routes1
Has abstractyes

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