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Relationship of electrocardiographic left ventricular hypertrophy to mortality and cardiovascular morbidity in high-risk patients

2003· article· en· W4244032973 on OpenAlexaff
Eva Lonn, James Mathew, Janice Pogue, David E. Johnstone, Kola Danisa, Jackie Bosch, Michael G. Baird, Gilles R. Dagenais, Peter Sleight, Salim Yusuf

Bibliographic record

VenueEuropean Journal of Cardiovascular Prevention & Rehabilitation · 2003
Typearticle
Languageen
FieldMedicine
TopicBlood Pressure and Hypertension Studies
Canadian institutionsMcMaster University
Fundersnot available
KeywordsMedicineLeft ventricular hypertrophyCardiologyInternal medicineHeart failureRamiprilStroke (engine)Diabetes mellitusCoronary artery diseaseBlood pressure

Abstract

fetched live from OpenAlex

The prognostic significance of left ventricular hypertrophy (LVH) identified by simple electrocardiographic (ECG) criteria in high-risk patients with established cardiovascular (CV) diseases is not clearly understood.The Heart Outcomes Prevention Evaluation (HOPE) trial was a randomized trial, which evaluated the effects of ramipril and of vitamin E on major CV outcomes in 9541 men and women aged 55 years or older with a history of coronary artery disease, stroke, peripheral vascular disease or diabetes mellitus with at least one additional CV risk factor. Patients were followed for an average of 4.5 years. We evaluated the association between simple ECG criteria for LVH and the risk for major vascular events, for CV and all-cause mortality and for heart failure.Electrocardiographic LVH was present in 793 (8.3%) HOPE study participants. Of these, 19.0% sustained a major CV event (MI, stroke or CV death), 15.6% died and 6.1% developed heart failure compared with 15.6%, 10.8% and 2.9% respectively of those without ECG-LVH (P = 0.0023; P < 0.0001 and P < 0.0001). In multivariate analysis ECG-LVH was an independent predictor of CV and all-cause death and of heart failure.In patients with CV disease simple, easily applicable ECG criteria for LVH identify a subset of individuals at particularly high risk for death and for heart failure.

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)0.007
metaresearch head score (Gemma)0.002
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 score0.030
Threshold uncertainty score0.733

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.002
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 head0.020
GPT teacher head0.243
Teacher spread0.223 · 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

Citations35
Published2003
Admission routes1
Has abstractyes

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