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Left Ventricular End‐Diastolic Pressure and Risk of Subsequent Heart Failure in Patients Following an Acute Myocardial Infarction

2007· article· en· W1980675477 on OpenAlexaff
Lisa Mielniczuk, Gervasio A. Lamas, Greg C. Flaker, Gary F. Mitchell, Sidney C. Smith, Bernard J. Gersh, Scott D. Solomon, Lemuel A. Moyé, Jean L. Rouleau, John D. Rutherford, Marc A. Pfeffer

Bibliographic record

VenueCongestive Heart Failure · 2007
Typearticle
Languageen
FieldMedicine
TopicCardiovascular Function and Risk Factors
Canadian institutionsUniversité de MontréalUniversity of Ottawa
Fundersnot available
KeywordsPreloadMedicineCardiologyInternal medicineMyocardial infarctionHazard ratioHeart failureConfidence intervalDiastoleVentricular pressureBlood pressureHemodynamics

Abstract

fetched live from OpenAlex

Left ventricular end-diastolic pressure (LVEDP) is an important measure of ventricular performance and may identify patients at increased risk for developing late clinical symptoms of heart failure (HF). The primary outcome in this analysis of 744 patients from the Survival and Ventricular Enlargement (SAVE) trial was the development of death or HF over a mean time of 36 months. The mean LVEDP for all patients was 23+/-9 mm Hg, and 75% of participants (n=558) had an LVEDP >15 mm Hg. Patients with an LVEDP >30 mm Hg (n=187) had the highest risk of death or HF (unadjusted hazard ratio, 1.40; 95% confidence interval [CI], 1.00-1.97) when compared with the other 2 cohorts combined (n=603). After adjustment for other known predictors of cardiac risk, LVEDP no longer remained significant (adjusted hazard ratio, 1.12; 95% CI, 0.77-1.65). Elevated LVEDP is common following myocardial infarction; however, it is not an independent predictor of subsequent HF risk. The variability in LVEDP is not fully explained by infarct size and atherosclerotic burden.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.060
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.007
GPT teacher head0.241
Teacher spread0.235 · 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

Citations80
Published2007
Admission routes1
Has abstractyes

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