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Record W4386878555 · doi:10.1093/ehjcvp/pvad054

Cardiovascular preventive actions

2023· editorial· en· W4386878555 on OpenAlexaboutno aff
Stefan Agewall

Bibliographic record

VenueEuropean Heart Journal - Cardiovascular Pharmacotherapy · 2023
Typeeditorial
Languageen
FieldMedicine
TopicLipoproteins and Cardiovascular Health
Canadian institutionsnot available
Fundersnot available
KeywordsMedicine

Abstract

fetched live from OpenAlex

Chronic hepatitis C virus ( HCV ) infection has been associated with inflammation of the cardiovascular system, which in turn might be associated with cardiovascular disease. 1 -5 Dr Wu and co-workers from Taiwan aimed to investigate the impac t of direc t-ac ting antivirals ( DAA s ) on HC V-associated cardiovascular event retrospective cohort study.The authors concluded that chronic HCV patients treated with DAAs experienced lower rates of cardiovascular events and all-cause mortality than those without treatment.Anthracyclines can cause cancer therapy related cardiac dysfunction ( CTRCD ) . 6 -10Dr Thavendiranathan and co-workers from Canada aimed to assess whether statins prevent decline in left ventricular ejection fraction ( LVEF ) in anthracycline-treated patients at increased risk for CTRCD in a multicentre double-blinded, placebo-controlled trial and patients with cancer who were at increased risk of anthracyclinerelated CTRCD ( per ASCO guidelines ) .The patients were randomly assigned to atorvastatin 40 mg or placebo once daily.Cardiovascular magnetic resonance ( CMR ) imaging was performed before and within 4 weeks after anthracyclines.Blood biomarkers were measured at every cycle.The authors concluded that primary prevention with atorvastatin during anthracycline therapy did not ameliorate LVEF decline, LV remodelling , C TRCD, change in serum cardiac biomarkers, or CMR myocardial tissue changes.Current pharmacogenetic guidelines require sequencing of the SLCO1B1 gene, which is more expensive and less accessible than genotyping.Variants in SLCO1B1, which encodes the hepatic transporter OATB1B1, influence statin pharmacokinetics, resulting in an altered plasma concentration of the drug and its met abolites . 11Dr Siddiqui et al. from the UK aimed to develop an easy, clinically implementable functional gene risk score of common variants in SLCO1B1 to identify patients at risk of statin intolerance.The authors concluded that a gene risk score based on four common SLCO1B1 variants provides an easily implemented genetic tool that is more reliable than the current recommended practice in estimating the risk and predicting early-onset statin intolerance.Guideline recommendations 12 for the treatment of heart failure with mildly reduced ejection fraction ( HFmrEF ) derive from small subgroups in post-hoc analyses of randomized trials.Dr Savarese and co-workers investigated predictors of renin-angiotensin system inhibitors/angiotensin receptor neprilysin inhibitors ( RASIs/ARNIs ) and beta-blocker use 13 , and the associations between these medications and mortalit y/morbidit y in a large real-world cohort with HFmrEF.Patients with HFmrEF ( EF 40-49% ) from the Swedish HF Registry

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)0.016
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Meta-epidemiology (broad), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Editorial · Consensus signal: Editorial
Teacher disagreement score0.118
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0160.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.028
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.007
Insufficient payload (model declined to judge)0.0000.003

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 head0.047
GPT teacher head0.346
Teacher spread0.299 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreEditorial

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

Citations1
Published2023
Admission routes1
Has abstractyes

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