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Record W2808943614 · doi:10.1002/ehf2.12307

Sex, Drugs, and Heart Failure: A Sex-Sensitive Review of the Evidence Base Behind Current Heart Failure Clinical Guidelines

2018· review· en· W2808943614 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueESC Heart Failure · 2018
Typereview
Languageen
FieldMedicine
TopicHeart Failure Treatment and Management
Canadian institutionsUniversité de MontréalMontreal Heart Institute
FundersCanadian Institutes of Health Research
KeywordsMedicineHeart failureEtiologyClinical trialEjection fractionRandomized controlled trialPopulationHeart failure with preserved ejection fractionIntensive care medicineDiseaseInternal medicine

Abstract

fetched live from OpenAlex

Heart failure (HF) is a complex disease, almost as common in women as in men. Nonetheless, HF clinical presentation, prognosis, and aetiology vary by sex. This review summarizes the current state of sex-sensitive issues related to HF drugs included in treatment guidelines and suggests future directions for improved care. Heart failure presentation differs between female and male patients: females more often show with hypertensive aetiology and the preserved ejection fraction phenotype, while men more often show ischaemic aetiology and the reduced ejection fraction phenotype. Yet the HF clinical guidelines in Europe, the United States, and Canada do not reflect the sexual dimorphism. Further, in randomized clinical trials of HF medication, women are largely underrepresented, typically consisting of ≥70% men. Given the knowledge that some adverse drug reactions, such as torsade de pointes and angiotensin-converting enzyme inhibitor-induced cough, occur more frequently in women, we emphasize the need to test medications thoroughly in both sexes and explore sexual dimorphisms. To better represent all of the targeted patient population and provide better care for all, two kinds of change must come about: recruitment methods to randomized clinical trial samples need to evolve and the participation needs to seem more attractive to women.

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.

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)0.005
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesMeta-epidemiology (narrow)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.185
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.003
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0070.003
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0010.001

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 head0.116
GPT teacher head0.426
Teacher spread0.311 · 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