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Record W2912555880 · doi:10.4081/monaldi.2018.988

The impact of gender in cardiovascular medicine: Lessons from the gender/sex-issue in heart failure

2018· review· en· W2912555880 on OpenAlex
Alberto M. Marra, Andrea Salzano, Michele Arcopinto, Lucrezia Piccioli, Valeria Raparelli

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.

Bibliographic record

VenueMonaldi Archives for Chest Disease · 2018
Typereview
Languageen
FieldMedicine
TopicHeart Failure Treatment and Management
Canadian institutionsMcGill University Health Centre
Fundersnot available
KeywordsHeart failureMedicineEpidemiologyEjection fractionHealth careCardiovascular healthIncidence (geometry)Sex characteristicsGerontologyIntensive care medicineInternal medicineDemographyDiseasePolitical science

Abstract

fetched live from OpenAlex

Heart Failure (HF) is a major healthcare issue, given its high prevalence and incidence, the rate of comorbidities, the related high health-care costs and its poor outcome. In the last years mounting evidence revealed several differences between men and women affected by this clinical condition. Apart from the well-known difference in phenotype (HF with reduced ejection fraction (HFrEF) occurs more commonly in men, and HF with preserved ejection fraction (HFpEF) is more frequent in women) other relevant sex-related issues dwell upon epidemiology, presentation, risk stratification and management. These differences shed new lights on the possibility to consider HF as a prototype of the impact of gender/sex issue in cardiovascular medicine. A call for action and future strategies might help in the achievement of a cleaver patient-care.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.775
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.071
GPT teacher head0.366
Teacher spread0.295 · 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