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Record W4392364555 · doi:10.1139/cjpp-2023-0390

Impact of biological sex on valvular heart disease, interventions, and outcomes

2024· review· en· W4392364555 on OpenAlexaffvenue
Evan J. Wiens, Kristal L. Kawa, Malek Kass, Ashish H. Shah

Bibliographic record

VenueCanadian Journal of Physiology and Pharmacology · 2024
Typereview
Languageen
FieldMedicine
TopicCardiovascular Issues in Pregnancy
Canadian institutionsUniversity of ManitobaUniversity of Alberta
Fundersnot available
KeywordsMedicinePregnancyPresentation (obstetrics)Diseasevalvular heart diseasePathophysiologyEpidemiologyPsychological interventionHeart diseaseIntensive care medicineInternal medicineSurgeryPsychiatry

Abstract

fetched live from OpenAlex

Valvular heart disease (VHD) is common, affecting >14% of individuals aged >75, and is associated with morbidity, including heart failure and arrhythmia, and risk of early mortality. Increasingly, important sex differences are being found between males and females with VHD. These sex differences can involve the epidemiology, pathophysiology, presentation, diagnosis, and outcomes of the disease. Females are often disadvantaged, and female sex has been shown to be associated with delayed diagnosis and inferior outcomes in various forms of VHD. In addition, the unique pathophysiologic state of pregnancy is associated with increased risk for maternal and fetal morbidity and mortality in many forms of VHD. Therefore, understanding and recognizing these sex differences, and familiarity with the attendant risks of pregnancy and management of pregnant females with VHD, is of great importance for any primary care or cardiovascular medicine practitioner caring for the female patient. This review will outline sex differences in aortic, mitral, pulmonic, and tricuspid VHD, with particular focus on differences in pathophysiology, clinical presentation, and outcomes. In addition, the pathophysiology and management implications of pregnancy will be discussed.

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)0.000
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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.807
Threshold uncertainty score0.737

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.073
GPT teacher head0.436
Teacher spread0.364 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations6
Published2024
Admission routes2
Has abstractyes

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