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Record W2331985163 · doi:10.1097/hco.0000000000000150

Gender differences in outcomes following cardiac surgery

2015· article· en· W2331985163 on OpenAlexaff
Anthony Tran, Marc Ruel, Vincent Chan

Bibliographic record

VenueCurrent Opinion in Cardiology · 2015
Typearticle
Languageen
FieldMedicine
TopicCardiac Valve Diseases and Treatments
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsMedicinevalvular heart diseasePresentation (obstetrics)Cardiac surgeryCoronary artery diseaseMitral valveDiseaseReferralHeart valveCardiologyInternal medicineHeart diseaseSurgery

Abstract

fetched live from OpenAlex

PURPOSE OF REVIEW: This review summarizes the differences in clinical outcomes following cardiac surgery according to gender. RECENT FINDINGS: Women comprise a large proportion of patients presenting with coronary artery or valvular heart disease. Although it is well known that women have poorer survival following bypass surgery compared with men, more recent data confirm that women also have poorer outcomes after heart valve surgery. Women are also more likely to receive mitral valve replacement instead of repair, when compared with men. These divergent outcomes are because of many factors, including valve disease and clinical presentation, which may result in delayed surgical referral in women. SUMMARY: Factors that result in poorer outcomes following heart valve surgery, including mitral valve surgery, between men and women remain incompletely understood. These may relate to differences in clinical presentation, valve morphology, and physiology. Further research is needed to clarify differences in heart valve outcomes according to gender.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.179
GPT teacher head0.427
Teacher spread0.248 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations12
Published2015
Admission routes1
Has abstractyes

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