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Record W4386776236 · doi:10.1016/j.cjco.2023.09.008

Change of HeART: Cardiovascular Implications of Assisted Reproductive Technology

2023· review· en· W4386776236 on OpenAlexaffabout
Elaha Niazi, Sandra M. Dumanski

Bibliographic record

VenueCJC Open · 2023
Typereview
Languageen
FieldMedicine
TopicAssisted Reproductive Technology and Twin Pregnancy
Canadian institutionsLibin Cardiovascular Institute of AlbertaUniversity of Calgary
Fundersnot available
KeywordsMedicineCardiologyInternal medicine

Abstract

fetched live from OpenAlex

Cardiovascular (CV) disease is the leading cause of death in women, and it may manifest differently than in men, in part related to sex-specific CV risk factors. In females, assisted reproductive technologies (ARTs) are commonly used to treat infertility, and they utilize controlled ovarian stimulation involving the administration of exogenous sex hormones. ARTs, and especially controlled ovarian stimulation, have been associated with an increased pregnancy and short-term CV risk, although the long-term CV implications of these treatments in individuals treated with ARTs and their offspring remain unclear. This review endeavors to provide a comprehensive examination of what is known about the relationship between ART and CV outcomes for females treated with ARTs, as well as their offspring, and recommendations for future research. Novel insights into female-specific CV risk factors are critical to reduce the disproportionate burden of CV disease in Canadian women. ART has revolutionized reproductive medicine, offering hope to millions of individuals with infertility worldwide, and a further understanding of the CV implications of this important sex-specific CV risk factor is warranted urgently.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.006
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0060.001

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 head0.186
GPT teacher head0.414
Teacher spread0.228 · 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 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

Citations7
Published2023
Admission routes2
Has abstractyes

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