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Record W2939292844 · doi:10.1080/14779072.2019.1606713

Cardiac arrhythmias secondary to hormone therapy in trans women

2019· review· en· W2939292844 on OpenAlexaff
Rachel Wamboldt, Sohaib Haseeb, Ashley Waddington, Adrián Baranchuk

Bibliographic record

VenueExpert Review of Cardiovascular Therapy · 2019
Typereview
Languageen
FieldMedicine
TopicHormonal and reproductive studies
Canadian institutionsQueen's University
Fundersnot available
KeywordsMedicineTestosterone (patch)TransgenderHormone therapyHormoneEstrogenIncidence (geometry)Internal medicineDiseaseAtrial fibrillationCardiologyBreast cancerCancer

Abstract

fetched live from OpenAlex

Introduction: With greater social acceptance and the evolution of transgender medicine as a specialty, more trans women are seeking hormone therapy (HT). Several studies have identified an increase in cardiovascular disease in trans women, however no studies have investigated the incidence of arrhythmias. Using two cases from the authors’ clinic as examples, we propose that hormone therapy in trans women may increase the risk of cardiac arrhythmias.Areas covered: A literature search of sex hormones and cardiac arrhythmias was conducted. Using sex hormone studies completed in cis individuals and animal models we identified several similarities to trans women on HT. In cis men, low levels of testosterone are associated with increased rates of atrial fibrillation and right ventricular outflow tract arrhythmias. The role of estradiol remains less clear but there is evidence to suggest that the administration of exogenous estrogen may increase the rates of cardiac arrhythmias in cis women.Expert opinion: Research in the field of transgender medicine is expanding. As more trans women initiate HT, we will have a larger database from which to collect information regarding the benefits and risks of treatment, including the potential side effect of arrhythmias.

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)0.003
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 score0.933
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0130.009
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.046
GPT teacher head0.340
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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

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

Citations22
Published2019
Admission routes1
Has abstractyes

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