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Record W3082155586 · doi:10.1186/s12890-020-01272-x

Worsening pulmonary outcomes during sex reassignment therapy in a transgender female with cystic fibrosis (CF) and asthma/allergic bronchopulmonary aspergillosis: a case report

2020· article· en· W3082155586 on OpenAlexafffund
Grace Y. Lam, Jodi Goodwin, Pearce Wilcox, Bradley S. Quon

Bibliographic record

VenueBMC Pulmonary Medicine · 2020
Typearticle
Languageen
FieldMedicine
TopicCystic Fibrosis Research Advances
Canadian institutionsCystic Fibrosis CanadaSt. Paul's HospitalUniversity of British Columbia
FundersMichael Smith Health Research BCCystic Fibrosis CanadaGilead Sciences
KeywordsMedicineAllergic bronchopulmonary aspergillosisAsthmaCystic fibrosisContext (archaeology)EstrogenPulmonary function testingPulmonary fibrosisDiseaseLungInternal medicinePediatricsImmunology

Abstract

fetched live from OpenAlex

BACKGROUND: Cystic Fibrosis (CF) is a hereditary pulmonary and extra-pulmonary disease that occurs equally in men and women. However, a difference in morbidity and mortality rates between the sexes has been long documented. Similarly, a sex-disparity in disease severity has been reported in asthma as well. Studies done to date point to estrogen as a possible cause of this sex disparity in pulmonary outcomes in both conditions. CASE PRESENTATION: Here, we describe a case of a patient with CF and asthma/allergic bronchopulmonary aspergillosis (ABPA) undergoing sex reassignment therapy (male-to-female) and the negative impact it had on her lung function and frequency of pulmonary exacerbations in the context of increasing doses of exogenous estrogen. CONCLUSIONS: This case raises the possibility of a link between estrogen and worsening pulmonary outcomes and the need for further studies into transgender individuals with CF and/or asthma/ABPA as well as those undergoing high dose estrogen therapy for other indications.

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)0.000
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: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0020.000

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 head0.037
GPT teacher head0.300
Teacher spread0.263 · 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 designCase report
Domainnot available
GenreEmpirical

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

Citations10
Published2020
Admission routes2
Has abstractyes

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