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Record W2033721752 · doi:10.1016/s1474-5151(09)60102-x

52 Do The Heart Transplant Patients Ask About Their Erectile Dysfunction to the Nurse?

2009· article· en· W2033721752 on OpenAlexaff
Carmen Segura Saint-Gerons, C Castillo Pedraza, Ana Segura, Miguel Sánchez, Miguel Ángel Muñoz, E. Bujalance, Carolina Dominguez Maldonado, Carlos Yanguas, José M. Arizón

Bibliographic record

VenueEuropean Journal of Cardiovascular Nursing · 2009
Typearticle
Languageen
FieldSocial Sciences
TopicWorkplace Violence and Bullying
Canadian institutionsDalhousie UniversityUniversity of CalgaryUniversity of Alberta
Fundersnot available
KeywordsMedicineErectile dysfunctionAsk priceIntensive care medicineHeart transplantationCardiologyInternal medicineHeart failure

Abstract

fetched live from OpenAlex

Purpose: There is a direct association between coronary disease and erectile dysfunction (ED). The objective of this study was to evaluate the incidence of patients who suffer from ED after a heart transplant and to identify the percentage of patients who consult a healthcare professional after their erectile function has decreased. Methods: Epidemiological, single centre, retrospective study. We reviewed the medical history of patients subjected to heart transplant and sexual history was completed during a single visit. The following data was obtained for each patient: demographic data and medication. ED was diagnosed by the SQUED screening interview. Results: 113 male patients who had suffered heart transplants were selected, with a mean age of 54.8 years. 92.9% of the patients were receiving concomitant treatment with corticoids, 81.4% with anti-ulcer agents and 80.5% with hypolipaemic agents. With regards to the use of immune suppressants, 79% of the patients were under treatment with cyclosporin, 72% with azathioprine, 21% with tacrolimus, 20% with mycophenolate mofetil and 8% with other immune suppressors. 18.6% of the patients suffered from diabetes mellitus, 28.6% of whom were not controlled with pharmacological treatment. 28.3% of the patients presented ED prior to surgery and 92.9% after surgery (p< 0.0001, Mc

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)0.005
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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.908
Threshold uncertainty score0.869

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
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 head0.011
GPT teacher head0.242
Teacher spread0.231 · 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 designOther design
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

Citations0
Published2009
Admission routes1
Has abstractyes

Explore more

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