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Record W2142285596

Andropause. Testosterone replacement therapy for aging men.

2001· article· en· W2142285596 on OpenAlexaff
Jerald Bain

Bibliographic record

VenuePubMed · 2001
Typearticle
Languageen
FieldMedicine
TopicHormonal and reproductive studies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsLibidoTestosterone (patch)MedicineErectile dysfunctionOsteoporosisMoodLethargyHormone replacement therapy (female-to-male)Sexual dysfunctionInternal medicinePediatricsPsychiatry
DOInot available

Abstract

fetched live from OpenAlex

OBJECTIVE: To review the rationale for treating symptomatic aging men whose testosterone levels are mildly reduced or low-normal with testosterone replacement therapy. QUALITY OF EVIDENCE: Large-scale multicentre prospective studies on the value of treating andropausal men with hormone therapy do not exist because the whole area of hormone therapy is barely 10 years old. Evidence presented is based on physiologic studies, particularly studies in which treatment has been assessed. These were largely uncontrolled open studies. Studies to date report positive responses to testosterone treatment with very few serious side effects. MAIN MESSAGE: Physicians should consider hypoandrogenism if male patients complain of loss of libido, erectile dysfunction, weakness, fatigue, lethargy, loss of motivation, or mood swings. Less obvious associations with reduced levels of testosterone are anemia and osteoporosis. The main cause of reduced testosterone production is primary gonadal insufficiency, but secondary causes, such as hypothalamic-pituitary disease, should be considered. Evidence shows that most men treated with testosterone will feel better about themselves and their lives. CONCLUSION: Andropause is a term of convenience describing a complex of symptoms in aging men who have low testosterone levels. Physicians should be aware of its existence, should consider ordering tests for men who have symptoms, and should treat carefully selected patients whose serum testosterone levels are low.

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)0.000
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 score0.858
Threshold uncertainty score0.245

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.051
GPT teacher head0.278
Teacher spread0.227 · 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

Citations24
Published2001
Admission routes1
Has abstractyes

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