An Individualized Approach to Managing Testosterone Therapy in the Primary Care Setting
Bibliographic record
Abstract
The incidence of testosterone deficiency and the use of testosterone therapy have increased in recent years, and currently the majority of testosterone prescriptions in the United States and Canada are written by primary care physicians. Meanwhile, the range of available testosterone therapy formulations has widened to include buccal tablets, intramuscular injections, transdermal gels, intranasal gel, subcutaneous injections, oral capsules, and subdermal pellets, each with unique pharmacokinetic and clinical characteristics. Despite the growing use of testosterone therapy and its overall efficacy and safety as demonstrated in clinical trials, concerns exist about the potential impact of testosterone therapy on spermatogenesis and fertility, development of prostate cancer, and risk of polycythemia and cardiovascular events. In addition, ongoing research aims to better characterize the effects of testosterone therapy in specific populations, such as patients aged 65 years and older, patients with obesity and type 2 diabetes, and transgender patients. The range of treatment options and the diversity of patients' goals, preferences, comorbidities, and risk factors necessitate an individualized approach to testosterone therapy that considers each patient's clinical needs alongside the distinct features of different testosterone formulations.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".