Cross-sex hormone administration changes pain in transsexual women and men
Bibliographic record
Abstract
Chronic pain is gender-related, since there is a clear predominance of one sex with respect to the other in most pain syndromes. Gonadal hormones are known to affect the occurrence and incidence of pain. Transsexuals receive cross-sex hormones to develop and maintain somatic characteristics of the opposite sex: male to female transsexuals (MtF) are administered estrogens and anti-androgens, while female to male transsexuals (FtM) are administered androgens. Hence, these subjects represent a model to study the relationship between sex hormones and pain. Questionnaires dealing with sociodemographic data and pain (occurrence, frequency, duration, intensity, location and associated symptoms) were administered to both MtF and FtM transsexuals under hormone treatment for sex reassignment for at least 1 year. Forty-seven MtF and 26 FtM completed the questionnaires. Fourteen of the 47 MtF (29.8%) reported painful conditions, which in 11 subjects were not present before the beginning of hormone treatment. Pain consisted mainly of headaches and breast and musculoskeletal pain. Five subjects suffered from more than one pain condition. Sixteen of the 26 FtM (61.5%) reported pain. In 11 subjects, the pain was present before the beginning of hormone intake, and in 6 of them it improved after testosterone administration. These data suggest that marked changes in sex hormones affect the occurrence of pain in a high percentage of humans but not in all of them. Whether these effects are due to peripheral or central actions of sex steroids is unknown.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".