Neurologic Care for Transgender and Gender-Diverse People
Bibliographic record
Abstract
Purpose of Review: To summarize the literature on neurologic care for transgender and gender-diverse (TGD) people and provide implications for clinical practice. Recent Findings: There are limited data on the frequency and management of neurologic conditions among TGD people. TGD people have a higher prevalence of various neurologic conditions compared with cisgender or general population cohorts, including migraine, subjective cognitive decline, sleep disturbances, functional disorders, and cerebrovascular disease. Gender-affirming hormone therapy interacts with commonly prescribed neurologic medications and increases stroke risk among transfeminine people. Sex hormones and sex chromosomes may play a role in neurodegeneration and disability progression in neuroimmunologic diseases. Clitoral reduction surgeries on intersex children can cause neurologic disability and sexual dysfunction in adulthood. Socioeconomic disparities among TGD people contribute to health care barriers. Summary: Neurologists should consider the unique experiences and health care needs of TGD people in their clinical practice and research protocols.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".