RESUMO
OBJECTIVE: To investigate the frequency, attack characteristics, and treatment experiences of migraine and tension-type headache (TTH) among gender dysphoric female-to-male (FtM) participants as well as in relation to psychiatric comorbidities and real-life experience that relates to being transgender in Turkey. BACKGROUND: There are only a few publications to date on transgender individuals with headache. Further studies to understand the distinctive needs might provide better management. METHODS: A total of 88 gender dysphoric FtM individuals (mean (SD) age: 24.8 (5.7) years) were included on a voluntary basis in this cross-sectional survey. Each participant filled out the questionnaire form that elicited items on sociodemographic characteristics, Gender Identity Transition Inventory, Beck Depression Inventory (BDI), Beck Anxiety Inventory (BAI), and Headache Questionnaire. RESULTS: Overall, 32/88 (36.4%; 95% confidence interval [CI]: 27.0%-47.0%) participants were diagnosed with migraine, and 36/88 (40.9%; 95% CI: 31.5%-52.3%) participants were diagnosed with TTH. High rates of unemployment, smoking, and social drinking were observed in our sample compared with the general population in Turkey. The three-item ID migraine screener was positive in 20.5% (18/88 patients) of our population. Patients with migraine in comparison with patients with TTH had statistically significantly higher BDI [12.0 (1-50) vs. 7.0 (0-33); p = 0.013] and BAI [13 (1-48) vs. 5 (0-22); p = 0.016] scores, longer headaches in the past month [median 3 vs. 1 day; p < 0.001], higher Numerical Rating Scale scores for headache severity [7 (2-10) vs. 5 (1-9), p < 0.001], and higher likelihood of menstruation acting as a triggering factor [8/32 patients (25.0%) vs. 0/36 patients (0.0%); p = 0.001] as well as increased rates of previously given diagnosis by a physician [15/32 patients (46.9%) vs. 4/36 patients (11.1%); p < 0.001], a greater number of neuroimaging tests being performed [12/32 patients (37.5%) vs. 3/36 patients (9.1%); p = 0.012], and a higher rate of emergency room utilization [7/32 patients (21.9%) vs. 1/36 patients (2.8%); p = 0.039] for headache. CONCLUSIONS: In the FtM transgender population we investigated, migraine and TTH were quite common. The screening and early recognition of comorbid migraine, as well as the comorbid depression and anxiety, seem to be important in gender dysphoric FtM individuals. Further studies are needed to better understand the potential interaction of migraine with comorbid psychiatric disorders and the prevalence of headache types and gender-affirmative hormone treatment outcomes in the transgender population.
Assuntos
Transtornos de Ansiedade , Transtorno Depressivo , Disforia de Gênero , Transtornos de Enxaqueca , Procedimentos de Readequação Sexual , Minorias Sexuais e de Gênero , Cefaleia do Tipo Tensional , Adulto , Transtornos de Ansiedade/epidemiologia , Comorbidade , Estudos Transversais , Transtorno Depressivo/epidemiologia , Feminino , Disforia de Gênero/epidemiologia , Disforia de Gênero/psicologia , Humanos , Masculino , Transtornos de Enxaqueca/epidemiologia , Transtornos de Enxaqueca/fisiopatologia , Transtornos de Enxaqueca/terapia , Procedimentos de Readequação Sexual/psicologia , Procedimentos de Readequação Sexual/estatística & dados numéricos , Minorias Sexuais e de Gênero/psicologia , Minorias Sexuais e de Gênero/estatística & dados numéricos , Cefaleia do Tipo Tensional/epidemiologia , Cefaleia do Tipo Tensional/fisiopatologia , Cefaleia do Tipo Tensional/terapia , Turquia/epidemiologia , Adulto JovemRESUMO
Telemedicine is now being used more frequently to evaluate patients with myasthenia gravis (MG). Assessing this condition involves clinical outcome measures, such as the standardized MG-ADL scale or the more complex MG-CE score obtained during clinical exams. However, human subjectivity limits the reliability of these examinations. We propose a set of AI-powered digital tools to improve scoring efficiency and quality using computer vision, deep learning, and natural language processing. This paper focuses on automating a standard telemedicine video by segmenting it into clips corresponding to the MG-CE assessment. This AI-powered solution offers a quantitative assessment of neurological deficits, improving upon subjective evaluations prone to examiner variability. It has the potential to enhance efficiency, patient participation in MG clinical trials, and broader applicability to various neurological diseases.