Introduction: This standardized-patient-based module prepares medical students to take inclusive, comprehensive sexual histories from patients of all sexual orientations and gender identities. Health disparities faced by lesbian, gay, bisexual, transgender, and queer (LGBTQ) people are at least partially the result of inadequate access to health care and insufficient provider training. This module incorporates implicit bias activities to emphasize the important role providers can play in mitigating these disparities through compassionate, competent care. Furthermore, two of the three included cases highlight the negative impact sexual dysfunction can have on emotional well-being. Methods: Over 3 hours, students participate in a 30-minute large-group lecture and three 40-minute small-group standardized patient encounters with debrief. Prework consists of a short video on sexual history taking, assigned readings, and an implicit bias activity. These materials are included in this resource, along with lecture slides, facilitator guide, and standardized patient cases. Though the cases are adaptable to all levels of medical education, this module is designed for second-year and early third-year medical students. Results: Qualitative student evaluations were positive, and postparticipation surveys revealed statistically significant improvement in comfort with their ability to take a sexual history in general, and take one from patients with a differing sexual orientation. Deployed in the second year of our Doctoring curriculum, this module continues to receive positive evaluations. Discussion: Introducing these skills begins to address the curricular deficiencies seen across medical education and lays the foundation for a more competent health care workforce to address the needs of LGBTQ patients.

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Exposure to ethanol during fetal development produces long-lasting neurobehavioral deficits caused by functional alterations in neuronal circuits across multiple brain regions. Therapeutic interventions currently used to treat these deficits are only partially efficacious, which is a consequence of limited understanding of the mechanism of action of ethanol. Here, we describe a novel effect of ethanol in the developing brain. Specifically, we show that exposure of rats to ethanol in vapor chambers during the equivalent to the third trimester of human pregnancy causes brain micro-hemorrhages. This effect was observed both at low and high doses of ethanol vapor exposure, and was not specific to this exposure paradigm as it was also observed when ethanol was administered via intra-esophageal gavage. The vast majority of the micro-hemorrhages were located in the cerebral cortex but were also observed in the hypothalamus, midbrain, olfactory tubercle, and striatum. The auditory, cingulate, insular, motor, orbital, retrosplenial, somatosensory, and visual cortices were primarily affected. Immunohistochemical experiments showed that the micro-hemorrhages caused neuronal loss, as well as reactive astrogliosis and microglial activation. Analysis with the Catwalk test revealed subtle deficits in motor function during adolescence/young adulthood. In conclusion, our study provides additional evidence linking developmental ethanol exposure with alterations in the fetal cerebral vasculature. Given that this effect was observed at moderate levels of ethanol exposure, our findings lend additional support to the recommendation that women abstain from consuming alcoholic beverages during pregnancy.

Prenatal exposure to alcohol causes a wide range of deficits known as fetal alcohol spectrum disorders (FASDs). Many factors determine vulnerability to developmental alcohol exposure including timing and pattern of exposure, nutrition and genetics. Here, we characterized how a prevalent single nucleotide polymorphism in the human brain-derived neurotrophic factor (BDNF) gene (val66met) modulates FASDs severity. This polymorphism disrupts BDNF's intracellular trafficking and activity-dependent secretion, and has been linked to increased incidence of neuropsychiatric disorders such as depression and anxiety. We hypothesized that developmental ethanol (EtOH) exposure more severely affects mice carrying this polymorphism. We used transgenic mice homozygous for either valine (BDNF ) or methionine (BDNF ) in residue 68, equivalent to residue 66 in humans. To model EtOH exposure during the second and third trimesters of human pregnancy, we exposed mice to EtOH in vapor chambers during gestational days 12 to 19 and postnatal days 2 to 9. We found that EtOH exposure reduces cell layer volume in the dentate gyrus and the CA1 hippocampal regions of BDNF but not BDNF mice during the juvenile period (postnatal day 15). During adulthood, EtOH exposure reduced anxiety-like behavior and disrupted trace fear conditioning in BDNF mice, with most effects observed in males. EtOH exposure reduced adult neurogenesis only in the ventral hippocampus of BDNF male mice. These studies show that the BDNF val66met polymorphism modulates, in a complex manner, the effects of developmental EtOH exposure, and identify a novel genetic risk factor that may regulate FASDs severity in humans.

Background Adverse events in COVID-19 are difficult to predict. Risk stratification is encumbered by the need to protect healthcare workers. We hypothesize that AI can help identify subtle signs of myocardial involvement in the 12-lead electrocardiogram (ECG), which could help predict complications. Objective Use intake ECGs from COVID-19 patients to train AI models to predict risk of mortality or major adverse cardiovascular events (MACE). Methods We studied intake ECGs from 1448 COVID-19 patients (60.5% male, 63.4±16.9 years). Records were labeled by mortality (death vs. discharge) or MACE (no events vs. arrhythmic, heart failure [HF], or thromboembolic [TE] events), then used to train AI models; these were compared to conventional regression models developed using demographic and comorbidity data. Results 245 (17.7%) patients died (67.3% male, 74.5±14.4 years); 352 (24.4%) experienced at least one MACE (119 arrhythmic; 107 HF; 130 TE). AI models predicted mortality and MACE with area under the curve (AUC) values of 0.60±0.05 and 0.55±0.07, respectively; these were comparable to AUC values for conventional models (0.73±0.07 and 0.65±0.10). There were no prominent temporal trends in mortality rate or MACE incidence in our cohort; holdout testing with data from after a cutoff date (June 9, 2020) did not degrade model performance. Conclusion Using intake ECGs alone, our AI models had limited ability to predict hospitalized COVID-19 patients’ risk of mortality or MACE. Our models’ accuracy was comparable to that of conventional models built using more in-depth information, but translation to clinical use would require higher sensitivity and positive predictive value. In the future, we hope that mixed-input AI models utilizing both ECG and clinical data may be developed to enhance predictive accuracy.

Conflict of Interest Disclosures: Dr Kvedar reports being on the advisory boards of Claritas Mindsciences, Medtronic Care Management Services, and Lumin Dx and being a member of the board of directors of b.Well Connected Health. No other disclosures were reported.

Background The coronavirus disease 2019 (COVID-19) pandemic has challenged researchers performing clinical trials to develop innovative approaches to mitigate infectious risk while maintaining rigorous safety monitoring. Methods In this report we describe the implementation of a novel exclusively remote randomized clinical trial (ClinicalTrials.gov NCT04354428) of hydroxychloroquine and azithromycin for the treatment of the SARS-CoV-2–mediated COVID-19 disease which included cardiovascular safety monitoring. All study activities were conducted remotely. Self-collected vital signs (temperature, respiratory rate, heart rate, and oxygen saturation) and electrocardiographic (ECG) measurements were transmitted digitally to investigators while mid-nasal swabs for SARS-CoV-2 testing were shipped. ECG collection relied on a consumer device (KardiaMobile 6L, AliveCor Inc.) that recorded and transmitted six-lead ECGs via participants’ internet-enabled devices to a central core laboratory, which measured and reported QTc intervals that were then used to monitor safety. Results Two hundred and thirty-one participants uploaded 3245 ECGs. Mean daily adherence to the ECG protocol was 85.2% and was similar to the survey and mid-nasal swab elements of the study. Adherence rates did not differ by age or sex assigned at birth and were high across all reported race and ethnicities. QTc prolongation meeting criteria for an adverse event occurred in 28 (12.1%) participants, with 2 occurring in the placebo group, 19 in the hydroxychloroquine group, and 7 in the hydroxychloroquine + azithromycin group. Conclusions Our report demonstrates that digital health technologies can be leveraged to conduct rigorous, safe, and entirely remote clinical trials.