Faculty Bibliography

PURPOSE/UNASSIGNED:Earlier literature has reported on the utility of diagnostic codes and demographic information for identifying transgender patients. We aim to assess which method identifies the most transgender patients utilizing readily available tools from within the electronic health record (EHR). METHODS/UNASSIGNED:(ICD-10) diagnostic codes and demographic data specific to transgender patients from January 2011 to April 2019. RESULTS/UNASSIGNED:Demographic data and ICD-10 codes yielded 1494 individual EHRs with transgender-specific data domains. ICD-10 diagnostic codes alone identified 942 (63.05%) unique EHRs. Demographics alone identified 218 (14.59%) unique EHRs. A total of 334 (22.36%) unique EHRs had both ICD-10 and demographic identifiers. Of those identified by transgender-specific demographic data (552), 294 (53.26%) were trans masculine, 215 (38.95%) were trans feminine, and 43 (7.79%) were nonbinary. Of the 552 demographic-identified transgender patients, 141 (25.86%) were identified by a two-part gender identity demographic question. CONCLUSIONS/UNASSIGNED:ICD-10 diagnostic codes, not demographic data, identified the most transgender patient records, but neither diagnostic codes alone nor demographic data captured the full population. Only 26.36% of the charts identified as transgender patients had both ICD-10 codes and demographic data. We recommend that when identifying transgender populations through EHR domains, a combination of diagnostic codes and demographic data be used. Furthermore, research is needed to optimize disclosure and collection of demographic information for gender minority populations.

Despite the growing number of genome-wide association studies (GWASs), it remains unclear to what extent gene-by-gene and gene-by-environment interactions influence complex traits in humans. The magnitude of genetic interactions in complex traits has been difficult to quantify because GWASs are generally underpowered to detect individual interactions of small effect. Here, we develop a method to test for genetic interactions that aggregates information across all trait-associated loci. Specifically, we test whether SNPs in regions of European ancestry shared between European American and admixed African American individuals have the same causal effect sizes. We hypothesize that in African Americans, the presence of genetic interactions will drive the causal effect sizes of SNPs in regions of European ancestry to be more similar to those of SNPs in regions of African ancestry. We apply our method to two traits: gene expression in 296 African Americans and 482 European Americans in the Multi-Ethnic Study of Atherosclerosis (MESA) and low-density lipoprotein cholesterol (LDL-C) in 74K African Americans and 296K European Americans in the Million Veteran Program (MVP). We find significant evidence for genetic interactions in our analysis of gene expression; for LDL-C, we observe a similar point estimate, although this is not significant, most likely due to lower statistical power. These results suggest that gene-by-gene or gene-by-environment interactions modify the effect sizes of causal variants in human complex traits.

Intimate Partner Violence (IPV) has been linked to poor health. Economic position may be an important risk factor for IPV. We examined the association between economic position and IPV at country and individual levels. We analyzed Demographic and Health Surveys data of 187,716 ever-partnered women between ages 10 and 59 from 20 low- and middle-income countries. We calculated direct age-standardized 12-month prevalence of physical IPV and performed ecological analysis using Gini coefficients and Concentration indexes to assess correlation with 12-month prevalence of physical IPV. We conducted multivariable logistic regression for each country to assess the association between wealth status and physical IPV and a meta-analysis of the regression model to present results across countries. Compared to the Poorest quintile, odds of IPV among wealthier quintiles varied by country. In the Middle quintile, India had significantly reduced IPV (OR 0.75, 95%CI: 0.68-0.83). In the Richer and Richest quintiles, 4 and 6 countries had significant reductions in IPV, respectively. Only Mozambique was found to have significant increased IPV in the wealthiest quintile (OR 2.51, 95%CI: 1.45-4.38). Gini coefficient and physical IPV had a correlation coefficient of 0.502 (p value 0.033), while Concentration index had -0.276 (p value .253). Standardized prevalence for physical IPV ranged from 1.58% to 18.91%. Findings suggest that the relationship between wealth and IPV vary considerably in the included low- and middle-income countries, and that risk of IPV may not necessarily be higher among women in lower wealth brackets. Mozambique was the only country with increased odds of IPV among the Richest group as compared to the Poorest group. This study provides evidence IPV may transcend economic boundaries, and that studies looking at the link between inequality and IPV are paramount for designing adequate preventative policies.

INTRODUCTION:Racial discrimination has been consistently linked to various health outcomes and health disparities, including studies associating racial discrimination with patterns of racial disparities in adverse pregnancy outcomes. To expand our knowledge, this systematic review and meta-analysis assesses all available evidence on the association between self-reported racial discrimination and adverse pregnancy outcomes. METHODS:statistic. RESULTS:Of 13 597 retrieved records, 24 articles were included. Studies included cohort, case-control and cross-sectional designs and were predominantly conducted in the USA (n=20). Across all outcomes, significant positive associations (between experiencing racial discrimination and an adverse pregnancy event) and non-significant associations (trending towards positive) were reported, with no studies reporting significant negative associations. The overall pooled odds ratio (OR) for preterm birth was 1.40 (95% CI 1.17 to 1.68; 13 studies) and for small for gestational age it was 1.23 (95% CI 0.76 to 1.99; 3 studies). When excluding low-quality studies, the preterm birth OR attenuated to 1.31 (95% CI 1.08 to 1.59; 10 studies). Similar results were obtained across sensitivity and subgroup analyses, indicating a significant positive association. CONCLUSION:These results suggest that racial discrimination has adverse impacts on pregnancy outcomes. This is supported by the broader literature on racial discrimination as a risk factor for adverse health outcomes. To further explore this association and underlying mechanisms, including mediating and moderating factors, higher quality evidence from large ethnographically diverse cohorts is needed.

PROBLEM/UNASSIGNED:Some medical schools have incorporated constructed response short answer questions (CR-SAQs) into their assessment toolkits. Although CR-SAQs carry benefits for medical students and educators, the faculty perception that the amount of time required to create and score CR-SAQs is not feasible and concerns about reliable scoring may impede the use of this assessment type in medical education. INTERVENTION/UNASSIGNED:) was used to evaluate inter-rater reliability. CONTEXT/UNASSIGNED:This research study was implemented at three US medical schools that are nationally dispersed and have been administering CR-SAQ summative exams as part of their programs of assessment for at least five years. The study exam question was included in an end-of-course summative exam during the first year of medical school. IMPACT/UNASSIGNED:=.59-.66, analytic rubric). LESSONS LEARNED/UNASSIGNED:Our findings show that from the faculty perspective it is feasible to include CR-SAQs in summative exams and we provide practical information for medical educators creating and scoring CR-SAQs. We also learned that CR-SAQs can be reliably scored by faculty without content expertise or senior medical students using an analytic rubric, or by senior medical students using a holistic rubric, which provides options to alleviate the faculty burden associated with grading CR-SAQs.

INTRODUCTION/UNASSIGNED:The elimination of the USMLE Step 1 three-digit score has created a deficit in standardized performance metrics for undergraduate medical educators and residency program directors. It is likely that there will be greater emphasis on USMLE Step 2 CK, an exam found to be associated with later clinical performance in residents and physicians. Because many previous models relied on Step 1 scores to predict student performance on Step 2 CK, we developed a model using other metrics. MATERIALS AND METHODS/UNASSIGNED:Assessment data for 228 students in three cohorts (classes of 2018, 2019, and 2020) were collected, including the Medical College Admission Test (MCAT), NBME Customized Assessment Service (CAS) exams and NBME Subject exams. A linear regression model was conducted to predict Step 2 CK scores at five time-points: at the end of years one and two and at three trimester intervals in year three. An additional cohort (class of 2021) was used to validate the model. RESULTS/UNASSIGNED:= 0.62). Including Step 1 scores did not significantly improve the final model. Using metrics from the class of 2021, the model predicted Step 2 CK performance within a mean square error (MSE) of 8.3 points (SD = 6.8) at the end of year 1 increasing predictability incrementally to within a mean of 5.4 points (SD = 4.1) by the end of year 3. CONCLUSION/UNASSIGNED:This model is highly generalizable and enables medical educators to predict student performance on Step 2 CK in the absence of Step 1 quantitative data as early as the end of the first year of medical education with increasingly stronger predictions as students progressed through the clerkship year.