Faculty Bibliography

Favourable body composition has been associated with higher dietary protein intake. However, little is known regarding this relationship in a population of Chinese Americans (CHA), who have lower BMI compared with other populations. The aim of the present study was to assess the relationship between dietary protein intake, fat mass (FM) and fat-free mass (FFM) in CHA. Data were from the Chinese American Cardiovascular Health Assessment (CHA CHA) 2010-2011 (n 1707); dietary intake was assessed using an adapted and validated FFQ. Body composition was assessed using bioelectrical impedance analysis. The associations between protein intake (% energy intake) and BMI, percentage FM (FM%), percentage FFM (FFM%), FM index (FMI) and FFM index (FFMI) were examined using multiple linear regression adjusted for age, sex, physical activity, acculturation, total energy intake, sedentary time, smoking status, education, employment and income. There was a significant positive association between dietary protein and BMI (B = 0·056, 95 % CI 0·017, 0·104; P = 0·005), FM (B = 0·106, 95 % CI 0·029, 0·184; P = 0·007), FM% (B = 0·112, 95 % CI 0·031, 0·194; P = 0·007) and FMI (B = 0·045, 95 % CI 0·016, 0·073; P = 0·002). There was a significant negative association between dietary protein and FFM% (B = -0·116, 95 % CI -0·196, -0·036; P = 0·004). In conclusion, higher dietary protein intake was associated with higher adiposity; however, absolute FFM and FFMI were not associated with dietary protein intake. Future work examining the relationship between protein source (i.e. animal) and body composition is warranted in this population of CHA.

BACKGROUND:Because of the strong link between childhood obesity and adulthood obesity comorbidities, and the difficulty in decreasing body mass index (BMI) later in life, effective strategies are needed to address this condition in early childhood. The ability to predict obesity before age five could be a useful tool, allowing prevention strategies to focus on high risk children. The few existing prediction models for obesity in childhood have primarily employed data from longitudinal cohort studies, relying on difficult to collect data that are not readily available to all practitioners. Instead, we utilized real-world unaugmented electronic health record (EHR) data from the first two years of life to predict obesity status at age five, an approach not yet taken in pediatric obesity research. METHODS AND FINDINGS/RESULTS:We trained a variety of machine learning algorithms to perform both binary classification and regression. Following previous studies demonstrating different obesity determinants for boys and girls, we similarly developed separate models for both groups. In each of the separate models for boys and girls we found that weight for length z-score, BMI between 19 and 24 months, and the last BMI measure recorded before age two were the most important features for prediction. The best performing models were able to predict obesity with an Area Under the Receiver Operator Characteristic Curve (AUC) of 81.7% for girls and 76.1% for boys. CONCLUSIONS:We were able to predict obesity at age five using EHR data with an AUC comparable to cohort-based studies, reducing the need for investment in additional data collection. Our results suggest that machine learning approaches for predicting future childhood obesity using EHR data could improve the ability of clinicians and researchers to drive future policy, intervention design, and the decision-making process in a clinical setting.

The main focus of this study is bridging the "evidence gap" between frontline decision-making in health care and the actual evidence, with the hope of reducing unnecessary diagnostic testing and treatments. From our work in pulmonary embolism (PE) and over ordering of computed tomography pulmonary angiography, we integrated the highly validated Wells' criteria into the electronic health record at two of our major academic tertiary hospitals. The Wells' clinical decision support tool triggered for patients being evaluated for PE and therefore determined a patients' pretest probability for having a PE. There were 12,759 patient visits representing 11,836 patients, 51% had no D-dimer, 41% had a negative D-dimer, and 9% had a positive D-dimer. Our study gave us an opportunity to determine which patients were very low probabilities for PE, with no need for further testing.

Antithrombotic therapy for stroke prevention in patients with atrial fibrillation (AF) has dramatically shifted from warfarin, a vitamin K antagonist, to the direct oral anticoagulants (DOACs) such as dabigatran, apixaban, and rivaroxaban. In patients with contraindications to oral anticoagulation, left atrial appendage occlusion (LAAO) devices, such as the Watchmanâ„¢ device, may be considered; however, temporary postimplantation antithrombotic therapy is still a recommended practice. We present a case of complex antithrombotic management, post LAAO device implantation, designed to avoid drug interactions with concomitant rifampin use and remained necessary secondary to subsequent device leak. This case highlights the challenges of antithrombotic therapy post LAAO device placement in a complex, but representative, patient.

Purpose: To explore the experiences of transgender and gender nonbinary (TGNB) medical students and physicians in the United States. Methods: The authors conducted a 79-item online survey using Likert-type and open-ended questions to assess the experiences of TGNB-identified U.S. medical students and physicians. Variables included demographic data, disclosure of TGNB status, exposure to transphobia, and descriptions of educational and professional experiences. Recruitment was conducted using snowball sampling through Lesbian, Gay, Bisexual, Transgender, Queer professional groups, list-servs, and social media. The survey was open from June 2017 through November 2017. Results: Respondents included 21 students and 15 physicians (10 transgender women, 10 transgender men, and 16 nonbinary participants). Half (50%; 18) of the participants and 60% (9) of physicians had not disclosed their TGNB identity to their medical school or residency program, respectively. Respondents faced barriers on the basis of gender identity/expression when applying to medical school (22%; 11) and residency (43%; 6). More than three-quarters (78%; 28) of participants censored speech and/or mannerisms half of the time or more at work/school to avoid unintentional disclosure of their TGNB status. More than two-thirds (69%; 25) heard derogatory comments about TGNB individuals at medical school, in residency, or in practice, while 33% (12) witnessed discriminatory care of a TGNB patient. Conclusion: TGNB medical students and physicians faced significant barriers during medical training, including having to hide their identities and witnessing anti-TGNB stigma and discrimination. This study, the first to exclusively assess experiences of TGNB medical students and physicians, reveals that significant disparities still exist on the basis of gender identity.