Faculty Bibliography

GIM/FP/GP: [Formula: see text] Endocrinology: [Formula: see text].

First-line treatment of endogenous Cushing's syndrome (CS) is surgical removal of the tumor responsible for cortisol excess. However, medical therapy has an established role in treatment when patients are not surgical candidates or decline surgery, residual or recurrent disease is present and not amenable to repeat resection, and control of hypercortisolism is needed either preoperatively or while awaiting the effects of radiotherapy. The approach to medical therapy should be tailored based on the etiology, degree of hypercortisolism, and patient characteristics. Currently available medical therapy for all etiologies of CS either blocks adrenal production of cortisol or blocks its action at the level of the glucocorticoid receptor. Currently available medical therapy for Cushing's disease (CD) targets the adrenocorticotropic hormone-secreting pituitary tumor through activation of somatostatin and dopamine receptors, alkylating DNA damage, or immune system activation. More focused therapy with greater efficacy and fewer adverse effects is needed, particularly in the case of CD, with potential targets and drugs identified and in development.

BACKGROUND:Abdominal computed tomography (CT) is commonly performed in adults. Abdominal aortic calcification (AAC) can be visualized and quantified using artificial intelligence (AI) on CTs performed for other clinical purposes (opportunistic CT). We sought to investigate the value of AI-enabled AAC quantification as a predictor of coronary artery disease and its association with cardiovascular events. METHODS:A fully automated AI algorithm to quantify AAC from the diaphragm to aortic bifurcation using the Agatston score was retrospectively applied to a cohort of patient that underwent both non-contrast abdominal CT for routine clinical care and cardiac CT for coronary artery calcification (CAC) assessment. Subjects were followed for a median of 36 months for major adverse cardiovascular events (MACE, composite of death, myocardial infarction [MI], ischemic stroke, coronary revascularization) and major coronary events (MCE, MI or coronary revascularization). RESULTS:Our cohort included 3599 patients (median age 60 years, 62% male, 74% white) with an evaluable abdominal and cardiac CT. There was a positive correlation between presence and severity of AAC and CAC (r=0.56, P<0.001). AAC showed excellent discriminatory power for detecting or ruling out any CAC (AUC for PREVENT risk score 0.701 [0.683 to 0.718]; AUC for PREVENT plus AAC 0.782 [0.767 to 0.797]; P<0.001). There were 324 MACE, of which 246 were MCE. Following adjustment for the 10-year cardiovascular disease PREVENT score, the presence of AAC was associated with a significant risk of MACE (adjHR 2.26, 95% CI 1.67-3.07, P<0.001) and MCE (adjHR 2.58, 95% CI 1.80-3.71, P<0.001). A doubling of the AAC score resulted in an 11% increase in the risk of MACE and a 13% increase in the risk of MCE. CONCLUSIONS:Using opportunistic abdominal CTs, assessment of AAC using a fully automated AI algorithm, predicted CAC and was independently associated with cardiovascular events. These data support the use of opportunistic imaging for cardiovascular risk assessment. Future studies should investigate whether opportunistic imaging can help guide appropriate cardiovascular prevention strategies.

Long COVID, characterized by persistent or recurring symptoms post-COVID-19 infection, poses challenges for pediatric care and research due to the lack of a standardized clinical definition. Adult-focused phenotypes do not translate well to children, given developmental and physiological differences, and pediatric-specific phenotypes have not been compared with chart review.This study introduces and evaluates a pediatric-specific rule-based computable phenotype (CP) to identify long COVID using electronic health record data. We compare its performance to manual chart review.We applied the CP, composed of diagnostic codes empirically associated with long COVID, to 339,467 pediatric patients with SARS-CoV-2 infection in the RECOVER PCORnet EHR database. The CP identified 31,781 patients with long COVID. Clinicians conducted chart reviews on a subset of patients across 16 hospital systems to assess performance. We qualitatively reviewed discordant cases to understand differences between CP and clinician identification.Among the 651 reviewed patients (339 females, M _age = 10.10 years), the CP showed moderate agreement with clinician identification (accuracy = 0.62, positive predictive value [PPV] = 0.49, negative predictive value [NPV] = 0.75, sensitivity = 0.52, specificity = 0.84). Performance was largely consistent across age and dominant variant but varied by symptom cluster count. Most discrepancies between the CP and chart review occurred when the CP identified a case, but the clinician did not, often because clinicians attributed symptoms to preexisting conditions (73%). When clinicians identified cases missed by the CP, they often used broader symptom or timing criteria (69%). Model performance improved when the CP accounted for preexisting conditions (accuracy = 0.71, PPV = 0.65, NPV = 0.74, sensitivity = 0.59, specificity = 0.79).This study presents a CP for pediatric long COVID. While agreement with manual review was moderate, most discrepancies were explained by differences in interpreting symptoms when patients had preexisting conditions. Accounting for these conditions improved accuracy and highlights the need for a consensus definition. These findings support the development of reliable, scalable tools for pediatric long COVID research.

OBJECTIVE:To assess HBV monitoring, HBV reactivation and hepatitis flares during tenofovir interruptions among people with HIV and HBV. DESIGN/METHODS:Cohort study of electronic health records. METHODS:All tenofovir (tenofovir disoproxil fumarate, tenofovir alafenamide) interruptions among people with HIV and positive HBV surface antigen (HBsAg) or positive HBV core antibody (HBcAb) were categorized by reactivation risk (high: HBsAg+; moderate: HBsAg-/HBcAb+/surface antibody [HBsAb] negative; low: HBsAg-/HBcAb+/HBsAb+). Incidence rates of HBV reactivation and hepatitis flare were assessed with Poisson regression. RESULTS:Among 5343 individuals with HIV and HBV, there were 6252 tenofovir interruptions (11% high-, 19% moderate-, 69% low-risk). During the interruptions, HBV DNA/HBsAg testing was infrequent (high: 52%/25%; moderate: 8%/31%, low: 5%/28%), although ALT testing was performed during nearly all interruptions. The HBV reactivation rate was 9.59 per 100 person-years (95% confidence interval [CI]: 7.91, 11.64) during high-risk, 0.58 (0.36, 0.91) during moderate-risk, and 0.04 (0.02, 0.11) during low-risk interruptions. The HBV reactivation with hepatitis flare incidence rate was much lower, especially in the high-risk group (3.06 per 100 person-year; 95% CI: 2.19, 4.29). CONCLUSIONS:In this large US cohort of people with HIV and HBV, tenofovir interruptions were common and HBV monitoring was sub-optimal. HBV reactivation rates were highest among the high-risk group, but much lower among the moderate- and low-risk groups. However, some reactivations were likely missed due to low monitoring frequency. Primary and HIV care providers must incorporate HBV monitoring in their standard of care and proceed with caution if considering a tenofovir interruption for people with HIV and HBV.

Liver transplant (LT) recipients experience a wide range of comorbidities, leading to frequent healthcare encounters. Until now, national registries, which have limited exposures and outcomes, and laborious small cohort studies have been the main data sources for LT research. Cosmos database offers electronic health record (EHR)-based insights into LT recipients at the national level with granular data. We evaluated if Cosmos data is representative of the entire US LT recipient population. Using Cosmos (N=20,235) and the national Scientific Registry of Transplant Recipients (SRTR) (N=51,281), we identified adult, first-time LT recipients between 7/2016-12/2022. We compared demographics, clinical data, and mortality across datasets, calculating Kaplan-Meier survival estimates and multi-variable Cox regressions. Recipient characteristics were highly comparable (e.g., female: Cosmos=36.5% vs. SRTR=36.4%, Black: 6.8% vs. 7.2%; BMI: 28.5 kg/m2 [24.8-32.9] vs. 28.2 [24.6-32.4]). Lab values were similar across cohorts, including MELD (24 [17-30] vs. 23 [16-30]). Transplant indications, donor characteristics, and 5-year survival (Cosmos 83.1% [82.3-83.8) vs. SRTR 80.9% [80.4-81.3]) were similar. The associations of clinical factors with survival were similar across both groups. Cosmos database demonstrated acceptable generalizability to the general US LT recipient population, which may advance LT research through a better understanding about LT recipients' experiences and outcomes.

INTRODUCTION/BACKGROUND:Implicit bias can influence patient-clinician communication through clinician implicit bias (actual) or patients' perception of bias (perceived). Few curricula focus on skills to address implicit bias. We developed and evaluated a skills-based curriculum addressing implicit bias in clinical encounters. MATERIALS & METHODS/METHODS:A 60-minute session was delivered to 4 cohorts of learners (N = 458, ranging from first-year medical students to attendings) in academic medical settings. All had prior exposure to the topic of implicit bias. Instruction grounded in the Implicit Bias Recognition and Management framework described the impact of actual and perceived bias and patients' recommendations for restoring rapport once bias had impacted an encounter. Through audience response systems or role-plays with feedback, participants developed verbal procedures-personalized, verbatim statements to restore patient rapport when implicit bias has impacted an encounter. Learners submitted their verbal procedures online, which were then coded to identify helpful and unhelpful elements. Investigators coded verbal procedures and assigned point values for "helpful" and "unhelpful" elements resulting in scores from -1-6. RESULTS:Each approach yielded helpful elements. Overall, of submitted verbal procedures, 91.3 % were "helpful" and 8.6 % "unhelpful." Compared to audience response systems, verbal procedures developed through role-plays included significantly more "helpful" elements (2.21/1.29, p = 0.003 and 2.46/1.87 p = 0.009). CONCLUSIONS:Findings suggest learners can develop verbatim statements to restore rapport with patients in a single session if those learners have prior foundational knowledge about implicit bias and its relevance to healthcare disparities. PRACTICE IMPLICATIONS/CONCLUSIONS:Teaching verbal procedures could expand skill-building opportunities within implicit bias curricula.

BACKGROUND:Glucagon-like peptide-1 (GLP-1) medications, recently introduced in the United States for treating type 2 diabetes and obesity, have sparked interest and discussion on social media. Social media has emerged as a prominent platform for the distribution of health information; its vast user base and accessibility make it a popular resource for individuals seeking medical advice. This study characterized GLP-1 medication-related content on Instagram about 3 critical areas of public health: women's health, access from nontraditional settings, and barriers to access. OBJECTIVE:This study aimed to perform passive content analysis in which information patterns would be observed from Instagram posts. METHODS:We examined 40 GLP-1 medication-related Instagram posts to develop a list of the most frequently used hashtags. In total, 10 "top posts" were collected for 7 days (July 11-17, 2023) for 11 study hashtags (eg, #Ozempic). Duplicates, deleted posts or accounts, non-English content, and unrelated posts were removed. Each post was reviewed by at least 2 coders. Coding discrepancies were resolved through discussion. RESULTS:The final sample included 239 posts. More than half of the posts (130/239, 54%) were from GLP-1 medication users. Raters perceived most users to be female (90/97, 92.8%); inferred that most used medications for weight loss (69/130, 53.1%); determined the most frequently noted health condition was polycystic ovarian syndrome (25/130, 19.2%); and judged posts to have positive sentiments about well-being (64/130, 49.2%) and toward the medications (100/130, 76.9%). About a quarter of the posts (55/239, 23%) offered services for obtaining GLP-1 medications; GLP-1 medications were perceived to be accessible via nontraditional health care settings (eg, medical spas) versus traditional settings (39/239,16.3% vs 12/239, 5%). Most users (78/97, 80.4%) were perceived to be White; barriers to access (ie, shortages, insurance, and cost) were infrequently mentioned (6/239, 2.5%; 3/239, 1.3%; and 1/239, 0.4%, respectively). CONCLUSIONS:Our findings highlight the perceived benefits of GLP-1 medications for women's health, the need to increase health literacy about where to safely access medications, and how additional attention is needed for equitable access to GLP-1 medications. The onus is on social media companies to promote content that is safe and for the health care system and its payers to address health care inequities for historically marginalized communities.