Faculty Bibliography

The landscape of HIV medicine dramatically changed with the advent of contemporary antiretroviral therapies (ART) which has allowed persons with HIV (PWH) to achieve good virologic control, essentially eliminating HIV-related complications and increasing life expectancy. As PWH are living longer, non-communicable diseases, such as cardiovascular disease (CVD), have become a leading cause of morbidity and mortality in PWH with rates that are 50-100% higher than in well-matched persons without HIV. In this review, we focus on disease of the coronary microvasculature and myocardium in HIV. We highlight a key hormonal system important to cardiovascular endocrinology, the renin-angiotensin-aldosterone system (RAAS), as a potential mediator of inflammatory driven-vascular and myocardial injury and consider RAAS blockade as a physiologically-targeted strategy to reduce CVD in HIV.

BACKGROUND:Cancer genetic testing to assess an individual's cancer risk and to enable genomics-informed cancer treatment has grown exponentially in the past decade. Because of this continued growth and a shortage of health care workers, there is a need for automated strategies that provide high-quality genetics services to patients to reduce the clinical demand for genetics providers. Conversational agents have shown promise in managing mental health, pain, and other chronic conditions and are increasingly being used in cancer genetic services. However, research on how patients interact with these agents to satisfy their information needs is limited. OBJECTIVE:Our primary aim is to assess user interactions with a conversational agent for pretest genetics education. METHODS:We conducted a feasibility study of user interactions with a conversational agent who delivers pretest genetics education to primary care patients without cancer who are eligible for cancer genetic evaluation. The conversational agent provided scripted content similar to that delivered in a pretest genetic counseling visit for cancer genetic testing. Outside of a core set of information delivered to all patients, users were able to navigate within the chat to request additional content in their areas of interest. An artificial intelligence-based preprogrammed library was also established to allow users to ask open-ended questions to the conversational agent. Transcripts of the interactions were recorded. Here, we describe the information selected, time spent to complete the chat, and use of the open-ended question feature. Descriptive statistics were used for quantitative measures, and thematic analyses were used for qualitative responses. RESULTS:We invited 103 patients to participate, of which 88.3% (91/103) were offered access to the conversational agent, 39% (36/91) started the chat, and 32% (30/91) completed the chat. Most users who completed the chat indicated that they wanted to continue with genetic testing (21/30, 70%), few were unsure (9/30, 30%), and no patient declined to move forward with testing. Those who decided to test spent an average of 10 (SD 2.57) minutes on the chat, selected an average of 1.87 (SD 1.2) additional pieces of information, and generally did not ask open-ended questions. Those who were unsure spent 4 more minutes on average (mean 14.1, SD 7.41; P=.03) on the chat, selected an average of 3.67 (SD 2.9) additional pieces of information, and asked at least one open-ended question. CONCLUSIONS:The pretest chat provided enough information for most patients to decide on cancer genetic testing, as indicated by the small number of open-ended questions. A subset of participants were still unsure about receiving genetic testing and may require additional education or interpersonal support before making a testing decision. Conversational agents have the potential to become a scalable alternative for pretest genetics education, reducing the clinical demand on genetics providers.

Numerous studies have found that organizational features connected with the work environment of nurses have a significant influence on patients' safety. The aim of this research was to capture nurses' opinions about patients' safety and discern relationships with work environment characteristics. This cross-sectional study surveyed 1825 nurses. The research used questionnaire consisting of four parts: (1) covered The Practice Environment Scale of the Nursing Work Index (PES-NWI); (2) assessed the quality of nursing care and care safety; (3) contained information on the most recent duty served by the nurses and (4) captured social and demographic data of participants. The research identified strong association between patient safety assessment and work environment of nurses in the aspect of employment adequacy, cooperation between nurses and doctors, support for nurses from the managing staff, the possibility to participate in the management as well as professional promotion of nurses employed in the hospital (p < 0.001). Nurses rated patient safety higher when responsible for a smaller number of patients. Work environment factors such as proper staffing, good cooperation with doctors, support from the management, as well as professional independence are significantly related to nurses' assessment of patients' safety.

BACKGROUND AND AIMS/OBJECTIVE:Rates of obesity are rising in patients with inflammatory bowel disease [IBD]. We conducted a US population-based study to determine the effects of obesity on outcomes in hospitalised patients with IBD. METHODS:We searched the Nationwide Readmissions Database 2016-2017 to identify all adult patients hospitalised for IBD, using ICD-10 codes. We compared obese (body mass index [BMI] ≥ 30) vs non-obese [BMI < 30] patients with IBD to evaluate the independent effects of obesity on readmission, mortality, and other hospital outcomes. Multivariate regression and propensity matching were performed. RESULTS:We identified 143 190 patients with IBD, of whom 9.1% were obese. Obesity was independently associated with higher all-cause readmission at 30 days {18% vs 13% (adjusted odds ratio [aOR] 1.16, p = 0.005)} and 90 days (29% vs 21% [aOR 1.27, p < 0.0001]), as compared with non-obese patients, with similar findings upon a propensity-matched sensitivity analysis. Obese and non-obese patients had similar risks of mortality on index admission [0.24% vs 0.31%, p = 0.18] and readmission [1.5% vs 1.8% p = 0.3]. Obese patients had longer [5.3 vs 4.9 days] and more expensive [USD12,195 vs USD11,154] hospitalisations on index admission. Obesity did not affect the risk of intestinal surgery or bowel obstruction. Compared with index admissions, readmissions were characterised by increased mortality [6-fold], health care use, and bowel obstruction [3-fold] [all p < 0.0001]. CONCLUSIONS:Obesity in IBD appears to be associated with increased early readmission, characterised by a higher burden, despite the introduction of weight-based therapeutics. Prevention of obesity should be a focus in the treatment of IBD to decrease readmission and health care burden.

OBJECTIVE:Estimate the seroprevalence of SARS-CoV-2 antibodies among New York City Health and Hospitals (NYC H+H) healthcare workers during the first wave of the COVID-19 pandemic, and describe demographic and occupational factors associated with SARS-CoV-2 antibodies among healthcare workers. DESIGN:Descriptive, observational, cross-sectional study using a convenience sample of data from SARS-CoV-2 serological tests accompanied by a demographic and occupational survey administered to healthcare workers. SETTING:A large, urban public healthcare system in NYC. PARTICIPANTS:Participants were employed by NYC H+H and either completed serological testing at NYC H+H between 30 April 2020 and 30 June 2020, or completed SARS-CoV-2 antibody testing outside of NYC H+H and were able to self-report results from the same time period. PRIMARY OUTCOME MEASURE:SARS-CoV-2 serostatus, stratified by key demographic and occupational characteristics reported through the demographic and occupational survey. RESULTS:Seven hundred and twenty-seven survey respondents were included in analysis. Participants had a mean age of 46 years (SD=12.19) and 543 (75%) were women. Two hundred and fourteen (29%) participants tested positive or reported testing positive for the presence of SARS-CoV-2 antibodies (IgG+). Characteristics associated with positive SARS-CoV-2 serostatus were Black race (25% IgG +vs 15% IgG-, p=0.001), having someone in the household with COVID-19 symptoms (49% IgG +vs 21% IgG-, p<0.001), or having a confirmed COVID-19 case in the household (25% IgG +vs 5% IgG-, p<0.001). Characteristics associated with negative SARS-CoV-2 serostatus included working on a COVID-19 patient floor (27% IgG +vs 36% IgG-, p=0.02), working in the intensive care unit (20% IgG +vs 28% IgG-, p=0.03), being employed in a clinical occupation (64% IgG +vs 78% IgG-, p<0.001) or having close contact with a patient with COVID-19 (51% IgG +vs 62% IgG-, p=0.03). CONCLUSIONS:Results underscore the significance that community factors and inequities might have on SARS-CoV-2 exposure for healthcare workers.

Type I interferon (IFN) is critical in our defense against viral infections. Increased type I IFN pathway activation is a genetic risk factor for systemic lupus erythematosus (SLE), and a number of common risk alleles contribute to the high IFN trait. We hypothesized that these common gain-of-function IFN pathway alleles may be associated with protection from mortality in acute COVID-19. We studied patients admitted with acute COVID-19 (756 European-American and 398 African-American ancestry). Ancestral backgrounds were analyzed separately, and mortality after acute COVID-19 was the primary outcome. In European-American ancestry, we found that a haplotype of interferon regulatory factor 5 (IRF5) and alleles of protein kinase cGMP-dependent 1 (PRKG1) were associated with mortality from COVID-19. Interestingly, these were much stronger risk factors in younger patients (OR=29.2 for PRKG1 in ages 45-54). Variants in the IRF7 and IRF8 genes were associated with mortality from COVID-19 in African-American subjects, and these genetic effects were more pronounced in older subjects. Combining genetic information with blood biomarker data such as C-reactive protein, troponin, and D-dimer resulted in significantly improved predictive capacity, and in both ancestral backgrounds the risk genotypes were most relevant in those with positive biomarkers (OR for death between 14 and 111 in high risk genetic/biomarker groups). This study confirms the critical role of the IFN pathway in defense against COVID-19 and viral infections, and supports the idea that some common SLE risk alleles exert protective effects in anti-viral immunity.

BACKGROUND:Older adults with HIV (OAH) experience more comorbidities and geriatric syndromes than their HIV-negative peers, perhaps due to chronic inflammation. Cell-free mitochondrial DNA (cfmtDNA) released from cells undergoing necrosis-mediated cell death potentially acts as both a mediator and marker of inflammatory dysregulation. We hypothesized that urinary cfmtDNA would be associated with frailty, body composition and fall history in OAH. METHODS:OAH completed frailty testing, a psychosocial survey, body composition assessment, and measurement of urine cfmtDNA and urine albumin:creatinine in this cross-sectional study. Urine cfmtDNA was measured by qPCR and normalized to urinary creatinine. RESULTS:Across 150 participants, the mean age was 61 years (SD 6 years), half identified as Black, one-third were female, and 93% had HIV-1 viral load <200 copies/ml. Two-thirds met criteria for a pre-frail or frail state. Those with unintentional weight loss had higher urine cfmtDNA concentrations (p=0.03). Higher urine cfmtDNA was inversely associated with skeletal muscle index (SMI) (β =-0.19, p<0.01) and fat mass index (FMI) (β =-0.08, p=0.02) in separate multiple linear regression models adjusted for age, sex, and presence of moderate-severe albuminuria. CONCLUSIONS:In this cross-sectional study of OAH, higher levels of urine cfmtDNA were more common in subjects with less robust physical condition, including unintentional weight loss and less height-scaled body mass of fat and muscle. These findings suggest urine cfmtDNA may reflect pathophysiologic aging processes in OAH, predisposing them to geriatric syndromes. Longitudinal investigation of urine cfmtDNA as a biomarker of geriatric syndromes is warranted.

PURPOSE:Residency programs face overwhelming numbers of residency applications, limiting holistic review. Artificial intelligence techniques have been proposed to address this challenge but have not been created. Here, a multidisciplinary team sought to develop and validate a machine learning (ML)-based decision support tool (DST) for residency applicant screening and review. METHOD:Categorical applicant data from the 2018, 2019, and 2020 residency application cycles (n = 8,243 applicants) at one large internal medicine residency program were downloaded from the Electronic Residency Application Service and linked to the outcome measure: interview invitation by human reviewers (n = 1,235 invites). An ML model using gradient boosting was designed using training data (80% of applicants) with over 60 applicant features (e.g., demographics, experiences, academic metrics). Model performance was validated on held-out data (20% of applicants). Sensitivity analysis was conducted without United States Medical Licensing Examination (USMLE) scores. An interactive DST incorporating the ML model was designed and deployed that provided applicant- and cohort-level visualizations. RESULTS:The ML model areas under the receiver operating characteristic and precision recall curves were 0.95 and 0.76, respectively; these changed to 0.94 and 0.72, respectively, with removal of USMLE scores. Applicants' medical school information was an important driver of predictions-which had face validity based on the local selection process-but numerous predictors contributed. Program directors used the DST in the 2021 application cycle to select 20 applicants for interview that had been initially screened out during human review. CONCLUSIONS:The authors developed and validated an ML algorithm for predicting residency interview offers from numerous application elements with high performance-even when USMLE scores were removed. Model deployment in a DST highlighted its potential for screening candidates and helped quantify and mitigate biases existing in the selection process. Further work will incorporate unstructured textual data through natural language processing methods.