Faculty Bibliography

The coronavirus disease 2019 (COVID-19) pandemic has disrupted health systems worldwide, gravely threatening continuity of care for non-communicable diseases (NCDs), particularly in low-resource settings. We describe our efforts to maintain the continuity of care for patients with NCDs in rural western Kenya during the COVID-19 pandemic, using a five-component approach: 1) Protect: protect staff and patients; 2) Preserve: ensure medication availability and clinical services; 3) Promote: conduct health education and screenings for NCDs and COVID-19; 4) Process: collect process indicators and implement iterative quality improvement; and 5) Plan: plan for the future and ensure financial risk protection in the face of a potentially overwhelming health and economic catastrophe. As the pandemic continues to evolve, we must continue to pursue new avenues for improvement and expansion. We anticipate continuing to learn from the evolving local context and our global partners as we proceed with our efforts.

INTRODUCTION:Self-rated health has been extensively studied, but the utility of a similarly structured question to rate diet quality is not well characterized. This study aims to assess the relative validity of self-rated diet quality, compared with that of a validated diet quality measure (Healthy Eating Index-2015) and to examine the associations with cardiometabolic risk factors. METHODS:Analyses were conducted in 2020-2021 using cross-sectional data from the National Health and Nutrition Examination Survey, 2011-2018. Nonpregnant adults who responded to the question: How healthy is your overall diet? and provided 2 dietary recalls were eligible (n=16,913). Associations between self-rated diet quality (modeled as a 5-point continuous variable, poor=1 to excellent=5) and Healthy Eating Index-2015 scores and cardiometabolic risk factors were assessed by linear regression, accounting for the complex survey design and adjusting for demographic and lifestyle characteristics. RESULTS:. CONCLUSIONS:Self-rated diet quality was associated with Healthy Eating Index-2015 scores and cardiometabolic disease risk factors. This single-item assessment may be useful in time-limited settings to quickly and easily identify patients in need of dietary counseling to improve cardiometabolic health.

A library of well-characterized human induced pluripotent stem cell (hiPSC) lines from clinically healthy human subjects could serve as a useful resource of normal controls for in vitro human development, disease modeling, genotype-phenotype association studies, and drug response evaluation. We report generation and extensive characterization of a gender-balanced, racially/ethnically diverse library of hiPSC lines from 40 clinically healthy human individuals who range in age from 22 to 61 years. The hiPSCs match the karyotype and short tandem repeat identities of their parental fibroblasts, and have a transcription profile characteristic of pluripotent stem cells. We provide whole-genome sequencing data for one hiPSC clone from each individual, genomic ancestry determination, and analysis of mendelian disease genes and risks. We document similar transcriptomic profiles, single-cell RNA-sequencing-derived cell clusters, and physiology of cardiomyocytes differentiated from multiple independent hiPSC lines. This extensive characterization makes this hiPSC library a valuable resource for many studies on human biology.

BACKGROUND:In home health care, language barriers are understudied. Language barriers between patients and providers are known to affect a variety of patient outcomes. How a patient's language preference influences hospital readmission risk from home health care has yet to be determined. OBJECTIVE:To determine if home care patients' language preference is associated with their risk for hospital readmission from home health care within 30 days of hospital discharge. DESIGN/METHODS:Retrospective cross-sectional study of hospital readmissions from an urban home health care agency's administrative records and the national electronic home health care record for the United States, captured between 2010 and 2015. SETTING/METHODS:New York City, New York, USA. PARTICIPANTS/METHODS:The dataset comprised 90,221 post-hospitalization patients and 6.5 million home health care visits. METHODS:First, a Chi-square test was used to determine if there were significant differences in crude readmission rates based on language group. Inverse probability of treatment weighting was used to adjust for significant differences in known hospital readmission risk factors between to examine all-cause hospital readmission during a home health care stay. The final matched sample included 87,561 patients with a language preference of English, Spanish, Russian, Chinese, or Korean. English-speaking patients were considered the comparison group to the non-English speaking patients. A Marginal Structural Model was applied to estimate the impact of non-English language preference against English language preference on rehospitalization. The results of the marginal structural model were expressed as an odds ratio of likelihood of readmission to the hospital from home health care. RESULTS:Home health patients with a non-English language preference had a higher hospital readmission risk than English-speaking patients. Crude readmission rate for the limited English proficiency patients was 20.4% (95% CI, 19.9-21.0%) overall compared to 18.5% (95% CI, 18.7-19.2%) for English speakers (p < 0.001). Being a non-English-speaking patient was associated with an odds ratio of 1.011 (95% CI, 1.004-1.018) in increased hospital readmission rates from home health care (p = 0.001). There were also statistically significant differences in readmission rate by language group (p < 0.001), with Korean speakers having the lowest rate and Spanish speakers having the highest, when compared to English speakers. CONCLUSIONS:People with a non-English language preference have a higher readmission rate from home health care. Hospital and home healthcare agencies may need specialized care coordination services to reduce readmission risk for these patients. Tweetable abstract: A new US-based study finds that home care patients with language barriers are at higher risk for hospital readmission.

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.