Faculty Bibliography

BACKGROUND/UNASSIGNED:Advancements in medical technology, healthcare delivery, and organ allocation resulted in improved patient/graft survival for older (age ≥65) kidney transplant (KT) recipients. However, the recent trends in these post-KT outcomes are uncertain in light of the mounting burden of cardiovascular disease, changing kidney allocation policies, heterogeneity in candidates' risk profile, and the coronavirus disease 2019 pandemic. Thus, we examined secular trends in post-KT outcomes among older and younger KT recipients over the last 3 decades. METHODS/UNASSIGNED:We identified 73 078 older and 378 800 younger adult (aged 18-64) recipients using Scientific Registry of Transplant Recipients (1990-2022). KTs were grouped into 6 prepandemic eras and 1 postpandemic-onset era. Kaplan-Meier and Cox proportional hazards models were used to examine temporal trends in post-KT mortality and death-censored graft failure. RESULTS/UNASSIGNED:From 1990 to 2022, a 19-fold increase in the proportion of older KT recipients was observed compared to a 2-fold increase in younger adults despite a slight decline in the absolute number of older recipients in 2020. The mortality risk for older recipients between 2015 and March 14, 2020, was 39% (adjusted hazard ratio [aHR] = 0.61, 95% confidence interval [CI], 0.50-0.75) lower compared to 1990-1994, whereas that for younger adults was 47% lower (aHR = 0.53, 95% CI, 0.48-0.59). However, mortality risk during the pandemic was 25% lower (aHR = 0.75, 95% CI, 0.61-0.93) in older adults and 37% lower in younger adults (aHR = 0.63, 95% CI, 0.56-0.70) relative to 1990-1994. For both populations, the risk of graft failure declined over time and was unaffected during the pandemic relative to the preceding period. CONCLUSIONS/UNASSIGNED:The steady improvements in 5-y mortality and graft survival were disrupted during the pandemic, particularly among older adults. Specifically, mortality among older adults reflected rates seen 20 y prior.

CONTEXT/UNASSIGNED:Minoritized populations such as racial and ethnic minorities and individuals of less privileged socioeconomic status experience a disproportionate burden of poor hypertension (HTN) control in the United States. Multilevel systems interventions have been shown to improve patient-level outcomes in minoritized populations; however, there remains a large translational gap in implementing these approaches into federally qualified health centers (FQHC), which serve those at highest risk of HTN-related morbidity and mortality. The paucity of purposeful collaborations between academic researchers and practice staff throughout the research process remains a significant roadblock to the timely translation of evidence to practice. DESIGN/UNASSIGNED:This commentary describes the key principles and best practices that underlie the development and sustainment of an equitable research-practice alignment, which is supporting the implementation of multilevel systems intervention for improved HTN care in a large FQHC in Brooklyn, New York. The key principles, which are derived from the central tenants of relationship development and maintenance in community-engaged participatory research, patient-centered outcomes research, and organizational alignment theory include (1) cocreation of a shared mental model, (2) bridging multilevel communication, (3) ensuring mutual accountability, and (4) creating a culture of continuous improvement. CONCLUSIONS/UNASSIGNED:Together, the principles guide how the research and practice teams work together to achieve a shared goal of improving the health and well-being of minoritized patients through the provision of high quality, community-oriented HTN care. Best practices to sustain our alignment require an ongoing and deliberate investment in honest and transparent communication by all members.

Research has linked spatial concentrations of incarceration with racial disparities in adverse birth outcomes. However, little is known about the specific mechanisms of this association. This represents an important knowledge gap in terms of intervention. We theorize two pathways that may account for the association between county-level prison rates and adverse birth outcomes: (1) community-level mental distress and (2) reduced health care access. Examining these mechanisms, we conducted a cross-sectional study of county-level prison rates, community-level mental distress, health insurance, availability of primary care physicians (PCP) and mental health providers (MHP), and adverse birth outcomes (preterm birth, low birth weight, infant mortality). Our data set included 475 counties and represented 2,677,840 live U.S. births in 2016. Main analyses involved between 170 and 326 counties. All data came from publicly available sources, including the U.S. Census and the Centers for Disease Control and Prevention. Descriptive and regression results confirmed the link between prison rates and adverse birth outcomes and highlighted Black-White inequities in this association. Further, bootstrap mediation analyses indicated that the impact of spatially concentrated prison rates on preterm birth was mediated by PCP, MHP, community-level mental distress, and health insurance in both crude and adjusted models. Community-level mental distress and health insurance (but not PCP or MHP) similarly mediated low birthweight in both models. Mediators were less stable in the effect on infant mortality with only MHP mediating consistently across models. We conclude that mass incarceration, health care access, and community mental distress represent actionable and urgent targets for structural-, community-, and individual-level interventions targeting population inequities in birth outcomes.

BACKGROUND:Maternal stress has negative consequences on infant behavioral development, and COVID-19 presented uniquely stressful situations to mothers of infants born during the pandemic. We hypothesized that mothers with higher levels of perceived stress during the pandemic would report higher levels of infant regulatory problems including crying and interrupted sleep patterns. METHODS:As part 6 sites of a longitudinal study, mothers of infants born during the pandemic completed the Perceived Stress Scale, the Brief Infant Sleep Questionnaire, and an Infant Crying survey at 6 (n = 433) and 12 (n = 344) months of infant age. RESULTS:Maternal perceived stress, which remained consistent at 6 and 12 months of infant age, was significantly positively correlated with time taken to settle infants. Although maternal perceived stress was not correlated with uninterrupted sleep length, time taken to put the infant to sleep was correlated. Perceived stress was also correlated with the amount of infant crying and fussiness reported at 6 months. CONCLUSIONS:Mothers who reported higher levels of perceived stress during the pandemic reported higher levels of regulatory problems, specifically at 6 months. Examining how varying levels of maternal stress and infant behaviors relate to overall infant developmental status over time is an important next step. IMPACT/CONCLUSIONS:Women giving birth during the COVID-19 pandemic who reported higher levels of stress on the Perceived Stress Scale also reported higher levels of infant fussiness and crying at 6 months old, and more disruptive sleep patterns in their infants at 6 months and 12 months old. Sleeping problems and excessive crying in infancy are two regulatory problems that are known risk factors for emotional and behavioral issues in later childhood. This paper is one of the first studies highlighting the associations between maternal stress and infant behaviors during the COVID-19 pandemic.

A more granular donor kidney grading scale, the kidney donor profile index (KDPI), has recently emerged in contradistinction to the standard criteria donor/expanded criteria donor framework. In this paper, we built a Markov decision process model to evaluate the survival, quality-adjusted life years (QALY), and cost advantages of using high-KDPI kidneys based on multiple KDPI strata over a 60-month time horizon as opposed to remaining on the waiting list waiting for a lower-KDPI kidney. Data for the model were gathered from the Scientific Registry of Transplant Recipients and the United States Renal Data System Medicare parts A, B, and D databases. Of the 129,024 phenotypes delineated in this model, 65% of them would experience a survival benefit, 81% would experience an increase in QALYs, 87% would see cost-savings, and 76% would experience cost-savings per QALY from accepting a high-KDPI kidney rather than remaining on the waiting list waiting for a kidney of lower-KDPI. Classification and regression tree analysis (CART) revealed the main drivers of increased survival in accepting high-KDPI kidneys were wait time ≥30 months, panel reactive antibody (PRA) <90, age ≥45 to 65, diagnosis leading to renal failure, and prior transplantation. The CART analysis showed the main drivers of increased QALYs in accepting high-kidneys were wait time ≥30 months, PRA <90, and age ≥55 to 65.

Stakeholders need data on health and drivers of health parsed to the boundaries of essential policy-relevant geographies. US Congressional Districts are an example of a policy-relevant geography which generally lack health data. One strategy to generate Congressional District heath data metric estimates is to aggregate estimates from other geographies, for example, from counties or census tracts to Congressional Districts. Doing so requires several methodological decisions. We refine a method to aggregate health metric estimates from one geography to another, using a population weighted approach. The method's accuracy is evaluated by comparing three aggregated metric estimates to metric estimates from the US Census American Community Survey for the same years: Broadband Access, High School Completion, and Unemployment. We then conducted four sensitivity analyses testing: the effect of aggregating counts vs. percentages; impacts of component geography size and data missingness; and extent of population overlap between component and target geographies. Aggregated estimates were very similar to estimates for identical metrics drawn directly from the data source. Sensitivity analyses suggest the following best practices for Congressional district-based metrics: utilizing smaller, more plentiful geographies like census tracts as opposed to larger, less plentiful geographies like counties, despite potential for less stable estimates in smaller geographies; favoring geographies with higher percentage population overlap.

INTRODUCTION/UNASSIGNED:Epidemiological studies commonly use residential addresses at birth to estimate exposures throughout pregnancy, ignoring residential mobility. Lack of consideration for residential mobility during pregnancy might lead to exposure misclassification that should be addressed in environmental epidemiology. METHODS/UNASSIGNED:), temperature, and greenness (Enhanced Vegetation Index [EVI]). RESULTS/UNASSIGNED:) and EVI (range -0.305 to 0.307, average -0.013), but not temperature. Overestimations were significantly larger for mothers with higher socioeconomic status. Our findings indicate that the error for prenatal exposure can occur when residential mobility is not considered and is disproportional by maternal characteristics. CONCLUSIONS/UNASSIGNED:Epidemiological studies should consider residential mobility in exposure assessments based on geolocation when possible, and results based on mother's residence at birth should be interpreted with understanding of potential differential exposure misclassification.

BACKGROUND/UNASSIGNED:Nightclub/festival attendees are a population with high rates of party drug use, but research is needed to determine whether there have been shifts in unintended drug exposure in this population (e.g., via adulterants) to inform prevention and harm reduction efforts. METHODS/UNASSIGNED:Adults entering nightclubs and festivals in New York City were asked about past-year drug use in 2016 through 2022, with a subset providing a hair sample for testing. We focused on the 1943 who reported ecstasy use (of which 247 had a hair sample analyzed) and compared trends in self-reported drug use, drug positivity, and adjusted prevalence (adjusting for unreported use). RESULTS/UNASSIGNED:MDMA positivity decreased from 74.4 % to 42.3 %, and decreases occurred regarding detection of synthetic cathinones ("bath salts"; a 100.0 % decrease), MDA (a 76.9 % decrease), amphetamine (an 81.3 % decrease), methamphetamine (a 64.2 % decrease), and ketamine (a 33.4 % decrease) (ps < .05). Although prevalence of MDA and synthetic cathinone use was comparable between self-report and adjusted report in 2022, gaps in prevalence were wider in 2016 (ps < .01). Adjusted prevalence of synthetic cathinone use decreased more across time than prevalence based on self-report (a 79.4 % vs. 69.1 % decrease) and adjusted report for MDA use decreased more than prevalence based on self-report (a 50.6 % vs. 38.9 % decrease). CONCLUSIONS/UNASSIGNED:Combining self-report and toxicology tests helped us determine that decreases in drug use/exposure were steeper regarding adjusted prevalence. Underreported drug exposure-possibly due to exposure to adulterants-appears to have had less of an effect on prevalence in 2022 than it did in 2016.

OBJECTIVE:To evaluate the association between census-tract level measures of social vulnerability and residential segregation and IPN follow up. METHODS:This retrospective cohort study included patients with IPN ≥6 mm in size or multiple subsolid/ground-glass IPNs <6 mm (with non-optional follow-up recommendations) diagnosed between January 1, 2018 and December 30, 2019 at a large urban tertiary center and followed ≥two years. Geographic sociodemographic context was characterized by 2018 U.S. Centers for Disease Control and Prevention Social Vulnerability Index (SVI) and the Index of Concentration at the Extreme (ICE), categorized in quartiles. Multivariable binomial regression models were utilized with a primary outcome of inappropriate IPN follow up (late or no follow up). Models were also stratified by nodule risk. RESULTS:The study consisted of 2,492 patients (mean age 65.6 years +/- 12.6 years; 1,361 women). Top-quartile SVI patients were more likely to have inappropriate follow up (Risk Ratio [RR]: 1.24, 95% Confidence Interval [95% CI], 1.12-1.36]), compared with the bottom quartile; risk was also elevated in top-quartile SVI subcategories of Socioeconomic Status (RR: 1.23, 95% CI, 1.13-1.34), Minority Status and Language (RR: 1.24, 95% CI, 1.03-1.48), Housing and Transportation (RR: 1.13, 95% CI, 1.02-1.26), and ICE (RR: 1.20, 95% CI, 1.11-1.30). Further, top-quartile ICE was associated with greater risk of inappropriate follow up among high-risk vs. lower-risk IPN (1.33 [1.18-1.50] vs. 1.13 [1.02-1.25]), respectively, P for interaction= 0.017). DISCUSSION/CONCLUSIONS:Local social vulnerability and residential segregation are associated with inappropriate IPN follow up and may inform policy or interventions tailored for neighborhoods.

BACKGROUND:We have an incomplete understanding of COVID-19 characteristics at hospital presentation and whether underlying subphenotypes are associated with clinical outcomes and therapeutic responses. METHODS:For this cross-sectional study, we extracted electronic health data from adults hospitalized between 1 March and 30 August 2020 with a PCR-confirmed diagnosis of COVID-19 at five New York City Hospitals. We obtained clinical and laboratory data from the first 24 h of the patient's hospitalization. Treatment with tocilizumab and convalescent plasma was assessed over hospitalization. The primary outcome was mortality; secondary outcomes included intubation, intensive care unit (ICU) admission and length of stay (LOS). First, we employed latent class analysis (LCA) to identify COVID-19 subphenotypes on admission without consideration of outcomes and assigned each patient to a subphenotype. We then performed robust Poisson regression to examine associations between COVID-19 subphenotype assignment and outcome. We explored whether the COVID-19 subphenotypes had a differential response to tocilizumab and convalescent plasma therapies. RESULTS:A total of 4620 patients were included. LCA identified six subphenotypes, which were distinct by level of inflammation, clinical and laboratory derangements and ranged from a hypoinflammatory subphenotype with the fewest derangements to a hyperinflammatory with multiorgan dysfunction subphenotypes. Multivariable regression analyses found differences in risk for mortality, intubation, ICU admission and LOS, as compared to the hypoinflammatory subphenotype. For example, in multivariable analyses the moderate inflammation with fever subphenotype had 3.29 times the risk of mortality (95% CI 2.05, 5.28), while the hyperinflammatory with multiorgan failure subphenotype had 17.87 times the risk of mortality (95% CI 11.56, 27.63), as compared to the hypoinflammatory subphenotype. Exploratory analyses suggested that subphenotypes may differential respond to convalescent plasma or tocilizumab therapy. CONCLUSION:COVID-19 subphenotype at hospital admission may predict risk for mortality, ICU admission and intubation and differential response to treatment.KEY MESSAGEThis cross-sectional study of COVID patients admitted to the Mount Sinai Health System, identified six distinct COVID subphenotypes on admission. Subphenotypes correlated with ICU admission, intubation, mortality and differential response to treatment.