Faculty Bibliography

OBJECTIVES:This study evaluated whether a range of demographic, social and geographic factors had an influence on glycaemic control longitudinally after an initial diagnosis of diabetes. DESIGN, SETTING AND PARTICIPANTS:We used the US Veterans Administration Diabetes Risk national cohort to track glycaemic control among patients 20-79-year old with a new diagnosis of type 2 diabetes. PRIMARY OUTCOME AND METHODS:We modelled associations between glycaemic control at follow-up clinical assessments and geographic factors including neighbourhood race/ethnicity, socioeconomic, land use and food environment measures. We also adjusted for individual demographics, comorbidities, haemoglobin A1c (HbA1c) at diagnosis and duration of follow-up. These factors were analysed within strata of community type: high-density urban, low-density urban, suburban/small town and rural areas. RESULTS:We analysed 246 079 Veterans who developed a new type 2 diabetes diagnosis in 2008-2018 and had at least 2 years of follow-up data available. Across all community types, we found that lower baseline HbA1c and female sex were strongly associated with a higher likelihood of within-range HbA1c at follow-up. Surprisingly, patients who were older or had more documented comorbidities were more likely to have within-range follow-up HbA1c results. While there was variation by community type, none of the geographic measures analysed consistently demonstrated significant associations with glycaemic control across all community types.

OBJECTIVE/UNASSIGNED:, the gene encoding the anti-inflammatory IL-1 receptor antagonist (IL-1Ra), on the cytokine release syndrome and mortality. METHODS/UNASSIGNED:gene were assessed for association with laboratory markers of the cytokine release syndrome (CRS) and mortality. RESULTS/UNASSIGNED:rs419598 CC SNV exhibited lower inflammatory biomarker levels, and was associated with reduced mortality compared to the CT/TT genotype in men (OR 0.49 (0.23 - 1.00); 0.052), with the most pronounced effect observed between the ages of 55-74 [5.5% vs. 18.4%, p<0.001]. CONCLUSION/UNASSIGNED:modulates the COVID-19 cytokine release syndrome via endogenous " anti-inflammatory" mechanisms. SIGNIFICANCE STATEMENT/UNASSIGNED:merits further evaluation in severe SARS-CoV-2 infection.

IntroductionOlder adults with IBD are at higher risk for postoperative complications as compared to their younger counterparts, however factors contributing to this are unknown. We assessed risk factors associated with adverse IBD-related surgical outcomes, evaluated trends in emergency surgery, and explored differential risks by age.MethodsUsing the American College of Surgeons National Surgical Quality Improvement Program (ACS-NSQIP) database, we identified adults ≥18 years of age who underwent an IBD-related intestinal resection from 2005-2019. Our primary outcome included a 30-day composite of mortality, readmission, reoperation, and/or major postoperative complication.ResultsOverall, 49,746 intestinal resections were performed with 9,390 (18.8%) occurring among older adults with IBD. Nearly 37% of older adults experienced an adverse outcome as compared to 28.1% among younger adults with IBD (p<0.01). Among all adults with IBD, the presence of preoperative sepsis (aOR, 2.08; 95%CI 1.94-2.24), malnutrition (aOR, 1.22; 95%CI 1.14-1.31), dependent functional status (aOR, 6.92; 95%CI 4.36-11.57), and requiring emergency surgery (aOR, 1.50; 95%CI 1.38-1.64) increased the odds of an adverse postoperative outcome, with similar results observed when stratifying by age. Further, 8.8% of surgeries among older adults were emergent, with no change observed over time (p=0.16).DiscussionPreoperative factors contributing to the risk of an adverse surgical outcome are similar between younger and older individuals with IBD, and include elements such as malnutrition and functional status. Incorporating these measures into surgical decision-making can reduce surgical delays in older individuals at low-risk and help target interventions in those at high risk, transforming care for thousands of older adults with IBD.

BACKGROUND:Internalizing and externalizing problems account for over 75% of the mental health burden in children and adolescents in the US, with higher burden among minority children. While complex interactions of multilevel factors are associated with these outcomes and may enable early identification of children in higher risk, prior research has been limited by data and application of traditional analysis methods. In this case example focused on Asian American children, we address the gap by applying data-driven statistical and machine learning methods to study clusters of mental health trajectories among children, investigate optimal predictions of children at high-risk cluster, and identify key early predictors. METHODS:Data from the US Early Childhood Longitudinal Study 2010-2011 were used. Multilevel information provided by children, families, teachers, schools, and care-providers were considered as predictors. Unsupervised machine learning algorithm was applied to identify groups of internalizing and externalizing problems trajectories. For prediction of high-risk group, ensemble algorithm, Superlearner, was implemented by combining several supervised machine learning algorithms. Performance of Superlearner and candidate algorithms, including logistic regression, was assessed using discrimination and calibration metrics via crossvalidation. Variable importance measures along with partial dependence plots were utilized to rank and visualize key predictors. FINDINGS/RESULTS:We found two clusters suggesting high- and low-risk groups for both externalizing and internalizing problems trajectories. While Superlearner had overall best discrimination performance, logistic regression had comparable performance for externalizing problems but worse for internalizing problems. Predictions from logistic regression were not well calibrated compared to those from Superlearner, however they were still better than few candidate algorithms. Important predictors identified were combination of test scores, child factors, teacher rated scores, and contextual factors, which showed non-linear associations with predicted probabilities. CONCLUSIONS:We demonstrated the application of data-driven analytical approach to predict mental health outcomes among Asian American children. Findings from the cluster analysis can inform critical age for early intervention, while prediction analysis has potential to inform intervention programing prioritization decisions. However, to better understand external validity, replicability, and value of machine learning in broader mental health research, more studies applying similar analytical approach is needed.

BACKGROUND:While emerging studies suggest that the COVID-19 pandemic caused disruptions in routine healthcare utilization, the full impact of the pandemic on healthcare utilization among diverse group of patients with type 2 diabetes is unclear. The purpose of this study is to examine trends in healthcare utilization, including in-person and telehealth visits, among U.S. veterans with type 2 diabetes before, during and after the onset of the COVID-19 pandemic, by demographics, pre-pandemic glycemic control, and geographic region. METHODS:We longitudinally examined healthcare utilization in a large national cohort of veterans with new diabetes diagnoses between January 1, 2008 and December 31, 2018. The analytic sample was 733,006 veterans with recently-diagnosed diabetes, at least 1 encounter with veterans administration between March 2018-2020, and followed through March 2021. Monthly rates of glycohemoglobin (HbA1c) measurements, in-person and telehealth outpatient visits, and prescription fills for diabetes and hypertension medications were compared before and after March 2020 using interrupted time-series design. Log-linear regression model was used for statistical analysis. Secular trends were modeled with penalized cubic splines. RESULTS:In the initial 3 months after the pandemic onset, we observed large reductions in monthly rates of HbA1c measurements, from 130 (95%CI,110-140) to 50 (95%CI,30-80) per 1000 veterans, and in-person outpatient visits, from 1830 (95%CI,1640-2040) to 810 (95%CI,710-930) per 1000 veterans. However, monthly rates of telehealth visits doubled between March 2020-2021 from 330 (95%CI,310-350) to 770 (95%CI,720-820) per 1000 veterans. This pattern of increases in telehealth utilization varied by community type, with lowest increase in rural areas, and by race/ethnicity, with highest increase among non-hispanic Black veterans. Combined in-person and telehealth outpatient visits rebounded to pre-pandemic levels after 3 months. Despite notable changes in HbA1c measurements and visits during that initial window, we observed no changes in prescription fills rates. CONCLUSIONS:Healthcare utilization among veterans with diabetes was substantially disrupted at the onset of the pandemic, but rebounded after 3 months. There was disparity in uptake of telehealth visits by geography and race/ethnicity.

Background/Purpose: Psoriatic arthritis (PsA) is a complex immune-mediated disease. Beyond its deleterious effects in the skin and joints, PsA can lead to decreased quality of life, increased psychosocial stress, and is associated with high levels of depression and anxiety. However, little is known about the effects of mental health on disease activity and severity. This may be especially important in PsA where up to half of patients have residual symptoms (i.e., pain, fatigue) despite effective immunomodulatory therapies. The objective of this study was to characterize the prevalence of psychiatric comorbidities and their impact on PsA outcomes in an urban, academic, combined clinic setting.
Method(s): Consecutive adult patients meeting CASPAR criteria (n=537) were prospectively recruited at the NYU Psoriatic Arthritis Center and followed for up to 2 years. All data was obtained from clinical visits using a standardized EPIC template. Depression was defined as patient-reported depression and/or use of anti-depressant medications.
Result(s): The cohort was 53% male, mostly Caucasian (79.7%) and had an average age of 49 years. Within our population, 23% had depression, 18% anxiety, and 4% ADHD (Table 1). At the initial visit, patients with depression were more likely to be female, older, and have concomitant anxiety compared to those without depression. Moreover, compared to their nondepressed counterparts, patients with depression had similar swollen joint counts (SJCs), tender joint counts (TJCs) and RAPID3 scores, as well as a lower percent body surface area (BSA). However, at the subsequent timepoints, while other outcomes remained similar between the groups, patients with depression had a higher TJC (Figure 1). When adjusting for age, sex, race, medication use, and comorbidities, the rate ratio (RR) of TJC in patients with depression vs. without depression was 1.23 (95%CI 0.78, 1.94, p=0.79) at baseline (Figure 2). This ratio was even higher at year 1 (RR 1.47, 95%CI 0.91, 2.35, p=0.19) and year 2 (RR 1.75, 95%CI 0.97, 3.14, p=0.07), nearing significance. In the adjusted models for SJC, BSA, and RAPID3, this pattern was not seen.
Conclusion(s): High rates of depression and anxiety in this cohort expand upon previously reported data. While most patients improve over time, TJC is significantly higher in those who carry a diagnosis of depression whereas SJC and BSA are similar in patients with and without depression. This may reflect differences in how patients with depression perceive their disease and may lead to difficulty in achieving low disease activity/remission by composite score measures. Therefore, addressing depression, along with inflammatory symptoms, should be considered, especially in those with residual pain. Further work is needed to understand if intervening on depression could help improve PsA outcomes

BACKGROUND/UNASSIGNED:Nonadherence to antihypertensive medications remains a persistent problem that leads to preventable morbidity and mortality. Behavioral economic strategies represent a novel way to improve antihypertensive medication adherence, but remain largely untested especially in vulnerable populations which stand to benefit the most. The Behavioral Economics Trial To Enhance Regulation of Blood Pressure (BETTER-BP) was designed in this context, to test whether a digitally-enabled incentive lottery improves antihypertensive adherence and reduces systolic blood pressure (SBP). DESIGN/UNASSIGNED:BETTER-BP is a pragmatic randomized trial conducted within 3 safety-net clinics in New York City: Bellevue Hospital Center, Gouveneur Hospital Center, and NYU Family Health Centers - Park Slope. The trial will randomize 435 patients with poorly controlled hypertension and poor adherence (<80% days adherent) in a 2:1 ratio (intervention:control) to receive either an incentive lottery versus passive monitoring. The incentive lottery is delivered via short messaging service (SMS) text messages that are delivered based on (1) antihypertensive adherence tracked via a wireless electronic monitoring device, paired with (2) a probability of lottery winning with variable incentives and a regret component for nonadherence. The study intervention lasts for 6 months, and ambulatory systolic blood pressure (SBP) will be measured at both 6 and 12 months to evaluate immediate and durable lottery effects. CONCLUSIONS/UNASSIGNED:BETTER-BP will generate knowledge about whether an incentive lottery is effective in vulnerable populations to improve antihypertensive medication adherence. If successful, this could lead to the implementation of this novel strategy on a larger scale to improve outcomes.

Background Angiotensin receptor neprilysin inhibitors (ARNI) reduce mortality and hospitalization for patients with heart failure. However, relatively high copayments for ARNI may contribute to suboptimal adherence, thus potentially limiting their benefits. Methods and Results We conducted a retrospective cohort study within a large, multi-site health system. We included patients with: ARNI prescription between November 20, 2020 and June 30, 2021; diagnosis of heart failure or left ventricular ejection fraction ≤40%; and available pharmacy or pharmacy benefit manager copayment data. The primary exposure was copayment, categorized as $0, $0.01 to $10, $10.01 to $100, and >$100. The primary outcome was prescription fill nonadherence, defined as the proportion of days covered <80% over 6 months. We assessed the association between copayment and nonadherence using multivariable logistic regression, and nonbinarized proportion of days covered using multivariable Poisson regression, adjusting for demographic, clinical, and neighborhood-level covariates. A total of 921 patients met inclusion criteria, with 192 (20.8%) having $0 copayment, 228 (24.8%) with $0.01 to $10 copayment, 206 (22.4%) with $10.01 to $100, and 295 (32.0%) with >$100. Patients with higher copayments had higher rates of nonadherence, ranging from 17.2% for $0 copayment to 34.2% for copayment >$100 (P<0.001). After multivariable adjustment, odds of nonadherence were significantly higher for copayment of $10.01 to $100 (odds ratio [OR], 1.93 [95% CI, 1.15-3.27], P=0.01) or >$100 (OR, 2.58 [95% CI, 1.63-4.18], P<0.001), as compared with $0 copayment. Similar associations were seen when assessing proportion of days covered as a proportion. Conclusions We found higher rates of not filling ARNI prescriptions among patients with higher copayments, which persisted after multivariable adjustment. Our findings support future studies to assess whether reducing copayments can increase adherence to ARNI and improve outcomes for heart failure.

BACKGROUND:Male sex, elevated troponin levels, and elevated D-dimer levels are associated with more complicated COVID-19 illness and greater mortality; however, while there are known sex differences in the prognostic value of troponin and D-dimer in other disease states, it is unknown whether they exist in the setting of COVID-19. OBJECTIVE:We assessed whether sex modified the relationship between troponin, D-dimer, and severe COVID-19 illness (defined as mechanical ventilation, ICU admission or transfer, discharge to hospice, or death). METHODS:We conducted a retrospective cohort study of patients hospitalized with COVID-19 at a large, academic health system. We used multivariable regression to assess associations between sex, troponin, D-dimer, and severe COVID-19 illness, adjusting for demographic, clinical, and laboratory covariates. To test whether sex modified the relationship between severe COVID-19 illness and troponin or D-dimer, models with interaction terms were utilized. RESULTS:Among 4,574 patients hospitalized with COVID-19, male sex was associated with higher levels of troponin and greater odds of severe COVID-19 illness, but lower levels of initial D-dimer when compared with female sex. While sex did not modify the relationship between troponin level and severe COVID-19 illness, peak D-dimer level was more strongly associated with severe COVID-19 illness in male patients compared to female patients (males: OR=2.91, 95%CI=2.63-2.34, p<0.001; females: OR=2.31, 95%CI=2.04-2.63, p<0.001; p-interaction=0.005). CONCLUSION/CONCLUSIONS:Sex did not modify the association between troponin level and severe COVID-19 illness, but did modify the association between peak D-dimer and severe COVID-19 illness, suggesting greater prognostic value for D-dimer in males with COVID-19.