Faculty Bibliography

PM2.5 is a frequently studied particulate matter metric, due to its wide range of identified overall adverse health effects, particularly cardiovascular health risks. However, there are no clear clinical practice guidelines for air pollution in regard to the prevention of cardiovascular health risks, since most of the current medical guidelines for CVD focus on metabolic risk factors such as hyperlipidemia or diabetes. We sought to determine the relationship between PM2.5 and cardiovascular disease, cardiovascular events, and all-cause mortality by performing a systematic review and meta-analysis. We searched Ovid MEDLINE, Ovid Embase, Ovid Cochrane Database of Systematic Reviews, Scopus, and Web of Science from the database inception to December 2022 for studies that reported an association between PM2.5 and cardiovascular disease, cardiovascular events, and all-cause mortality. We used the DerSimonian & Laird random-effects method to pool hazard ratios or risk ratios separately from the included studies. Of the total 18 prospective studies, 7,300,591 individuals were followed for a median follow-up of 9 years. Compared to low long-term exposure to PM 2.5 levels, an increase in exposure to PM 2.5 levels resulted in an increase in all-cause mortality (HR 1.08 95% CI of 1.05-1.11, P < 0.05). Similarly, when compared to a low long-term exposure to PM 2.5 levels, an increase in exposure to PM 2.5 levels resulted in an increase in cardiovascular disease (HR 1.09, 95% CI of 1.00-1.18, P < 0.05) and an increase in cardiovascular disease mortality (HR 1.12, 95% CI of 1.07-1.18, P < 0.05). Increased exposure to PM 2.5 levels is significantly associated with an increased risk of all-cause mortality, cardiovascular disease, and cardiovascular disease mortality. Although federal primary and secondary standards are in place, those standards are not low enough to prevent CVD health effects. Clinicians should emphasize PM2.5 as a modifiable CV risk factors for their patients to potentially reduce the development of CV complications. A clinical action guideline is needed specifically for air pollution effects on CVD, and how to mitigate them.

Post-traumatic stress disorder (PTSD) is a mental disorder diagnosed by clinical interviews, self-report measures and neuropsychological testing. Traumatic brain injury (TBI) can have neuropsychiatric symptoms similar to PTSD. Diagnosing PTSD and TBI is challenging and more so for providers lacking specialized training facing time pressures in primary care and other general medical settings. Diagnosis relies heavily on patient self-report and patients frequently under-report or over-report their symptoms due to stigma or seeking compensation. We aimed to create objective diagnostic screening tests utilizing Clinical Laboratory Improvement Amendments (CLIA) blood tests available in most clinical settings. CLIA blood test results were ascertained in 475 male veterans with and without PTSD and TBI following warzone exposure in Iraq or Afghanistan. Using random forest (RF) methods, four classification models were derived to predict PTSD and TBI status. CLIA features were selected utilizing a stepwise forward variable selection RF procedure. The AUC, accuracy, sensitivity, and specificity were 0.730, 0.706, 0.659, and 0.715, respectively for differentiating PTSD and healthy controls (HC), 0.704, 0.677, 0.671, and 0.681 for TBI vs. HC, 0.739, 0.742, 0.635, and 0.766 for PTSD comorbid with TBI vs HC, and 0.726, 0.723, 0.636, and 0.747 for PTSD vs. TBI. Comorbid alcohol abuse, major depressive disorder, and BMI are not confounders in these RF models. Markers of glucose metabolism and inflammation are among the most significant CLIA features in our models. Routine CLIA blood tests have the potential for discriminating PTSD and TBI cases from healthy controls and from each other. These findings hold promise for the development of accessible and low-cost biomarker tests as screening measures for PTSD and TBI in primary care and specialty settings.

BACKGROUND:Particulate matter (PM) exposure is responsible for seven million deaths annually and has been implicated in the pathogenesis of respiratory infections such as severe acute respiratory syndrome (SARS). Understanding modifiable risk factors of high mortality, resource burdensome C19 and exposure risks such as PM is key to mitigating their devastating effects. This systematic review focuses on the literature available, identifying the spatial and temporal variation in the role of quantified PM exposure in SARS disease outcome and planning our future experimental studies. METHODS:The systematic review utilized keywords adhered to the PRISMA guidelines. We included original human research studies in English. RESULTS:and SARS-related outcomes. A geographic and temporal variation in both PM and C19's role was observed. CONCLUSION/CONCLUSIONS:C19 is a high mortality and resource intensive disease which devastated the globe. PM exposure is also a global health crisis. Our systematic review focuses on the intersection of this impactful disease-exposure dyad and understanding the role of PM is important in the development of interventions to prevent future spread of viral infections.

OBJECTIVE:The primary objective was to determine the effect of the COVID-19 pandemic on volume, demographics, and mechanisms of injury (MOI) for patients seen at an urban multidisciplinary concussion center. During the first phase of the pandemic in the United States, stay-at-home orders led to decreased group activities and required cancellation of outpatient appointments or initiation of telemedicine visits. METHODS:This study was a retrospective chart review of 3500 patient electronic medical records (EMR). Patients aged 1-99 years were eligible if they had been seen at New York University Langone Health Concussion Center during March 1-December 31, 2019 (control/pre-pandemic period) or during the same period in 2020 (pandemic period). Injury date, appointment date, age, sex, and MOI were captured; statistical analyses were performed using Stata17 (StataCorp, College Station, TX). RESULTS:There were 48% fewer visits during the COVID-19 pandemic period compared to the 2019 control period. There was a decreased proportion of pediatric patients (15% control, 6% pandemic; p = 0.007, chi-square test). Fewer concussions were related to team sports (21% control, 5% pandemic; p < 0.001), and a greater proportion were caused by bicycle accidents (4% control, 8% pandemic; p = 0.037) and assault/domestic violence (3% control, 9% pandemic; p < 0.001). CONCLUSION/CONCLUSIONS:The relative proportions of concussion MOI, age distributions, and visit volumes were significantly associated with pre-pandemic vs. pandemic periods, suggesting that COVID-19 changed concussion epidemiology during the pandemic period. This study demonstrates how epidemiologic data may inform future resource allocation during public health emergencies.

BACKGROUND:Incidence is one of the most important epidemiologic indices in surveillance. However, determining incidence is complex and requires time-consuming cohort studies or registries with date of diagnosis. Estimating incidence from prevalence using mathematical relationships may facilitate surveillance efforts. The aim of this study was to examine whether a partial differential equation (PDE) can be used to estimate diabetes incidence from prevalence in youth. METHODS:We used age-, sex-, and race/ethnicity-specific estimates of prevalence in 2001 and 2009 as reported in the SEARCH for Diabetes in Youth study. Using these data, a PDE was applied to estimate the average incidence rates of type 1 and type 2 diabetes for the period between 2001 and 2009. Estimates were compared to annual incidence rates observed in SEARCH. Precision of the estimates was evaluated using 95% bootstrap confidence intervals. RESULTS:Despite the long period between prevalence measures, the estimated average incidence rates mirror the average of the observed annual incidence rates. Absolute values of the age-standardized sex- and type-specific mean relative errors are below 8%. CONCLUSIONS:Incidence of diabetes can be accurately estimated from prevalence. Since only cross-sectional prevalence data is required, employing this methodology in future studies may result in considerable cost savings.

The COVID-19 pandemic's impact on cardiovascular health behaviors including diet, physical activity, medication adherence, and self-care among people living with HIV (PLWH) remains unknown. Using qualitative analyses, we examined the impact of the COVID-19 pandemic on cardiovascular health behaviors among PLWH. Twenty-four PLWH were enrolled in this multisite study from September to October 2020. Individuals participated in semi-structured telephone interviews that were recorded, transcribed, and coded by 4 independent coders. Codes were adjudicated and analyzed for common themes. Participants were, on average, 59.2 years old (+/-9.4), 75% African American (n = 18) and 71% male (n = 17). The pandemic altered cardiovascular disease health behaviors. PLWH changed diet based on stay-at-home orders and food access. Alterations in physical activity included transitioning from gym and group class exercise to home-based exercise. Antiretroviral adherence was maintained, even when other health behaviors wavered, suggesting resilience in PLWH that may be harnessed to maintain other health behaviors.

PURPOSE/OBJECTIVE:It is unknown whether compliance with recommended monitoring tests during observation of localized prostate cancer has changed over time. MATERIALS AND METHODS/METHODS:We performed a retrospective cohort study of Medicare beneficiaries diagnosed with low- or intermediate-risk prostate cancer in 2004-2016 who were initially managed with observation for a minimum of 12 months. The primary objective was to examine rates of PSA testing, prostate biopsy, and prostate MRI. We used multivariable mixed effects Poisson regression to determine whether rates of PSA testing and prostate biopsy increased over time. In addition, we identified clinical, sociodemographic, and provider factors associated with the frequency of monitoring tests during observation. RESULTS:We identified 10,639 patients diagnosed at a median age of 73 (IQR 69-77) years. The median follow-up time was 4.3 (IQR 2.7-6.6) years after diagnosis. Among patients managed without treatment for 5 years, 98% received at ≥1 PSA test, 48.0% ≥1 additional prostate biopsy, and 31.0% ≥1 prostate MRI. Among patients managed with observation for ≥12 months, mixed effects Poisson regression revealed that rates of PSA testing and biopsy increased over time (per calendar year: RR 1.02, 95% CI: 1.02-1.03 and RR 1.10, 95% CI: 1.08-1.11, respectively). Clinical and sociodemographic factors including age, clinical risk, race/ethnicity, census tract poverty, and region were associated with rates of biopsy and PSA testing. CONCLUSIONS:Use of recommended monitoring tests including repeat prostate biopsy remains low among Medicare beneficiaries undergoing observation for low and intermediate-risk prostate cancer.

BACKGROUND:Patients presenting to emergency departments (EDs) after a nonfatal opioid-involved overdose are at high risk for future overdose and death. Responding to this risk, the New York City (NYC) Department of Health and Mental Hygiene operates the Relay initiative, which dispatches trained peer "Wellness Advocates" to meet patients in the ED after a suspected opioid-involved overdose and follow them for up to 90 days to provide support, education, referrals to treatment, and other resources using a harm reduction framework. METHODS:In this article, we describe the protocol for a multisite randomized controlled trial of Relay. Study participants are recruited from four NYC EDs and are randomized to receive the Relay intervention or site-directed care (the control arm). Outcomes are assessed through survey questionnaires conducted at 1-, 3-, and 6-months after the baseline visit, as well as through administrative health data. The primary outcome is the number of opioid-related adverse events, including any opioid-involved overdose or any other substance use-related ED visit, in the 12 months post-baseline. Secondary and exploratory outcomes will also be analyzed, as well as hypothesized mediators and moderators of Relay program effectiveness. CONCLUSION/CONCLUSIONS:We present the protocol for a multisite randomized controlled trial of a peer-delivered OD prevention intervention in EDs. We describe how the study was designed to minimize disruption to routine ED operations, and how the study was implemented and adapted during the COVID-19 pandemic. This trial is registered with ClinicalTrials.gov [NCT04317053].

BACKGROUND:The within-person and between-sensor variability of metrics from different interstitial continuous glucose monitoring (CGM) sensors in adults with type 2 diabetes not taking insulin is unclear. METHODS:Secondary analysis of data from 172 participants from the Hyperglycemic Profiles in Obstructive Sleep Apnea randomized clinical trial. Participants simultaneously wore Dexcom G4 and Abbott Libre Pro CGM sensors for up to 2 weeks at baseline and again at the 3-month follow-up visit. RESULTS:At baseline (up to 2 weeks of CGM), mean glucose for both the Abbott and Dexcom sensors was approximately 150 mg/dL (8.3 mmol/L) and time in range (70-180 mg/dL [3.9-10.0 mmol/L]) was just below 80%. When comparing the same sensor at 2 different time points (two 2-week periods, 3 months apart), the within-person coefficient of variation (CVw) in mean glucose was 17.4% (Abbott) and 14.2% (Dexcom). CVw for percent time in range: 20.1% (Abbott) and 18.6% (Dexcom). At baseline, the Pearson correlation of mean glucose from the 2 sensors worn simultaneously was r = 0.86, root mean squared error (RMSE), 13 mg/dL (0.7 mmol/L); for time in range, r = 0.88, RMSE, 8 percentage points. CONCLUSIONS:Substantial variation was observed within sensors over time and across 2 different sensors worn simultaneously on the same individuals. Clinicians should be aware of this variability when using CGM technology to make clinical decisions. ClinicalTrials.gov Identifier: NCT02454153.