Faculty Bibliography

IMPORTANCE/UNASSIGNED:Among older adults with ischemic heart disease, participation in traditional ambulatory cardiac rehabilitation (CR) remains low. While mobile health CR (mHealth-CR) provides a novel opportunity to deliver care, age-specific impairments to technology use may limit uptake, and efficacy data are currently lacking. OBJECTIVE/UNASSIGNED:To test whether mHealth-CR improves functional capacity in older adults. DESIGN, SETTING, AND PARTICIPANTS/UNASSIGNED:The RESILIENT phase 2, multicenter, randomized clinical trial recruited patients aged 65 years or older with ischemic heart disease (defined as a hospital visit for myocardial infarction or coronary revascularization) from 5 academic hospitals in New York, Connecticut, and Massachusetts between January 9, 2020, and April 22, 2024. INTERVENTION/UNASSIGNED:Participants were randomized 3:1 to mHealth-CR or usual care. mHealth-CR consisted of commercially available software delivered on a tablet computer, coupled with remote monitoring and weekly exercise therapist telephone calls, delivered over a 3-month duration. As RESILIENT was a trial conducted in a routine care setting to inform decision-making, participants in both arms were also allowed to receive traditional CR at their cardiologist's discretion. MAIN OUTCOMES AND MEASURES/UNASSIGNED:The primary outcome was change from baseline to 3 months in functional capacity, measured by 6-minute walk distance (6MWD). Secondary outcomes were health status (12-Item Short Form Health Survey [SF-12]), residual angina, and impairment in activities of daily living. RESULTS/UNASSIGNED:A total of 400 participants (median age, 71.0 years [range, 65.0-91.0 years]; 291 [72.8%] male) were randomized to mHealth-CR (n = 298) or usual care (n = 102) and included in the intention-to-treat analysis. Of those, 356 participants (89.0%) returned in person for 6MWD assessment at 3 months. For the primary outcome, there was no adjusted difference in 6MWD between participants receiving mHealth-CR vs usual care (15.6 m; 95% CI, -0.3 to 31.5 m; P = .06). Among subgroups, there was an improvement in 6MWD among women (36.6 m; 95% CI, 8.7-64.4 m). There were no differences in any secondary outcomes between groups (eg, adjusted difference in SF-12 physical component scores at 3 months: -1.9 points; 95% CI, -3.9 to 0.2 points). Based on inverse propensity score weighting, there was no effect of mHealth-CR on 6MWD among those who did not attend traditional CR (25.7 m; 95% CI, -8.7 to 60.2 m). CONCLUSIONS AND RELEVANCE/UNASSIGNED:In this randomized clinical trial of mHealth-CR vs usual care, mHealth-CR did not significantly increase 6MWD or result in improvements in secondary outcomes. The findings suggest the older adult population may require more age-tailored mHealth strategies to effectively improve outcomes. TRIAL REGISTRATION/UNASSIGNED:ClinicalTrials.gov Identifier: NCT03978130.

BACKGROUND:In cohort studies with time-to-event outcomes, covariates of interest often have values that change over time. The classical Cox regression model can handle time-dependent covariates but assumes linear effects on the log hazard function, which can be limiting in practice. Furthermore, when multiple correlated covariates are studied, it is of great interest to model their joint effects by allowing a flexible functional form and to delineate their relative contributions to survival risk. METHODS:Motivated by the World Trade Center (WTC)-exposed Fire Department of New York cohort study, we proposed a partial-linear single-index Cox (PLSI-Cox) model to investigate the effects of repeatedly measured metabolic syndrome indicators on the risk of developing WTC lung injury associated with particulate matter exposure. The PLSI-Cox model reduces the dimensionality of covariates while providing interpretable estimates of their effects. The model's flexible link function accommodates nonlinear effects on the log hazard function. We developed an iterative estimation algorithm using spline techniques to model the nonparametric single-index component for potential nonlinear effects, followed by maximum partial likelihood estimation of the parameters. RESULTS:Extensive simulations showed that the proposed PLSI-Cox model outperformed the classical time-dependent Cox regression model when the true relationship was nonlinear. When the relationship was linear, both the PLSI-Cox model and classical time-dependent Cox regression model performed similarly. In the data application, we found a possible nonlinear joint effect of metabolic syndrome indicators on survival risk. Among the different indicators, BMI had the largest positive effect on the risk of developing lung injury, followed by triglycerides. CONCLUSION/CONCLUSIONS:The PLSI-Cox models allow for the evaluation of nonlinear effects of covariates and offer insights into their relative importance and direction. These methods provide a powerful set of tools for analyzing data with multiple time-dependent covariates and survival outcomes, potentially offering valuable insights for both current and future studies.

BACKGROUND:The optimal management of patients with intermediate-risk pulmonary embolism (PE), who have right heart dysfunction (determined by a combination of imaging and cardiac biomarkers) but a normal blood pressure, is uncertain. These patients suffer from reduced functional capacity and a lower quality of life over the long-term, despite use of anticoagulant therapy. Catheter-directed therapy (CDT) is a promising treatment for acute PE that rapidly removes thrombus and potentially improves cardiac dysfunction. However, CDT has risk and is costly, and it is not known whether it improves long-term cardiorespiratory fitness and/or quality of life compared with anticoagulation alone. METHODS:) with cardiopulmonary exercise testing at 3 months and reduce New York Heart Association (NYHA) Class at 12 months compared with No-CDT. These 2 primary efficacy outcomes will be analyzed sequentially using a "gatekeeping" procedure; for NYHA class to be compared, peak oxygen consumption must first be shown to be significantly increased by CDT. Safety and cost-effectiveness will also be assessed. CONCLUSION/CONCLUSIONS:When completed, PE-TRACT will provide important evidence regarding the benefits and risks of CDT to treat intermediate-risk PE compared with anticoagulation alone. TRIAL REGISTRATION/BACKGROUND:clinicaltrials.gov: NCT05591118.

PURPOSE/OBJECTIVE:The Zoster Eye Disease Study (ZEDS) is the first randomized clinical trial to study the efficacy of long-term (1 year) suppressive valacyclovir treatment on herpes zoster ophthalmicus (HZO) outcomes. This article details the baseline characteristics of participants. SETTING/METHODS:The study was set at 95 participating clinical centers in 33 states, Canada, and New Zealand. STUDY POPULATION/METHODS:Immunocompetent adults with a history of a characteristic HZO unilateral rash and documentation of an episode of active dendriform epithelial keratitis, stromal keratitis, endothelial keratitis, or iritis within the preceding year, enrolled in ZEDS from November 2017 to January 2023. INTERVENTION/METHODS:Participants were randomized to double-masked oral valacyclovir 1 gm daily versus placebo for 1 year of treatment and followed for 18 months. RESULTS:Five hundred twenty-seven participants were enrolled across 4 strata according to age at HZO onset (younger or older than 60 years) and duration of HZO at enrollment (less or greater than 6 months), with an even distribution of men and women and a median age of 60 years. More participants with recent (57%, 300/527) than chronic HZO and younger than 60 years at HZO onset (54%, 286/527) were enrolled. Most participants were treated acutely with a recommended antiviral regimen (91%, 480/527) and had not been vaccinated against zoster (79%, 418/527). CONCLUSIONS:The broad ZEDS study population enhances the likelihood that ZEDS will provide generalizable high-quality evidence regarding the efficacy and safety of suppressive valacyclovir for HZO immunocompetent adults and whether it should become standard of care. TRIAL REGISTRATION/BACKGROUND:ClinicalTrials.gov Identifier: NCT03134196.

BACKGROUND:Asian Americans have the lowest colorectal cancer screening uptake of any racial and ethnic group in the United States. Asian Indians are among the most under-screened Asian American subgroups, but there is limited data for this population. We sought to characterize predictors of colonoscopy use among Asian Indians in New York City. METHODS:Using 2003 to 2016 data from the New York City Community Health Survey, we identified all Asian Indian participants aged 50 years or older. We examined the association between sociodemographic and medical factors and up-to-date colonoscopy use (defined as colonoscopy within the last 10 y) using logistic regression over 4 time periods: 2003 to 2008, 2009 to 2012, 2013 to 2014, 2015 to 2016. RESULTS:On multivariable analysis, language, age, income, recent exercise, body mass index, and influenza vaccination were associated with colonoscopy uptake in 1 time period. Compared with participants who preferred English, those who preferred an Indian language were less likely to have been up-to-date in 2013 to 2014 (odds ratio 0.12, 95% CI 0.02-0.66). Individuals older than 65 years were more likely than those aged 50 to 64 years to have received a colonoscopy in 2009 to 2012 (odds ratio 3.91, 95% CI 1.49-10.24), although the risk estimates were also consistently positive in the other 3 time periods. CONCLUSIONS:Among Asian Indians living in New York City, several demographic, socioeconomic, and health-related characteristics predict colonoscopy use. These findings highlight the importance of examining determinants of colonoscopy uptake in this understudied population to inform future public health interventions.

In studies with time-to-event outcomes, multiple, inter-correlated, and time-varying covariates are commonly observed. It is of great interest to model their joint effects by allowing a flexible functional form and to delineate their relative contributions to survival risk. A class of semiparametric transformation (ST) models offers flexible specifications of the intensity function and can be a general framework to accommodate nonlinear covariate effects. In this paper, we propose a partial-linear single-index (PLSI) transformation model that reduces the dimensionality of multiple covariates into a single index and provides interpretable estimates of the covariate effects. We develop an iterative algorithm using the regression spline technique to model the nonparametric single-index function for possibly nonlinear joint effects, followed by nonparametric maximum likelihood estimation. We also propose a nonparametric testing procedure to formally examine the linearity of covariate effects. We conduct Monte Carlo simulation studies to compare the PLSI transformation model with the standard ST model and apply it to NYU Langone Health de-identified electronic health record data on COVID-19 hospitalized patients' mortality and a Veteran's Administration lung cancer trial.

The stepped wedge design is often used to evaluate interventions as they are rolled out across schools, health clinics, communities, or other clusters. Most models used in the design and analysis of stepped wedge trials assume that the intervention effect is immediate and constant over time following implementation of the intervention (the "exposure time"). This is known as the IT (immediate treatment effect) assumption. However, recent research has shown that using methods based on the IT assumption when the treatment effect varies over exposure time can give extremely misleading results. In this manuscript, we discuss the need to carefully specify an appropriate measure of the treatment effect when the IT assumption is violated and we show how a stepped wedge trial can be powered when it is anticipated that the treatment effect will vary as a function of the exposure time. Specifically, we describe how to power a trial when the exposure time indicator (ETI) model of Kenny et al. (Statistics in Medicine, 41, 4311-4339, 2022) is used and the estimand of interest is a weighted average of the time-varying treatment effects. We apply these methods to the ADDRESS-BP trial, a type 3 hybrid implementation study designed to address racial disparities in health care by evaluating a practice-based implementation strategy to reduce hypertension in African American communities.

BACKGROUND:There is a need to understand the relationship between COVID-19 Convalescent Plasma (CCP) anti-SARS-CoV-2 IgG levels and clinical outcomes to optimize CCP use. This study aims to evaluate the relationship between recipient baseline clinical status, clinical outcomes, and CCP antibody levels. METHODS:The study analyzed data from the COMPILE study, a meta-analysis of pooled individual patient data from 8 randomized clinical trials (RCTs) assessing the efficacy of CCP vs. control, in adults hospitalized for COVID-19 who were not receiving mechanical ventilation at randomization. SARS-CoV-2 IgG levels, referred to as 'dose' of CCP treatment, were retrospectively measured in donor sera or the administered CCP, semi-quantitatively using the VITROS Anti-SARS-CoV-2 IgG chemiluminescent immunoassay (Ortho-Clinical Diagnostics) with a signal-to-cutoff ratio (S/Co). The association between CCP dose and outcomes was investigated, treating dose as either continuous or categorized (higher vs. lower vs. control), stratified by recipient oxygen supplementation status at presentation. RESULTS:A total of 1714 participants were included in the study, 1138 control- and 576 CCP-treated patients for whom donor CCP anti-SARS-CoV2 antibody levels were available from the COMPILE study. For participants not receiving oxygen supplementation at baseline, higher-dose CCP (/control) was associated with a reduced risk of ventilation or death at day 14 (OR = 0.19, 95% CrI: [0.02, 1.70], posterior probability Pr(OR < 1) = 0.93) and day 28 mortality (OR = 0.27 [0.02, 2.53], Pr(OR < 1) = 0.87), compared to lower-dose CCP (/control) (ventilation or death at day 14 OR = 0.79 [0.07, 6.87], Pr(OR < 1) = 0.58; and day 28 mortality OR = 1.11 [0.10, 10.49], Pr(OR < 1) = 0.46), exhibiting a consistently positive CCP dose effect on clinical outcomes. For participants receiving oxygen at baseline, the dose-outcome relationship was less clear, although a potential benefit for day 28 mortality was observed with higher-dose CCP (/control) (OR = 0.66 [0.36, 1.13], Pr(OR < 1) = 0.93) compared to lower-dose CCP (/control) (OR = 1.14 [0.73, 1.78], Pr(OR < 1) = 0.28). CONCLUSION/CONCLUSIONS:Higher-dose CCP is associated with its effectiveness in patients not initially receiving oxygen supplementation, however, further research is needed to understand the interplay between CCP anti-SARS-CoV-2 IgG levels and clinical outcome in COVID-19 patients initially receiving oxygen supplementation.

INTRODUCTION/BACKGROUND:Diverse neurological conditions are reported associated with the SARS-CoV-2 virus; neurological symptoms are the most common conditions to persist after the resolution of acute infection, affecting 20% of patients 6 months after acute illness. The COVID-19 Neuro Databank (NeuroCOVID) was created to overcome the limitations of siloed small local cohorts to collect detailed, curated, and harmonized de-identified data from a large diverse cohort of adults with new or worsened neurological conditions associated with COVID-19 illness, as a scientific resource. METHODS:A Steering Committee including US and international experts meets quarterly to provide guidance. Initial study sites were recruited to include a wide US geographic distribution; academic and non-academic sites; urban and non-urban locations; and patients of different ages, disease severity, and comorbidities seen by a variety of clinical specialists. The NeuroCOVID REDCap database was developed, incorporating input from professional guidelines, existing common data elements, and subject matter experts. A cohort of eligible adults is identified at each site; inclusion criteria are: a new or worsened neurological condition associated with a COVID-19 infection confirmed by testing. De-identified data are abstracted from patients' medical records, using standardized common data elements and five case report forms. The database was carefully enhanced in response to feedback from site investigators and evolving scientific interest in post-acute conditions and their timing. Additional US and international sites were added, focusing on diversity and populations not already described in published literature. By early 2024, NeuroCOVID included over 2,700 patient records, including data from 16 US and 5 international sites. Data are being shared with the scientific community in compliance with NIH requirements. The program has been invited to share case report forms with the National Library of Medicine as an ongoing resource for the scientific community. CONCLUSION/CONCLUSIONS:The NeuroCOVID database is a unique and valuable source of comprehensive de-identified data on a wide variety of neurological conditions associated with COVID-19 illness, including a diverse patient population. Initiated early in the pandemic, data collection has been responsive to evolving scientific interests. NeuroCOVID will continue to contribute to scientific efforts to characterize and treat this challenging illness and its consequences.