Faculty Bibliography

Understanding neural function requires quantification of the sensory signals that an animal's brain evolved to interpret. These signals in turn depend on the morphology and mechanics of the animal's sensory structures. Although the house mouse (Mus musculus) is one of the most common model species used in neuroscience, the spatial arrangement of its facial sensors has not yet been quantified. To address this gap, the present study quantifies the facial morphology of the mouse, with a particular focus on the geometry of its vibrissae (whiskers). The study develops equations that establish relationships between the three-dimensional (3D) locations of whisker basepoints, whisker geometry (arclength, curvature) and the 3D angles at which the whiskers emerge from the face. Additionally, the positions of facial sensory organs are quantified relative to bregma-lambda. Comparisons with the Norway rat (Rattus norvegicus) indicate that when normalized for head size, the whiskers of these two species have similar spacing density. The rostral-caudal distances between facial landmarks of the rat are a factor of ∼2.0 greater than the mouse, while the scale of bilateral distances is larger and more variable. We interpret these data to suggest that the larger size of rats compared with mice is a derived (apomorphic) trait. As rodents are increasingly important models in behavioral neuroscience, the morphological model developed here will help researchers generate naturalistic, multimodal patterns of stimulation for neurophysiological experiments and allow the generation of synthetic datasets and simulations to close the loop between brain, body and environment.

BACKGROUND:Low medication adherence is a common cause of high blood pressure but is often unrecognized in clinical practice. Electronic data linkages between electronic health records (EHRs) and pharmacies offer the opportunity to identify low medication adherence, which can be used for interventions at the point of care. We developed a multicomponent intervention that uses linked EHR and pharmacy data to automatically identify patients with elevated blood pressure and low medication adherence. The intervention then combines team-based care with EHR-based workflows to address medication nonadherence. OBJECTIVE:This study aims to describe the design of the Leveraging EHR Technology and Team Care to Address Medication Adherence (TEAMLET) trial, which tests the effectiveness of a multicomponent intervention that leverages EHR-based data and team-based care on medication adherence among patients with hypertension. METHODS:TEAMLET is a pragmatic, cluster randomized controlled trial in which 10 primary care practices will be randomized 1:1 to the multicomponent intervention or usual care. We will include all patients with hypertension and low medication adherence who are seen at enrolled practices. The primary outcome is medication adherence, as measured by the proportion of days covered, and the secondary outcome is clinic systolic blood pressure. We will also assess intervention implementation, including adoption, acceptability, fidelity, cost, and sustainability. RESULTS:As of May 2023, we have randomized 10 primary care practices into the study, with 5 practices assigned to each arm of the trial. The enrollment for the study commenced on October 5, 2022, and the trial is currently ongoing. We anticipate patient recruitment to go through the fall of 2023 and the primary outcomes to be assessed in the fall of 2024. CONCLUSIONS:The TEAMLET trial will evaluate the effectiveness of a multicomponent intervention that leverages EHR-based data and team-based care on medication adherence. If successful, the intervention could offer a scalable approach to address inadequate blood pressure control among millions of patients with hypertension. TRIAL REGISTRATION/BACKGROUND:ClinicalTrials.gov NCT05349422; https://clinicaltrials.gov/ct2/show/NCT05349422. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)/UNASSIGNED:DERR1-10.2196/47930.

BACKGROUND/UNASSIGNED:Type 2 diabetes (T2D) disproportionately affects South Asians in the United States (US). Living with T2D can be challenging due to the distress it can create for an individual. Distress associated with diabetes, commonly known as diabetes distress (DD), may lead to complications and challenges with the management of diabetes. This study aims to describe the prevalence of DD among a sample of South Asians in New York City (NYC) seeking care in community-based primary care settings and its association with sociodemographic characteristics and clinical measures. METHODS/UNASSIGNED:This study utilized baseline data from the Diabetes Research, Education, and Action for Minorities (DREAM) Initiative, an intervention designed to reduce hemoglobin A1C (HbA1c) among South Asians with uncontrolled T2D in NYC. DD was measured using the Diabetes Distress Scale (DDS). First, descriptive statistics were used to analyze sociodemographic variables. Chi-square tests assessed categorical variables and Wilcoxon Rank Sum tests assessed continuous variables using a Type I error rate of 0.05. Logistic regression was performed to determine if HbA1c and mental health, along with other covariates, were associated with dichotomized DDS subscales. RESULTS/UNASSIGNED:Overall, 415 participants completed the DDS at baseline. Median age was 56 years (IQR: 48-62). A total of 25.9% had high emotional burden distress, 6.6% had high physician-related distress, and 22.2% had high regimen-related distress based on subscales. In adjusted analyses, individuals with any days of poor mental health had significantly higher odds of overall distress (OR:3.7, p=0.014), emotional burden distress (OR:4.9, p<0.001), and physician-related distress (OR:5.0, p=0.002) compared to individuals with no days of poor mental health. Individuals with higher HbA1c had significantly higher odds of regimen-related distress (OR:1.31, p=0.007). CONCLUSIONS/UNASSIGNED:Findings suggest that DD is prevalent among this sample of South Asians with diagnosed T2D in NYC. Screening for DD in patients with prediabetes/diabetes should be considered by providers to help provide mental and physical health services during primary care visits. Future research can also benefit from a longitudinal analysis of the impact of DD on diabetes self-management, medication adherence, and mental and physical health. TRIAL REGISTRATION/UNASSIGNED:This study uses baseline data from "Diabetes Management Intervention For South Asians" (NCT03333044), which was registered with clinicaltrials.gov on 6/11/2017.

Clinical trials are constantly evolving in the context of increasingly complex research questions and potentially limited resources. In this review article, we discuss the emergence of "adaptive" clinical trials that allow for the preplanned modification of an ongoing clinical trial based on the accumulating evidence with application across translational research. These modifications may include terminating a trial before completion due to futility or efficacy, re-estimating the needed sample size to ensure adequate power, enriching the target population enrolled in the study, selecting across multiple treatment arms, revising allocation ratios used for randomization, or selecting the most appropriate endpoint. Emerging topics related to borrowing information from historic or supplemental data sources, sequential multiple assignment randomized trials (SMART), master protocol and seamless designs, and phase I dose-finding studies are also presented. Each design element includes a brief overview with an accompanying case study to illustrate the design method in practice. We close with brief discussions relating to the statistical considerations for these contemporary designs.

BACKGROUND:Patient-reported outcomes (PROs) capture patients' views on their health conditions and its management, and are increasingly used in clinical trials, including those targeting type 2 diabetes (T2D). Mobile health (mHealth) tools offer novel solutions for collecting PRO data in real time. Although patients are at the center of any PRO-based intervention, few studies have examined user engagement with PRO mHealth tools. OBJECTIVE:This study aimed to evaluate user engagement with a PRO mHealth tool for T2D management, identify patterns of user engagement and similarities and differences between the patients, and identify the characteristics of patients who are likely to drop out or be less engaged with a PRO mHealth tool. METHODS:We extracted user engagement data from an ongoing clinical trial that tested the efficacy of a PRO mHealth tool designed to improve hemoglobin A1c levels in patients with uncontrolled T2D. To date, 61 patients have been randomized to the intervention, where they are sent 6 PRO text messages a day that are relevant to T2D self-management (healthy eating and medication adherence) over the 12-month study. To analyze user engagement, we first compared the response rate (RR) and response time between patients who completed the 12-month intervention and those who dropped out early (noncompleters). Next, we leveraged latent class trajectory modeling to classify patients from the completer group into 3 subgroups based on similarity in the longitudinal engagement data. Finally, we investigated the differences between the subgroups of completers from various cross-sections (time of the day and day of the week) and PRO types. We also explored the patient demographics and their distribution among the subgroups. RESULTS:Overall, 19 noncompleters had a lower RR to PRO questions and took longer to respond to PRO questions than 42 completers. Among completers, the longitudinal RRs demonstrated differences in engagement patterns over time. The completers with the lowest engagement showed peak engagement during month 5, almost at the midstage of the program. The remaining subgroups showed peak engagement at the beginning of the intervention, followed by either a steady decline or sustained high engagement. Comparisons of the demographic characteristics showed significant differences between the high engaged and low engaged subgroups. The high engaged completers were predominantly older, of Hispanic descent, bilingual, and had a graduate degree. In comparison, the low engaged subgroup was composed mostly of African American patients who reported the lowest annual income, with one of every 3 patients earning less than US $20,000 annually. CONCLUSIONS:There are discernible engagement phenotypes based on individual PRO responses, and their patterns vary in the timing of peak engagement and demographics. Future studies could use these findings to predict engagement categories and tailor interventions to promote longitudinal engagement. TRIAL REGISTRATION/BACKGROUND:Clinicaltrials.gov NCT03652389; https://clinicaltrials.gov/ct2/show/NCT03652389. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)/UNASSIGNED:RR2-10.2196/18554.

BACKGROUND:The integration of behavioral economics (BE) principles and electronic health records (EHRs) using clinical decision support (CDS) tools is a novel approach to improving health outcomes. Meanwhile, the American Geriatrics Society has created the Choosing Wisely (CW) initiative to promote less aggressive glycemic targets and reduction in pharmacologic therapy in older adults with type 2 diabetes mellitus. To date, few studies have shown the effectiveness of combined BE and EHR approaches for managing chronic conditions, and none have addressed guideline-driven deprescribing specifically in type 2 diabetes. We previously conducted a pilot study aimed at promoting appropriate CW guideline adherence using BE nudges and EHRs embedded within CDS tools at 5 clinics within the New York University Langone Health (NYULH) system. The BE-EHR module intervention was tested for usability, adoption, and early effectiveness. Preliminary results suggested a modest improvement of 5.1% in CW compliance. OBJECTIVE:This paper presents the protocol for a study that will investigate the effectiveness of a BE-EHR module intervention that leverages BE nudges with EHR technology and CDS tools to reduce overtreatment of type 2 diabetes in adults aged 76 years and older, per the CW guideline. METHODS:A pragmatic, investigator-blind, cluster randomized controlled trial was designed to evaluate the BE-EHR module. A total of 66 NYULH clinics will be randomized 1:1 to receive for 18 months either (1) a 6-component BE-EHR module intervention + standard care within the NYULH EHR, or (2) standard care only. The intervention will be administered to clinicians during any patient encounter (eg, in person, telemedicine, medication refill, etc). The primary outcome will be patient-level CW compliance. Secondary outcomes will measure the frequency of intervention component firings within the NYULH EHR, and provider utilization and interaction with the BE-EHR module components. RESULTS:Study recruitment commenced on December 7, 2020, with the activation of all 6 BE-EHR components in the NYULH EHR. CONCLUSIONS:This study will test the effectiveness of a previously developed, iteratively refined, user-tested, and pilot-tested BE-EHR module aimed at providing appropriate diabetes care to elderly adults, compared to usual care via a cluster randomized controlled trial. This innovative research will be the first pragmatic randomized controlled trial to use BE principles embedded within the EHR and delivered using CDS tools to specifically promote CW guideline adherence in type 2 diabetes. The study will also collect valuable information on clinician workflow and interaction with the BE-EHR module, guiding future research in optimizing the timely delivery of BE nudges within CDS tools. This work will address the effectiveness of BE-inspired interventions in diabetes and chronic disease management. TRIAL REGISTRATION/BACKGROUND:ClinicalTrials.gov NCT04181307; https://clinicaltrials.gov/ct2/show/NCT04181307. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)/UNASSIGNED:DERR1-10.2196/28723.

OBJECTIVES/OBJECTIVE:To determine if the Integrated Community-Based Health Systems-Strengthening (ICBHSS) initiative was effective in expanding health coverage, improving care quality, and reducing child mortality in Togo. METHODS:Population-representative cross-sectional household surveys adapted from the Demographic Household Survey and Multiple Indicator Cluster Surveys were conducted at baseline (2015) and then annually (2016-2020) in 4 ICBHSS catchment sites in Kara, Togo. The primary outcome was under-5 mortality, with health service coverage and health-seeking behavior as secondary outcomes. Costing analyses were calculated by using "top-down" methodology with audited financial statements and programmatic data. RESULTS:There were 10 022 household surveys completed from 2015 to 2020. At baseline (2015), under-5 mortality was 51.1 per 1000 live births (95% confidence interval [CI]: 35.5-66.8), and at the study end period (2020), under-5 mortality was 35.8 (95% CI: 23.4-48.2). From 2015 to 2020, home-based treatment by a community health worker increased from 24.1% (95% CI: 21.9%-26.4%) to 45.7% (95% CI: 43.3%-48.2%), and respondents reporting prenatal care in the first trimester likewise increased (37.5% to 50.1%). Among respondents who sought care for a child with fever, presenting for care within 1 day increased from 51.9% (95% CI: 47.1%-56.6%) in 2015 to 80.3% (95% CI: 74.6%-85.0%) in 2020. The estimated annual additional intervention cost was $8.84 per person. CONCLUSIONS:Our findings suggest that the ICBHSS initiative, a bundle of evidence-based interventions implemented with a community-based strategy, improves care access and quality and was associated with reduction in child mortality.

Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) poses a public health threat for which preventive and therapeutic agents are urgently needed. Neutralizing antibodies are a key class of therapeutics which may bridge widespread vaccination campaigns and offer a treatment solution in populations less responsive to vaccination. Herein, we report that high-throughput microfluidic screening of antigen-specific B-cells led to the identification of LY-CoV555 (also known as bamlanivimab), a potent anti-spike neutralizing antibody from a hospitalized, convalescent patient with coronavirus disease 2019 (COVID-19). Biochemical, structural, and functional characterization of LY-CoV555 revealed high-affinity binding to the receptor-binding domain, angiotensin converting enzyme 2 binding inhibition, and potent neutralizing activity. A pharmacokinetic study of LY-CoV555 conducted in cynomolgus monkeys demonstrated a mean half-life of 13 days, and clearance of 0.22 mL/hr/kg, consistent with a typical human therapeutic antibody. In a rhesus macaque challenge model, prophylactic doses as low as 2.5 mg/kg reduced viral replication in the upper and lower respiratory tract in samples collected through study Day 6 following viral inoculation. This antibody has entered clinical testing and is being evaluated across a spectrum of COVID-19 indications, including prevention and treatment.