Faculty Bibliography

Importance/UNASSIGNED:Many older survivors of acute myocardial infarction (AMI) experience functional decline, an outcome of primary importance to older adults. Mobility impairment has been proposed as a risk factor for functional decline but has not been evaluated to date in older patients hospitalized for AMI. Objective/UNASSIGNED:To examine the association of mobility impairment, measured during hospitalization, as a risk marker for functional decline among older patients with AMI. Design, Setting, and Participants/UNASSIGNED:Prospective cohort study among 94 academic and community hospitals in the United States. Participants were 2587 hospitalized patients with AMI who were 75 years or older. The study dates were January 2013 to June 2017. Main Outcomes and Measures/UNASSIGNED:Mobility was evaluated during AMI hospitalization using the Timed "Up and Go," with scores categorized as preserved mobility (≤15 seconds to complete), mild impairment (>15 to ≤25 seconds to complete), moderate impairment (>25 seconds to complete), and severe impairment (unable to complete). Self-reported function in activities of daily living (ADLs) (bathing, dressing, transferring, and walking around the home) and walking 0.4 km (one-quarter mile) was assessed at baseline and 6 months after discharge. The primary outcomes were worsening of 1 or more ADLs and loss of ability to walk 0.4 km from baseline to 6 months after discharge. The association between mobility impairment and risk of functional decline was evaluated with multivariable-adjusted logistic regression. Results/UNASSIGNED:Among 2587 hospitalized patients with AMI, the mean (SD) age was 81.4 (4.8) years, and 1462 (56.5%) were male. More than half of the cohort exhibited mobility impairment during AMI hospitalization (21.8% [564 of 2587] had mild impairment, 16.0% [414 of 2587] had moderate impairment, and 15.2% [391 of 2587] had severe impairment); 12.8% (332 of 2587) reported ADL decline, and 16.7% (431 of 2587) reported decline in 0.4-km mobility. Only 3.8% (30 of 800) of participants with preserved mobility experienced any ADL decline compared with 6.9% (39 of 564) of participants with mild impairment (adjusted odds ratio [aOR], 1.24; 95% CI, 0.74-2.09), 18.6% (77 of 414) of participants with moderate impairment (aOR, 2.67; 95% CI, 1.67-4.27), and 34.7% (136 of 391) of participants with severe impairment (aOR, 5.45; 95% CI, 3.29-9.01). Eleven percent (90 of 800) of participants with preserved mobility declined in ability to walk 0.4 km compared with 15.2% (85 of 558) of participants with mild impairment (aOR, 1.51; 95% CI, 1.04-2.20), 19.0% (78 of 411) of participants with moderate impairment (aOR, 2.03; 95% CI, 1.37-3.02), and 24.6% (95 of 386) of participants with severe impairment (aOR, 3.25; 95% CI, 2.02-5.23). Conclusions and Relevance/UNASSIGNED:This study's findings suggest that mobility impairment assessed during hospitalization may be a potent risk marker for functional decline in older survivors of AMI. These findings also suggest that brief, validated assessments of mobility should be part of the care of older hospitalized patients with AMI to identify those at risk for this important patient-centered outcome.

Importance/UNASSIGNED:Air pollutants interact with estrogen nuclear receptors, but their effect on thyroid signaling is less clear. Thyroid function is of particular importance for pregnant women because of the thyroid's role in fetal brain development. Objective/UNASSIGNED:To determine the short-term association of exposure to air pollution in the first trimester with thyroid function throughout pregnancy. Design, Setting, and Participants/UNASSIGNED:In this cohort study, 9931 pregnant women from 4 European cohorts (the Amsterdam Born Children and Their Development Study, the Generation R Study, Infancia y Medio Ambiente, and Rhea) and 1 US cohort (Project Viva) with data on air pollution exposure and thyroid function during pregnancy were included. The recruitment period for the Amsterdam Born Children and Their Development Study was January 2003 to March 2004; for Generation R, April 2002 to January 2006; for Infancia y Medio Ambiente, November 2003 to January 2008; for Rhea, February 2007 to February 2008; and for Project Viva, April 1999 to November 2002. Statistical analyses were conducted from January 2018 to April 2019. Main Outcomes and Measures/UNASSIGNED:Residential air pollution concentrations (ie, nitrogen oxide and particulate matter [PM]) during the first trimester of pregnancy were estimated using land-use regression and satellite-derived aerosol optical depth models. Free thyroxine, thyrotropin, and thyroid peroxidase antibody levels were measured across gestation. Hypothyroxinemia was defined as free thyroxine below the fifth percentile of the cohort distribution with normal thyrotropin levels, following the American Thyroid Association guidelines. Results/UNASSIGNED:Among 9931 participants, the mean (SD) age was 31.2 (4.8) years, 4853 (48.9%) had more than secondary educational levels, 5616 (56.6%) were nulliparous, 404 (4.2%) had hypothyroxinemia, and 506 (6.7%) tested positive for thyroid peroxidase antibodies. Concentrations of nitrogen dioxide and PM with an aerodynamic diameter of 2.5 μm or less (PM2.5) were lower and had less variation in women in the US cohort than those in European cohorts. No associations of nitrogen oxide with thyroid function were found. Higher exposures to PM2.5 were associated with higher odds of hypothyroxinemia in pregnant women (odds ratio per 5-μg/m3 change, 1.21; 95% CI, 1.00-1.47). Although exposure to PM with an aerodynamic diameter of 10 μm or less was not significantly associated with hypothyroxinemia, the coefficient was similar to that for the association of PM2.5 with hypothyroxinemia (odds ratio per 10-μg/m3 change, 1.18; 95% CI, 0.93-1.48). Absorbances of PM2.5 and PM with aerodynamic diameter from 2.5 to 10 μg and were not associated with hypothyroxinemia. There was substantial heterogeneity among cohorts with respect to thyroid peroxidase antibodies (P for heterogeneity, <.001), showing associations of nitrogen oxide and PM with thyroid autoimmunity only in the women in the Generation R Study. Conclusions and Relevance/UNASSIGNED:The findings of this study suggest that first-trimester exposures to PM2.5 were associated with mild thyroid dysfunction throughout pregnancy. The association of PM2.5 exposure with thyroid function during pregnancy is of global health importance because air pollution exposure is widespread and hypothyroxinemia may adversely influence the brain development of offspring.

Context/UNASSIGNED:Dipeptidyl peptidase 4 (DPP4) inhibitors may increase the risk of heart failure. Decreased degradation of vasoactive peptides like substance P [also degraded by angiotensin-converting enzyme (ACE)] and Y1 agonists peptide YY (PYY 1-36) and neuropeptide Y (NPY 1-36) could contribute. Objective/UNASSIGNED:This study tested the hypothesis that there is an interactive effect of DPP4 inhibition and ACE inhibition (vs antihypertensive control subjects) on vasoactive peptides after a mixed meal. Participants and Design/UNASSIGNED:Fifty-three patients with type 2 diabetes and hypertension were randomized to double-blind treatment with ramipril, valsartan, or amlodipine for 15 weeks in parallel groups. During the 5th, 10th, and 15th weeks, participants also received placebo + placebo, sitagliptin 100 mg/d + placebo, and sitagliptin + aprepitant 80 mg/d in random order. On the last day of each crossover treatment, participants underwent a mixed-meal study. Results/UNASSIGNED:Sitagliptin increased postprandial glucagon-like peptide-1 and decreased glucose in all antihypertensive groups. Sitagliptin increased NPY 1-36 and decreased Y2 agonists NPY 3-36 and PYY 3-36 in all groups. During ramipril or valsartan, but not amlodipine, sitagliptin increased postprandial norepinephrine; substance P receptor blockade with aprepitant prevented this effect. Despite increased norepinephrine, sitagliptin decreased postprandial blood pressure during ACE inhibition. Conclusion/UNASSIGNED:DPP4 inhibition increases postprandial concentrations of the Y1 agonist NPY 1-36. During treatment with an ACE inhibitor or angiotensin receptor blocker, DPP4 inhibition increased postprandial norepinephrine through a substance P receptor-dependent mechanism. Increased NPY 1-36 and norepinephrine could increase risk of heart failure but did not result in higher postprandial blood pressure.

BACKGROUND:Few studies have documented patient attitudes and experiences with extended-release naltrexone (XR-NTX) opioid relapse prevention in criminal justice settings. This study assessed barriers and facilitators of jail-to-community reentry among adults with opioid use disorder (OUD) treated with XR-NTX, buprenorphine, methadone, and no medications. METHODS:This qualitative study conducted individual interviews with a purposeful and convenience sample of adults with OUD who were recently released from NYC jails. XR-NTX, no medication, and methadone participants were concurrently enrolled in a large randomized controlled trial evaluating XR-NTX vs. a no medication Enhanced Treatment As Usual (ETAU) condition, or enrolled in a non-randomized quasi-experimental methadone maintenance cohort. Buprenorphine participants were referred from NYC jails to a public hospital office-based buprenorphine program and not enrolled in the parent trial. Interviews were audio recorded, transcribed, independently coded by two researchers, and analyzed per a grounded theory approach adapted to the Social Cognitive Theory framework. The research team reviewed transcripts and coding to reach consensus on emergent themes. RESULTS:N = 33 adults with OUD (28 male, 5 female) completed a single individual interview. Purposeful sampling recruited persons leaving jail on XR-NTX (n = 11), no active medication treatment (n = 9), methadone (n = 9), and buprenorphine (n = 4). Emergent themes were: (1) general satisfaction with XR-NTX's long-acting antagonist effects and control of cravings; (2) "testing" XR-NTX's blockade with heroin upon reentry was common; (3) early discontinuation of XR-NTX treatment was most common among persons with high self-efficacy and/or heavy exposure to drug use environments and peers; (4) similar satisfaction regarding effects of methadone and buprenorphine maintenance among retained-in-treatment individuals, alongside general dissatisfaction with daily observed dosing requirements and misinformation and stigmas regarding methadone adverse effects; (5) unstable housing, economic insecurity, and exposure to actively using peers were attributed to early termination of treatment and relapse; (6) individual motivation and willpower as central to long-term opioid abstinence and reentry success. CONCLUSIONS:In the context of more familiar agonist maintenance treatments, XR-NTX relapse prevention during jail-to-community reentry was viewed as a helpful and unique intervention though with important limitations. Commonly described barriers to treatment retention and heroin abstinence included homelessness, economic insecurity, and drug-using peers. Trial registration ClinicalTrials.gov, NCT01999946 (XOR), Registered 03 December 2013, https://clinicaltrials.gov/ct2/show/NCT01999946 .

OBJECTIVE:To investigate pathways by which interventions that promote shared reading and play help prevent child behavior problems. We examined whether family processes associated with the family investment pathway (eg, parental cognitive stimulation) and the family stress pathway (eg, mothers' psychosocial functioning) mediated impacts of a pediatric-based preventive intervention on child behavior. STUDY DESIGN/METHODS:The sample included 362 low-income mothers and their children who participated in a randomized controlled trial of the Video Interaction Project, a pediatrics-based preventive intervention that promotes parent-child interactions in the context of shared reading and play. Parent-child dyads were randomly assigned to group at birth. Three mediators-parental cognitive stimulation, maternal stress about the parent-child relationship, and maternal depressive symptoms-were assessed at child ages 6 and 36 months. The outcome, child externalizing behaviors, was assessed at 36 months. We used a series of path analytic models to examine how these family processes, separately or together, mediated the impacts of the Video Interaction Project on child behavioral outcomes. RESULTS:Intervention impacts on child behavior were mediated by enhancements in cognitive stimulation and by improvements in mothers' psychosocial functioning. A sequential mediation model showed that Video Interaction Project impacts on cognitive stimulation at 6 months were associated with later decreases in mothers' stress about the parent-child relationship and that this pathway mediated intervention impacts on child behavioral outcomes at 3 years of age (P = .023). CONCLUSIONS:Using an experimental design, this study identifies pathways by which parent-child interactions in shared reading and play can improve child behavioral outcomes. TRIAL REGISTRATION/BACKGROUND:Clinicaltrials.gov: NCT00212576.

Introduction: The decision of admitting a stable patient to the ICU after major operation currently relies on clinical judgment and local hospital policies. We programmed an artificial intelligence (AI) to determine the appropriate level of care after major operation and compared its performance with clinician's judgement.
Method(s): ICU admission was deemed "appropriate" when at least 1 of 15 criteria (eg re-intubation, prolonged hypotension, new-onset arrhythmia) was observed. Using Institutional data (512 patients, 87 clinical variables), we programmed an AI to predict when ICU admission would have been appropriate. We prospectively evaluated whether surgeon, anesthesiologist, intensivist, or AI was the most accurate predictor in determining appropriateness of ICU admissions across 50 patients undergoing major surgery (general, vascular, urological). Accuracy of predictions was compared using receiver operating characteristic curve analysis.
Result(s): ICU care was appropriate (at least 1 of 15 objective criteria met) in 9 of 50 patients. Artificial intelligence correctly triaged to the appropriate level of care 82% of patients (surgeon 70%, anesthesiologist 58%, intensivist 64%). Receiver operating characteristic curve analysis revealed that AI's triage was the most accurate (area under the curve [AUC] 0.82), followed by anesthesiologist's (AUC 0.70), intensivist's (AUC 0.69), and surgeon's (AUC 0.60). Overall, clinicians leaned toward over-triaging patients to the ICU (Table).
Conclusion(s): Our study provides the first evidence that AI can have a role in supporting clinical decisions on postoperative triage. In the future, more sophisticated platforms can become integrated in daily clinical practice. [Figure presented]
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Introduction: The Strengthening Referral Networks for Management of Hypertension Across the Health System (STRENGTHS) trial is creating and testing interventions to improve the effectiveness of referral networks for patients with hypertension in Western Kenya.
Purpose(s): Network analysis of facility-based healthcare providers was used to understand the existing network of referrals. The ultimate goal was to identify both structural gaps and opportunities for implementation of the planned intervention.
Method(s): A network survey was administered to providers who deliver care to patients with hypertension asking individuals to nominate a) individuals to whom, and b) facilities to which they refer patients, both up and down the health system. We analyzed survey data using centrality measures of in-degree and out-degree (number of links each provider received and sent, respectively), as well as fitting a core-periphery (CP) model. A higher CP indicates a strong referral network, while a lower CP indicates a relatively weaker network.
Result(s): Data were collected from 130 providers across 39 sites within 7 geographically separate network clusters. Each cluster consists of a mix of primary, secondary, and/or tertiary facilities. Compared to a perfect CP referral network model (Correlation Score [CP] = 1.00) and a random referral network model (CP = 0.200), the provider referral networks within each cluster showed a weak tendency for CP structure. There was a large range in CP from 0.334 to 0.639. In contrast, cluster-level facility networks showed a strong tendency for CP structure, with a CP range of 0.857 to 0.949.
Conclusion(s): The current health system across Western Kenya does not demonstrate a strong network of referrals between providers for patients with hypertension. While facility-to-facility referrals are more in-line with a perfect referral model, there are gaps in communication between the specific providers. These results highlight the need for STRENGTHS to design and test interventions that strengthen provider referral patterns in order to improve blood pressure control and reduce cardiovascular risk

Objectives: Digital innovation has the potential to transform both the science and practice of child mental health. Creation of pediatric digital health tools requires that bioethics, human-centered design, and clinical and scientific expertise are integrated with digital tool development, digital data collection, and data analytics. In this talk, we will describe the opportunities for innovations in pediatric digital mental health and the concurrent ethical and security risks. We will then present a framework and design methodology for creating ethical, human-centered, clinically informed, and evidence-based digital tools for children's mental health.
Method(s): The data presented will come from our experience founding and leading the New York University Langone Department of Child and Adolescent Psychiatry's WonderLab, which creates pediatric digital mental health tools that are evidence based, scalable, and ethical, as well as beautiful and fun so that parents and children would want to use them. The WonderLab brings clinical, scientific, digital engineering, digital design, data science, and bioethics expertise together with user engagement and a "build, measure, learn" agile development culture and methodology. We will use the WonderLab team's development and launch of our first app-based study, "When to Wonder: Picky Eating," to illustrate our framework and methodology.
Result(s): We will describe the innovation opportunities in pediatric digital mental health, including innovation in measurement, engagement, access, and collaborative methodologies. We will then present the ethical, privacy, security, and safety risks related to digital health applications and app-based data collection with children and their families. Finally, we will describe how the WonderLab team, methodology, and products innovate across multiple domains within an explicit ethical and clinically informed framework.
Conclusion(s): Digital innovation and data science have great potential to address the challenges facing our patients and our field. To build ethical and useful digital health tools for children's mental health requires multidisciplinary teams, user engagement, collaborative agile methodology, and a framework that ensures that innovations are integrated with and reflect our ethics and commitment to children. R, COMP, DAM
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Air quality data from satellites and low-cost sensor systems, together with output from air quality models, have the potential to augment high-quality, regulatory-grade data in countries with in situ monitoring networks and provide much-needed air quality information in countries without them. Each of these technologies has strengths and limitations that need to be considered when integrating them to develop a robust and diverse global air quality monitoring network. To address these issues, the American Thoracic Society, the U.S. Environmental Protection Agency, the National Aeronautics and Space Administration, and the National Institute of Environmental Health Sciences convened a workshop in May 2017 to bring together global experts from across multiple disciplines and agencies to discuss current and near-term capabilities to monitor global air pollution. The participants focused on four topics: 1) current and near-term capabilities in air pollution monitoring, 2) data assimilation from multiple technology platforms, 3) critical issues for air pollution monitoring in regions without a regulatory-quality stationary monitoring network, and 4) risk communication and health messaging. Recommendations for research and improved use were identified during the workshop, including a recognition that the integration of data across monitoring technology groups is critical to maximizing the effectiveness (e.g., data accuracy, as well as spatial and temporal coverage) of these monitoring technologies. Taken together, these recommendations will advance the development of a global air quality monitoring network that takes advantage of emerging technologies to ensure the availability of free, accessible, and reliable air pollution data and forecasts to health professionals, as well as to all global citizens.