Influencing basic behavioral mechanisms of action while targeting daily walking in sedentary adults at risk for cardiovascular disease: randomised factorial design protocol.

Introduction: Cardiovascular disease (CVD) is the leading cause of mortality worldwide, though it may be prevented by increasing physical activity (PA). When behaviour change techniques (BCTs) are bundled together, they increase PA, though which individual BCTs increase PA (and the behavioural mechanism of action (MoA) responsible for said increase) have not been studied. The aim of this study is to conduct a randomised factorial experiment to determine which of four BCTs significantly engage the proposed MoA-self-efficacy for PA-in adults at risk for CVD.

Monotone response surface of multi-factor condition: estimation and Bayes classifiers.

We formulate the estimation of monotone response surface of multiple factors as the inverse of an iteration of partially ordered classifier ensembles. Each ensemble (called PIPE-classifiers) is a projection of Bayes classifiers on the constrained space. We prove the inverse of PIPE-classifiers (iPIPE) exists, and propose algorithms to efficiently compute iPIPE by reducing the space over which optimisation is conducted.

The effect of a multi-component behavior change technique intervention on medication adherence among individuals on primary prevention statin therapy: a dose-finding protocol.

Background: In the USA, the primary cause of death and morbidity continues to be cardiovascular disease (CVD). Numerous trials have shown that statin medication reduces the likelihood of CVD events; it is a cornerstone of CVD prevention. However, studies have also indicated that up to 60% of the estimated 26.

A Series of Remote Melatonin Supplement Interventions for Poor Sleep: Protocol for a Feasibility Pilot Study for a Series of Personalized (N-of-1) Trials.

Background: Poor sleep, defined as short-duration or poor-quality sleep, is a frequently reported condition with many deleterious effects including poorer cognitive functioning, increased accidents, and poorer health. Melatonin has been shown to be an efficacious treatment to manage symptoms of poor sleep. However, the treatment effects of melatonin on sleep can vary greatly between participants.

Analysis of N-of-1 trials using Bayesian distributed lag model with autocorrelated errors.

An N-of-1 trial is a multi-period crossover trial performed in a single individual, with a primary goal to estimate treatment effect on the individual instead of population-level mean responses. As in a conventional crossover trial, it is critical to understand carryover effects of the treatment in an N-of-1 trial, especially when no washout periods between treatment periods are instituted to reduce trial duration. To deal with this issue in situations where a high volume of measurements are made during the study, we introduce a novel Bayesian distributed lag model that facilitates the estimation of carryover effects, while accounting for temporal correlations using an autoregressive model.

Breaking Up Prolonged Sitting to Improve Cardiometabolic Risk: Dose-Response Analysis of a Randomized Crossover Trial.

Purpose: Sedentary time is ubiquitous in developed nations and is associated with deleterious health outcomes. Physical activity guidelines recommend reductions in sedentary time; however, quantitative guidelines that inform how often and how long sedentary time should be interrupted have not been provided. The purpose of this study was to examine the acute effects of multiple doses of a sedentary break intervention on cardiometabolic risk factors, concurrently evaluating efficacy of varying frequencies and durations of sedentary breaks.

Genome-wide association study of executive function in a multi-ethnic cohort implicates LINC01362: Results from the northern Manhattan study.

Executive function is a cognitive domain with sizable heritability representing higher-order cognitive abilities. Genome-wide association studies (GWAS) of executive function are sparse, particularly in populations underrepresented in medical research. We performed a GWAS on a composite measure of executive function that included measures of mental flexibility and reasoning using data from the Northern Manhattan Study, a racially and ethnically diverse cohort (N = 1077, 69% Hispanic, 17% non-Hispanic Black and 14% non-Hispanic White).

Physical Activity Is Inversely Associated With Severe Intracranial Stenosis in Stroke-Free Participants of NOMAS.

Background: Although protective in secondary stroke prevention of intracranial arterial stenosis (ICAS), it is uncertain if the benefits of leisure time physical activity (LTPA) extend to asymptomatic ICAS or extracranial carotid stenosis (ECAS). Therefore, we sought to determine LTPA's relationship with ECAS and ICAS in a stroke-free, race-ethnically diverse cohort.

Methods: This cross-sectional study included participants from the magnetic resonance imaging substudy of the Northern Manhattan Study, of whom 1274 had LTPA assessments at enrollment.

STATISTICAL INFERENCE IN QUANTILE REGRESSION FOR ZERO-INFLATED OUTCOMES.

An extension of quantile regression is proposed to model zero-inflated outcomes, which have become increasingly common in biomedical studies. The method is flexible enough to depict complex and nonlinear associations between the covariates and the quantiles of the outcome. We establish the theoretical properties of the estimated quantiles, and develop inference tools to assess the quantile effects.

Integrating non-concurrent controls in the analyses of late-entry experimental arms in multi-arm trials with a shared control group in the presence of parameter drift.

Background: Under a master protocol, open platform trials allow new experimental treatments to enter an existing clinical trial. Whether late-entry experimental treatments should be compared to all available or concurrently randomized controls is not well established. Using all available data can increase power and precision; however, drift in population parameters can yield biased estimates and impact type I error rate.

Series of virtual light therapy interventions for fatigue: a feasibility pilot study protocol for a series of personalised (N-of-1) trials.

Introduction: Fatigue is one of the most commonly recorded patient symptoms that can result in deficits in aspects of psychomotor functioning, cognition, work performance and mood. Research shows that bright light and dim light therapy may be an efficacious way to reduce symptoms of fatigue. Still, the feasibility, scalability, individual treatment effects and adverse event heterogeneity of these treatments are unknown.

A NOVEL FRAMEWORK TO ESTIMATE MULTIDIMENSIONAL MINIMUM EFFECTIVE DOSES USING ASYMMETRIC POSTERIOR GAIN AND -TAPERING.

In this article we address the problem of estimating minimum effective doses in dose-finding clinical trials of multidimensional treatment. We are motivated by a behavioral intervention trial where we introduce sedentary breaks to subjects with a goal to reduce their glucose level monitored over 8 hours. Each sedentary break regimen is defined by two elements: break frequency and break duration.

TASC (Telehealth After Stroke Care): a study protocol for a randomized controlled feasibility trial of telehealth-enabled multidisciplinary stroke care in an underserved urban setting.

Background: Hypertension is the most important modifiable risk factor for recurrent stroke, and blood pressure (BP) reduction is associated with decreased risk of stroke recurrence. However, hypertension remains poorly controlled in many stroke survivors. Black and Hispanic patients have a higher prevalence of uncontrolled BP and higher rates of stroke.

Introducing Data Sciences to N-of-1 Designs, Statistics, Use-Cases, the Future, and the Moniker 'N-of-1' Trial.

This article, an introduction to 's "Personalized (N-of-1) Trials: Methods, Applications, and Impact" special issue, describes the rationale for a primer of the methods, data types and management, designs, and use cases for personalized (N-of-1) trials. It explains that the design and implementation of personalized (N-of-1) trials is only useful if patients volunteer for research involving them and actively participate in clinical services that use them. However, 'N-of-1 trials' may be an inadequate name to enact such patient engagement.

Personalized Policy Learning using Longitudinal Mobile Health Data.

Personalized policy represents a paradigm shift from one-decision-rule-for-all users to an individualized decision rule for each user. Developing personalized policy in mobile health applications imposes challenges. First, for lack of adherence, data from each user are limited.

Gut permeability and cognitive decline: A pilot investigation in the Northern Manhattan Study.

Background: Gut microbiota may impact cognitive function and decline, though data are limited. This pilot study examines the associations between gut dysbiosis products, plasma lipopolysaccharide (LPS) and soluble CD14 (sCD14), with cognitive decline and immune molecule activation among 40 participants in the longitudinal population-based Northern Manhattan Study.

Methods: We selected stroke- and dementia-free participants at baseline with high activation levels of core components of the immune signaling pathways underlying microbiota metabolite-cognitive associations (IL-1, IL-17, TNF).

Systolic Blood Pressure and Cognition in the Elderly: The Northern Manhattan Study.

Background: Increasing evidence suggests that hypertension is a risk factor for cognitive impairment and dementia. The relationship between blood pressure and cognition in a racially and ethnically diverse population remains unclear.

Objective: To study association of blood pressure with cognition cross-sectionally and longitudinally in the elderly.

Clinical comparison between trial participants and potentially eligible patients using electronic health record data: A generalizability assessment method.

Objective: To present a generalizability assessment method that compares baseline clinical characteristics of trial participants (TP) to potentially eligible (PE) patients as presented in their electronic health record (EHR) data while controlling for clinical setting and recruitment period.

Methods: For each clinical trial, a clinical event was defined to identify patients of interest using available EHR data from one clinical setting during the trial's recruitment timeframe. The trial's eligibility criteria were then applied and patients were separated into two mutually exclusive groups: (1) TP, which were patients that participated in the trial per trial enrollment data; (2) PE, the remaining patients.

A randomized double-blind controlled trial of convalescent plasma in adults with severe COVID-19.

BACKGROUNDAlthough convalescent plasma has been widely used to treat severe coronavirus disease 2019 (COVID-19), data from randomized controlled trials that support its efficacy are limited.METHODSWe conducted a randomized, double-blind, controlled trial among adults hospitalized with severe and critical COVID-19 at 5 sites in New York City (USA) and Rio de Janeiro (Brazil). Patients were randomized 2:1 to receive a single transfusion of either convalescent plasma or normal control plasma.

Comparison of Clinical Characteristics Between Clinical Trial Participants and Nonparticipants Using Electronic Health Record Data.

Importance: Assessing generalizability of clinical trials is important to ensure appropriate application of interventions, but most assessments provide minimal granularity on comparisons of clinical characteristics.

Objective: To assess the extent of underlying clinical differences between clinical trial participants and nonparticipants by using a combination of electronic health record and trial enrollment data.

Design, Setting, And Participants: This cross-sectional study used data obtained from a single academic medical center between September 1996 and January 2019 to identify 1645 clinical trial participants from a diverse set of 202 available trials conducted at the center.

Race/Ethnic Disparities in Mild Cognitive Impairment and Dementia: The Northern Manhattan Study.

Background: Variability in dementia rates across racial and ethnic groups has been estimated at 60%. Studies suggest disparities in Caribbean Hispanic and Black populations, but community-based data are limited.

Objective: Estimate the prevalence of mild cognitive impairment (MCI) and dementia in the racially and ethnically diverse community-based Northern Manhattan Study cohort and examine sociodemographic, vascular risk factor, and brain imaging correlates.