Generalized single index modeling of longitudinal data with multiple binary responses.

In health and clinical research, medical indices (eg, BMI) are commonly used for monitoring and/or predicting health outcomes of interest. While single-index modeling can be used to construct such indices, methods to use single-index models for analyzing longitudinal data with multiple correlated binary responses are underdeveloped, although there are abundant applications with such data (eg, prediction of multiple medical conditions based on longitudinally observed disease risk factors). This article aims to fill the gap by proposing a generalized single-index model that can incorporate multiple single indices and mixed effects for describing observed longitudinal data of multiple binary responses.

Comparing two hazard curves when there is a treatment time-lag effect.

In cancer and other medical studies, time-to-event (eg, death) data are common. One major task to analyze time-to-event (or survival) data is usually to compare two medical interventions (eg, a treatment and a control) regarding their effect on patients' hazard to have the event in concern. In such cases, we need to compare two hazard curves of the two related patient groups.

Multiblock partial least squares and rank aggregation: Applications to detection of bacteriophages associated with antimicrobial resistance in the presence of potential confounding factors.

Urban environments, characterized by bustling mass transit systems and high population density, host a complex web of microorganisms that impact microbial interactions. These urban microbiomes, influenced by diverse demographics and constant human movement, are vital for understanding microbial dynamics. We explore urban metagenomics, utilizing an extensive dataset from the Metagenomics & Metadesign of Subways & Urban Biomes (MetaSUB) consortium, and investigate antimicrobial resistance (AMR) patterns.

Predicting high-risk periods for weight regain following initial weight loss.

Objective: The aim of this study was to develop a predictive algorithm of "high-risk" periods for weight regain after weight loss.

Methods: Longitudinal mixed-effects models and random forest regression were used to select predictors and develop an algorithm to predict weight regain on a week-to-week basis, using weekly questionnaire and self-monitoring data (including daily e-scale data) collected over 40 weeks from 46 adults who lost ≥5% of baseline weight during an initial 12-week intervention (Study 1). The algorithm was evaluated in 22 adults who completed the same Study 1 intervention but lost <5% of baseline weight and in 30 adults recruited for a separate 30-week study (Study 2).

Identification of shared biological features in four different lung cell lines infected with SARS-CoV-2 virus through RNA-seq analysis.

The COVID-19 pandemic caused by SARS-CoV-2 has resulted in millions of confirmed cases and deaths worldwide. Understanding the biological mechanisms of SARS-CoV-2 infection is crucial for the development of effective therapies. This study conducts differential expression (DE) analysis, pathway analysis, and differential network (DN) analysis on RNA-seq data of four lung cell lines, NHBE, A549, A549.

Multivariate single index modeling of longitudinal data with multiple responses.

In medical studies, composite indices and/or scores are routinely used for predicting medical conditions of patients. These indices are usually developed from observed data of certain disease risk factors, and it has been demonstrated in the literature that single index models can provide a powerful tool for this purpose. In practice, the observed data of disease risk factors are often longitudinal in the sense that they are collected at multiple time points for individual patients, and there are often multiple aspects of a patient's medical condition that are of our concern.

Comparing D3-Creatine Dilution and Dual-Energy X-ray Absorptiometry Muscle Mass Responses to Strength Training in Low-Functioning Older Adults.

Background: In contrast to dual-energy x-ray absorptiometry (DXA), the D3-creatine (D3Cr) dilution method provides a direct measure of skeletal muscle mass and in a cohort of older men has been strongly associated with health-related outcomes. However, sensitivity to detect changes in D3Cr-derived muscle mass due to an intervention is limited.

Methods: Twenty-one older adults (≥70 years) with low-to-moderate physical function were randomized to a 15-week high-intensity strength training (ST) or a health education (HE) group.

Analysis of US Household Catastrophic Health Care Expenditures Associated With Chronic Disease, 2008-2018.

This cross-sectional study evaluates trends in catastrophic health care expenditures associated with chronic diseases in US households from 2008 to 2018.

Impact of transition from face-to-face to telehealth on behavioral obesity treatment during the COVID-19 pandemic.

Objective: This study evaluated whether the transition of a face-to-face behavioral intervention to videoconferencing-based telehealth delivery during the COVID-19 pandemic resulted in significantly smaller weight losses than those typically observed in gold-standard, face-to-face programs.

Methods: Participants were 160 adults with obesity (mean [SD] age = 49.2 [11.

Non-parametric treatment time-lag effect estimation.

In general, the change point problem considers inference of a change in distribution for a set of time-ordered observations. This has applications in a large variety of fields, and can also apply to survival data. In survival analysis, most existing methods compare two treatment groups for the entirety of the study period.

Edge-Preserving Denoising of Image Sequences.

To monitor the Earth's surface, the satellite of the NASA Landsat program provides us image sequences of any region on the Earth constantly over time. These image sequences give us a unique resource to study the Earth's surface, changes of the Earth resource over time, and their implications in agriculture, geology, forestry, and more. Besides natural sciences, image sequences are also commonly used in functional magnetic resonance imaging (fMRI) of medical studies for understanding the functioning of brains and other organs.

Effective disease surveillance by using covariate information.

Effective surveillance of infectious diseases, cancers, and other deadly diseases is critically important for public health and safety of our society. Incidence data of such diseases are often collected spatially from different clinics and hospitals through a regional, national or global disease reporting system. In such a system, new batches of data keep being collected over time, and a decision needs to be made immediately after new data are collected regarding whether there is a disease outbreak at the current time point.

Joint modeling of multivariate nonparametric longitudinal data and survival data: A local smoothing approach.

In many clinical studies, evaluating the association between longitudinal and survival outcomes is of primary concern. For analyzing data from such studies, joint modeling of longitudinal and survival data becomes an appealing approach. In some applications, there are multiple longitudinal outcomes whose longitudinal pattern is difficult to describe by a parametric form.

Ratings of Perceived Exertion During Walking: Predicting Major Mobility Disability and Effect of Structured Physical Activity in Mobility-Limited Older Adults.

Background: This study evaluated the association between ratings of perceived exertion (RPE) of walking and major mobility disability (MMD), as well as their transitions in response to a physical activity (PA) compared to a health education (HE) program.

Methods: Older adults (n = 1633) who were at risk for mobility impairment were randomized to structured PA or HE programs. During a 400 m walk, participants rated exertion as "light" or "hard.

Innovations in Geroscience to enhance mobility in older adults.

Aging is the primary risk factor for functional decline; thus, understanding and preventing disability among older adults has emerged as an important public health challenge of the 21st century. The science of gerontology - or geroscience - has the practical purpose of "adding life to the years." The overall goal of geroscience is to increase healthspan, which refers to extending the portion of the lifespan in which the individual experiences enjoyment, satisfaction, and wellness.

Disparities in Pancreatic Ductal Adenocarcinoma-The Significance of Hispanic Ethnicity, Subgroup Analysis, and Treatment Facility on Clinical Outcomes.

Background: Disparities exist among patients with pancreatic ductal adenocarcinoma (PDAC). Non-White race is regarded as a negative predictor of expected treatment and overall survival. Data suggest that Academic Research Programs (ARP) provide better outcomes for minorities, but ethnic/minority outcomes are underreported.

Optimizing the Treatment of CRPS With Ketamine.

Objective: This study aimed to develop a method that objectively measures the clinical benefits of ketamine infusions to treat complex regional pain syndrome (CRPS), thus making it possible, for the first time, to determine the optimal dosing of ketamine and duration of treatment to treat CRPS.

Materials And Methods: All patients were diagnosed with hyperalgesia associated with CRPS. Patients underwent an outpatient, 4-day, escalating dose ketamine infusion.

Early detection of high disease activity in juvenile idiopathic arthritis by sequential monitoring of patients' health-related quality of life scores.

Juvenile idiopathic arthritis (JIA) is a chronic disease. During its "high disease activity (HDA)" stage, JIA can cause severe pain, and thus could seriously affect patients' physical and psychological health. Early detection of the HDA stage of JIA can reduce the damage of the disease by treating it at an early stage and alleviating the painful experience of the patients.

Association of Long-Term Dynamics in Circulating Testosterone with Serum PSA in Prostate Cancer-Free Men with Initial-PSA < 4 ng/mL.

We previously reported that an accelerated decline in circulating testosterone level is associated with a higher risk of prostate cancer (PCa). This study is to examine whether testosterone change rate is related to serum prostate-specific antigen (PSA) concentration among PCa-free men. Longitudinal data were derived from electronic medical records at a tertiary hospital in the Southeastern USA.

Week-to-week predictors of weight loss and regain.

Objectives: Despite increased interest in the development of individually tailored weight management programs, little is known about what factors proximally predict weight change.

Method: The current study investigated proximal (week-to-week) predictors of weight loss and regain in 74 adults during a 3-month, Internet-based behavioral weight loss program followed by a 9-month "maintenance" period (during which no additional intervention was provided). Participants were asked to self-weigh daily using scales that transmitted weight via the cellular network and to answer a brief questionnaire each week querying mood, behaviors, and cognitions hypothesized to be associated with weight loss and regain.

Nonparametric estimation of the spatio-temporal covariance structure.

Spatio-temporal modeling is an active research problem with broad applications. In this problem, proper description and estimation of the data covariance structure plays an important role. In the literature, most available methods assume that the data covariance is stationary and follows a specific parametric form.

Errors-in-variables jump regression using local clustering.

Errors-in-variables (EIV) regression is widely used in econometric models. The statistical analysis becomes challenging when the regression function is discontinuous and the distribution of measurement error is unknown. In the literature, most existing jump regression methods either assume that there is no measurement error involved or require that jumps are explicitly detected before the regression function can be estimated.

Objective Preoperative Parameters Predict Difficult Pelvic Dissections and Clinical Outcomes.

Background: Objective criteria to predict difficult pelvic dissection with prognostic significance are lacking. Previous studies have focused on predicting intraoperative conversion and not evaluated factors specific to pelvic surgery. We aimed to develop an objective, prognostic, preoperative assessment to predict difficult pelvic dissections and clinical outcomes.

Readmission After Elective Ileostomy in Colorectal Surgery Is Predictable.

Background And Objectives: Patients who undergo colorectal surgery have high postoperative morbidity, with ileostomates being the most disadvantaged. Recent studies assessing readmission risk factors do not provide a specific prediction model and, if so, do not focus on patients who have had colorectal surgery; thus, the results of these studies have limited applicability to our specialized practice. We wanted to develop a prediction model for readmission within 30 days of discharge after ileostomy creation.