Aims: This study sought to examine how perceived social support changes over time for U.S. veterans and how social support relates to their mental health longitudinally.
View Article and Find Full Text PDFBackground: This study investigated the association between prior incarceration length and edentulism among US adults 55 years and older. Analyses explored indirect factors such as wealth, smoking status, mental health, and chronic health conditions that may explain this relationship. In addition, the study analyzed how associations between incarceration and edentulism vary by race and ethnicity.
View Article and Find Full Text PDFTo provide a comprehensive examination of different types of social support and associations with mental health among U.S. military veterans, a group vulnerable to psychosocial dysfunction.
View Article and Find Full Text PDFIntroduction: Dental care is a critical component of healthy aging; however, emerging evidence suggests that having been previously incarcerated is a risk factor for not using dental care services. This study investigates the relationship between prior incarceration and dental care among older adults and assesses whether wealth and dental insurance explain this relationship.
Methods: Data are from the Health and Retirement Study, a nationally representative sample of community-dwelling older adults in the United States, collected in 2012 and 2014.
BACKGROUND: Delay time to hospital arrival may be influenced by lack of recognition of stroke signs and the necessity to seek emergency medical, which in turn is influenced by language barriers to, a modifiable risk factor, stroke awareness education. The objective was to determine the comprehension and satisfaction of a Spanish stroke awareness acronym, RÁPIDO, among community-living, Hispanic and Latino, Spanish-reading adults. METHODS: A 33-item survey was completed by 166 adults.
View Article and Find Full Text PDFObjectives: To investigate health-related quality of life in patients with idiopathic inflammatory myopathies (IIMs) compared with those with non-IIM autoimmune rheumatic diseases (AIRDs), non-rheumatic autoimmune diseases (nrAIDs) and without autoimmune diseases (controls) using Patient-Reported Outcome Measurement Information System (PROMIS) instrument data obtained from the second COVID-19 vaccination in autoimmune disease (COVAD-2) e-survey database.
Methods: Demographics, diagnosis, comorbidities, disease activity, treatments and PROMIS instrument data were analysed. Primary outcomes were PROMIS Global Physical Health (GPH) and Global Mental Health (GMH) scores.
Background: The effect of COVID-19 infection on post-operative mortality and the optimal timing to perform ambulatory surgery from diagnosis date remains unclear in this population. Our study was to determine whether a history of COVID-19 diagnosis leads to a higher risk of all-cause mortality following ambulatory surgery.
Methods: This cohort constitutes retrospective data obtained from the Optum dataset containing 44,976 US adults who were tested for COVID-19 up to 6 months before surgery and underwent ambulatory surgery between March 2020 to March 2021.
Deep intracerebral hemorrhage (ICH) exerts a direct force on corticospinal tracts (CST) causing shape deformation. Using serial MRI, Generalized Procrustes Analysis (GPA), and Principal Components Analysis (PCA), we temporally evaluated the change in CST shape. Thirty-five deep ICH patients with ipsilesional-CST deformation were serially imaged on a 3T-MRI with a median imaging time of day-2 and 84 of onset.
View Article and Find Full Text PDFTracheostomy following severe traumatic brain injury (TBI) is common, yet the outcomes associated with tracheostomy timing are unclear. The objective of this study was to assess hospital outcomes of tracheostomy timing in TBI patients. We retrospectively analyzed data from the National Inpatient Sample database of adult patients aged ≥18 years with a primary diagnosis of TBI.
View Article and Find Full Text PDFBackground: Traumatic brain injury (TBI) and obstructive sleep apnea (OSA) are common in the general population and are associated with significant morbidity and mortality. The objective of this study was to assess hospital outcomes of patients with TBI with and without a pre-existing OSA diagnosis.
Methods: We retrospectively analyzed data from the National Inpatient Sample (NIS) database of adult patients aged ≥ 18 years with a primary diagnosis of TBI.
Setting: In the last few decades, an opioid related health crisis has been a challenging problem in many countries around the world, especially the United States. Better understanding of the association of pre-admission opioid abuse and/or dependence (POAD) on specific major complications in traumatic brain injury (TBI) patients can aid the medical team in improving patient care management and outcomes.
Study Objective: Our goal is to assess and quantify the risk of POAD on in-hospital mortality and major complications in TBI patients.
The exponential growth of genomic/genetic data in the era of Big Data demands new solutions for making these data findable, accessible, interoperable and reusable. In this article, we present a web-based platform named Gene Expression Time-Course Research (GETc) Platform that enables the discovery and visualization of time-course gene expression data and analytical results from the NIH/NCBI-sponsored Gene Expression Omnibus (GEO). The analytical results are produced from an analytic pipeline based on the ordinary differential equation model.
View Article and Find Full Text PDFBackground: Acute traumatic spinal cord injuries (SCIs) often result in impairments in respiration that may lead to a sequelae of pulmonary dysfunction, increased risk of infection, and death. The optimal timing for tracheostomy in patients with acute SCI is currently unknown. This systematic review and meta-analysis aims to assess the optimal timing of tracheostomy in SCI patients and evaluate the potential benefits of early versus late tracheostomy.
View Article and Find Full Text PDFObjective: Subarachnoid hemorrhage (SAH) is often devastating with increased early mortality, particularly in those with presumed delayed cerebral ischemia (DCI). The ability to accurately predict survival for SAH patients during the hospital course would provide valuable information for healthcare providers, patients, and families. This study aims to utilize electronic health record (EHR) data and machine learning approaches to predict the adverse outcome for nontraumatic SAH adult patients.
View Article and Find Full Text PDFObjective: Subarachnoid hemorrhage (SAH) is a devastating cerebrovascular condition, not only due to the effect of initial hemorrhage, but also due to the complication of delayed cerebral ischemia (DCI). While hypertension facilitated by vasopressors is often initiated to prevent DCI, which vasopressor is most effective in improving outcomes is not known. The objective of this study was to determine associations between initial vasopressor choice and mortality in patients with nontraumatic SAH.
View Article and Find Full Text PDFAberrant activation of the Sonic Hedgehog (SHH) gene is observed in various cancers. Previous studies have shown a "cross-talk" effect between the canonical Hedgehog signaling pathway and the Epidermal Growth Factor (EGF) pathway when SHH is active in the presence of EGF. However, the precise mechanism of the cross-talk effect on the entire gene population has not been investigated.
View Article and Find Full Text PDFCurrently, methods for conducting multiple treatment propensity scoring in the presence of high-dimensional covariate spaces that result from "big data" are lacking-the most prominent method relies on inverse probability treatment weighting (IPTW). However, IPTW only utilizes one element of the generalized propensity score (GPS) vector, which can lead to a loss of information and inadequate covariate balance in the presence of multiple treatments. This limitation motivates the development of a novel propensity score method that uses the entire GPS vector to establish a scalar balancing score that, when adjusted for, achieves covariate balance in the presence of potentially high-dimensional covariates.
View Article and Find Full Text PDFInt J Comput Biol Drug Des
February 2020
Gene dynamic analysis is essential in identifying target genes involved pathogenesis of various diseases, including cancer. Cancer prognosis is often influenced by hypoxia. We apply a multi-step pipeline to study dynamic gene expressions in response to hypoxia in three cancer cell lines: prostate (DU145), colon (HT29), and breast (MCF7) cancers.
View Article and Find Full Text PDFObjective: The centrality of data to biomedical research is difficult to understate, and the same is true for the importance of the biomedical literature in disseminating empirical findings to scientific questions made on such data. But the connections between the literature and related datasets are often weak, hampering the ability of scientists to easily move between existing datasets and existing findings to derive new scientific hypotheses. This work aims to recommend relevant literature articles for datasets with the ultimate goal of increasing the productivity of researchers.
View Article and Find Full Text PDFJ Biopharm Stat
January 2015
In this article, we discuss an optimization approach to the sample size question, founded on maximizing the value of information in comparison studies with binary responses. The expected value of perfect information (EVPI) is calculated and the optimal sample size is obtained by maximizing the expected net gain of sampling (ENGS), the difference between the expected value of sample information (EVSI) and the cost of conducting the trial. The data are assumed to come from two independent binomial distributions, while the parameter of interest is the difference between the two success probabilities, [Formula: see text].
View Article and Find Full Text PDFIn this study, we discuss a decision theoretic or fully Bayesian approach to the sample size question in clinical trials with binary responses. Data are assumed to come from two binomial distributions. A Dirichlet distribution is assumed to describe prior knowledge of the two success probabilities p1 and p2.
View Article and Find Full Text PDFSample size computations are largely based on frequentist or classical methods. In the Bayesian approach the prior information on the unknown parameters is taken into account. In this work we consider a fully Bayesian approach to the sample size determination problem which was introduced by Grundy et al.
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