Influence of Digital Health Literacy on Blood Pressure and Hemoglobin A1c in Patients With Comorbid Type 2 Diabetes and Hypertension.

Digital health literacy is emerging as an important element in chronic illness management, yet its relationship with clinical outcomes remains unclear. Utilizing data from the ongoing EXpanding Technology-Enabled, Nurse-Delivered Chronic Disease Care trial, this cross-sectional, correlational study explored the association between digital health literacy, health literacy, and patient outcomes, specifically blood pressure and hemoglobin A1c levels in 76 patients managing comorbid type 2 diabetes and hypertension. Results indicate patients had moderate digital health literacy, which was not significantly correlated with health literacy (r = 0.

Sensitivity Analysis for Effects of Multiple Exposures in the Presence of Unmeasured Confounding.

Epidemiological research aims to investigate how multiple exposures affect health outcomes of interest, but observational studies often suffer from biases caused by unmeasured confounders. In this study, we develop a novel sensitivity model to investigate the effect of correlated multiple exposures on the continuous health outcomes of interest. The proposed sensitivity analysis is model-agnostic and can be applied to any machine learning algorithm.

Machine learning prediction model of the treatment response in schizophrenia reveals the importance of metabolic and subjective characteristics.

Predicting early treatment response in schizophrenia is pivotal for selecting the best therapeutic approach. Utilizing machine learning (ML) technique, we aimed to formulate a model predicting antipsychotic treatment outcomes. Data were obtained from 299 patients with schizophrenia from three multicenter, open-label, non-comparative clinical trials.

Sensitivity Analysis for Effects of Multiple Exposures in the Presence of Unmeasured Confounding: Non-Gaussian and Time-to-Event Outcomes.

In epidemiological studies, evaluating the health impacts stemming from multiple exposures is one of the important goals. To analyze the effects of multiple exposures on discrete or time-to-event health outcomes, researchers often employ generalized linear models, Cox proportional hazards models, and machine learning methods. However, observational studies are prone to unmeasured confounding factors, which can introduce the potential for substantial bias in the multiple exposure effects.

Pharmacokinetics of Vancomycin in Healthy Korean Volunteers and Monte Carlo Simulations to Explore Optimal Dosage Regimens in Patients with Normal Renal Function.

: To date, population pharmacokinetic (PK) studies of vancomycin on healthy Korean adults have not been conducted. This study aimed to investigate the PK properties of vancomycin in healthy volunteers and to identify optimal dosing regimens based on the area under the concentration-time curve (AUC) in adult patients with normal renal function. : We conducted a prospective clinical study, analysing PK samples from 12 healthy participants using noncompartmental analysis and non-linear mixed-effects modelling.

Modeling the Determinants of Subjective Well-Being in Schizophrenia.

Background: The ultimate goal of successful schizophrenia treatment is not just to alleviate psychotic symptoms, but also to reduce distress and achieve subjective well-being (SWB). We aimed to identify the determinants of SWB and their interrelationships in schizophrenia.

Methods: Data were obtained from 637 patients with schizophrenia enrolled in multicenter, open-label, non-comparative clinical trials.

Backward induction-based deep image search.

Conditional image retrieval (CIR), which involves retrieving images by a query image along with user-specified conditions, is essential in computer vision research for efficient image search and automated image analysis. The existing approaches, such as composed image retrieval (CoIR) methods, have been actively studied. However, these methods face challenges as they require either a triplet dataset or richly annotated image-text pairs, which are expensive to obtain.

EXpanding Technology-Enabled, Nurse-Delivered Chronic Disease Care (EXTEND): Protocol and Baseline Data for a Randomized Trial.

Background: Approximately 10-15 % of individuals with type 2 diabetes have persistently poorly-controlled diabetes mellitus (PPDM) despite receiving available care, and frequently have comorbid hypertension. Mobile monitoring-enabled telehealth has the potential to improve outcomes in treatment-resistant chronic disease by supporting self-management and facilitating patient-clinician contact but must be designed in a manner amenable to real-world use.

Methods: Expanding Technology-Enabled, Nurse-Delivered Chronic Disease Care (EXTEND) is an ongoing randomized trial comparing two 12-month interventions for comorbid PPDM and hypertension: 1) EXTEND, a mobile monitoring-enabled self-management intervention; and 2) EXTEND Plus, a comprehensive, nurse-delivered telehealth program incorporating mobile monitoring, self-management support, and pharmacist-supported medication management.

Beyond One-Size-Fits-All: Tailoring Teicoplanin Regimens for Normal Renal Function Patients Using Population Pharmacokinetics and Monte Carlo Simulation.

In patients with normal renal function, significant teicoplanin dose adjustments are often necessary. This study aimed to develop a population pharmacokinetic (PK) model for teicoplanin in healthy adults and use it to recommend optimal dosage regimens for patients with normal renal function. PK samples were obtained from 12 subjects and analyzed using a population approach.

Intrapulmonary and Systemic Pharmacokinetics of Colistin Following Nebulization of Low-Dose Colistimethate Sodium in Patients with Ventilator-Associated Pneumonia Caused by Carbapenem-Resistant .

Colistimethate sodium (CMS) nebulization is associated with reduced systemic toxicity compared to intravenous injection, with potentially enhanced clinical efficacy. This study aimed to assess the pharmacokinetic (PK) properties of colistin during low-dose CMS nebulization in patients with ventilator-associated pneumonia (VAP) caused by carbapenem-resistant . A nonlinear mixed-effects modeling approach was applied to develop population PK models for colistin in both epithelial lining fluid (ELF) and plasma.

Endoplasmic reticular stress as an emerging therapeutic target for chronic pain: a narrative review.

Chronic pain is a severely debilitating condition with enormous socioeconomic costs. Current treatment regimens with nonsteroidal anti-inflammatory drugs (NSAIDs), steroids, or opioids have been largely unsatisfactory with uncertain benefits or severe long-term side effects. This is mainly because chronic pain has a multifactorial aetiology.

The Natural L. (fig) Extract as an Effective Prophylactic Antibacterial Agent for Inflammation-Related Infections.

() is a multidrug-resistance Gram-negative organism responsible for carbapenem-resistant infections. These challenges have inspired studies on the use of natural products as alternatives to conventional drugs. The aim of this study was to analyze the antibacterial and antioxidant effects of L.

Effect of subscapularis repair on joint contact forces based on degree of posterior-superior rotator cuff tear severity in reverse shoulder arthroplasty.

Massive irreparable rotator cuff tears (RCTs) affect the clinical outcomes of reverse shoulder arthroplasty (RSA). However, the effects of subscapularis repair on the outcomes of RSA, based on the degree of posterior-superior RCTs, are unclear. This study aimed to examine the effect of subscapularis repair on three-dimensional joint contact forces (JCFs) based on the degree of posterior-superior RCT severity in RSA.

Bias reduction for semi-competing risks frailty model with rare events: application to a chronic kidney disease cohort study in South Korea.

In a semi-competing risks model in which a terminal event censors a non-terminal event but not vice versa, the conventional method can predict clinical outcomes by maximizing likelihood estimation. However, this method can produce unreliable or biased estimators when the number of events in the datasets is small. Specifically, parameter estimates may converge to infinity, or their standard errors can be very large.

Comparing predictions among competing risks models with rare events: application to KNOW-CKD atudy-a multicentre cohort study of chronic kidney disease.

A prognostic model to determine an association between survival outcomes and clinical risk factors, such as the Cox model, has been developed over the past decades in the medical field. Although the data size containing subjects' information gradually increases, the number of events is often relatively low as medical technology develops. Accordingly, poor discrimination and low predicted ability may occur between low- and high-risk groups.

Femoral Tunnel Geometry and Graft Inclination Angles in Anterior Cruciate Ligament Reconstruction Using a Flexible Reamer System.

: The aim of this study is to investigate the femoral tunnel geometry (femoral tunsnel location, femoral graft bending angle, and femoral tunnel length) on three-dimensional (3D) computed tomography (CT) and graft inclination on magnetic resonance imaging (MRI) after anatomic anterior cruciate ligament (ACL) reconstruction using a flexible reamer system. : A total of 60 patients who underwent anatomical ACL reconstruction (ACLR) using a flexible reamer system were retrospectively reviewed. One day after the ACLR procedure was performed, all patients underwent three-dimensional computed tomography (3D-CT) and magnetic resonance imaging (MRI).

The Growth Characteristics and the Active Compounds of Fruits in Different Cultivation Environments in South Korea.

is a traditional medicinal herb in East Asia. The compounds of plants vary depending on environmental factors, such as soil, temperature, drainage, and so on. However, few to no studies have been done on the correlation among environment, growth, and compounds in .

Population Pharmacokinetics and Monte Carlo Simulation of Cefepime in Critically Ill Patients with Hospital-Acquired/Ventilator-Associated Pneumonia.

Background: This study aimed to investigate the population pharmacokinetics (PK) profile and determine the optimal dosage regimen of cefepime in critically ill adult patients with hospital-acquired pneumonia (HAP) or ventilator-associated pneumonia (VAP).

Materials And Methods: Population-PK models for cefepime were developed using a nonlinear mixed-effect modeling approach. The percentage of time within 24 h in which the free concentration exceeded the minimum inhibitory concentration (MIC) at a steady state (50%T, 100%T, and 100%T) for various combinations of dosage regimens and renal function was explored using Monte Carlo simulation.

Evaluation of the color stability of 3D printed resin according to the oxygen inhibition effect and temperature difference in the post-polymerization process.

The aim of this study was to determine the color stability of 3D printed resin according to the post-curing conditions (polymerization conditions and temperature). Specimens were post-polymerized under different conditions of oxygen inhibition, such as on glycerin immersion (GLY), medium-low vacuum environment (VA), and oxygen contact (CON, the control group), and temperature (35 °C, 60 °C, and 80 °C). The degree of conversion (DC), water sorption (W) and solubility (W), surface roughness (Ra) were measured.

Overall assessment for selected markers from high-throughput data.

Reproducibility, a hallmark of science, is typically assessed in validation studies. We focus on high-throughput studies where a large number of biomarkers is measured in a training study, but only a subset of the most significant findings is selected and re-tested in a validation study. Our aim is to get the statistical measures of overall assessment for the selected markers, by integrating the information in both the training and validation studies.