Medication-Taking Trajectory and Its Correlates in Patients With Diabetes: Based on the Information–Motivation–Behavioral Skills Model

PURPOSE: The purpose was to identify trajectories of medication taking among patients with diabetes and investigate correlates of these trajectories using the information-motivation-behavioral skills (IMB) model. METHODS: This study employed a descriptive correlational, longitudinal design using convenience sampling. The participants were 96 adults with diabetes from an outpatient diabetes clinic at a university-affiliated hospital. Medication taking was assessed at 3 time points: baseline, 6 months, and 12 months. At baseline, study variables based on the IMB model were measured: medication knowledge (information), motivational readiness and social support (motivation), and medication self-efficacy (behavioral skills). Group-based trajectory modeling was used to identify medication-taking trajectories, and multinomial logistic regression was used to assess factors associated with medication-taking trajectories. RESULTS: Three distinct medication-taking trajectory groups were identified: "high medication taking," "increasing medication taking," and "low medication taking." Higher medication knowledge was associated with the high and increasing medication-taking trajectory groups. Motivational readiness was associated with the high and increasing medication-taking groups. In contrast, higher medication self-efficacy was associated only with the high medication-taking group, not with the increasing and low medication-taking groups. CONCLUSIONS: The findings suggest that knowledge, motivational readiness, and self-efficacy are essential in IMB model-based intervention strategies across dynamic medication-taking patterns to enhance medication taking. Health care providers can help patients with diabetes improve medication taking by understanding their medication-taking trajectories and their correlates. Strategies that enhance medication self-efficacy are essential for patients in the increasing and low medication-taking groups

KF-NIPT: K-mer and fetal fraction-based estimation of chromosomal anomaly from NIPT data

BACKGROUND: Non-Invasive Prenatal Testing (NIPT) is a technique that allows pregnant women to screen for chromosomal abnormalities in their developing fetus without the need for invasive procedures like amniocentesis or chorionic villus sampling. However, current methods to detect anomaly from maternal cell-free DNAs (cfDNAs) that are based on the sequence read counts calculating z-scores face challenges with false positives and negatives. To address these challenges, we aimed to develop a novel NIPT algorithm named KF-NIPT, which is derived from the initials of k-mer and fetal fraction used in its development with the goal of significantly improving accuracy. RESULTS: We developed a KF-NIPT, a new algorithm that estimate chromosomal anomaly by calculating K-mer-based sequence depth and fetal fraction from the whole genome sequencing (WGS) data. Moreover, we implemented a modified preprocessing pipeline for the WGS data, correcting the biases of the genomic mapping quality and the GC contents. The performance of our method was evaluated using publicly available NIPT data. We could demonstrate that our method has better accuracy and sensitivity compared to those of the previous methods. CONCLUSIONS: We found that using k-mer and fetal fraction reduces errors in NIPT and have integrated this into a pipeline, showing that the traditional read count-based z-score method can be improved. KF-NIPT is implemented in the R and Python environment. The source code is available at https://github.com/eastbrain/KF-NIPT . KF-NIPT has been tested on Ubuntu Linux-64 server and Linux-64 on Windows using a WSL (Windows Subsystem for Linux)

Inhibitory effects of kukoamine B on adipogenesis and lipid accumulation in vitro and obesity in vivo

Obesity, characterized by excessive adipose tissue accumulation, is an important risk factor for the development of several chronic conditions, including cardiovascular disease, type 2 diabetes mellitus, and hypertension. The present study aimed to investigate the effects of kukoamine B (KB), a major component of the Lycii Radicis Cortex (LRC), on adipogenesis and lipid accumulation in vitro and further assess its role in obesity in vivo. For the in vitro experiments, 3T3-L1 cells and primary-cultured adipose-derived stem cells were used. Lipid accumulation was measured using Oil Red O staining, and adipogenesis-related gene expression was assessed using quantitative reverse transcription polymerase chain reaction. For the in vivo experiments, LRC or KB was orally administered to ovariectomized and high-fat diet-induced obese mice. LRC exhibited antiadipogenic and antiobesity effects in vitro and in vivo experiments. Fractionation of the LRC extract identified KB as a bio-active component. KB treatment resulted in a dose-dependent reduction in lipid droplet formation and downregulation of adipogenesis-related genes, including Pparg, Cebpa, Srebp1, Fasn, and Plin2, in both cell types. Western blot analysis revealed that KB significantly suppressed the protein expression of key adipogenic factors, including phosphorylated CREB, CEBPB, PPARG, and CEBPA. In vivo, KB administration significantly reduced body weight gain, hepatic steatosis, and adipocyte hypertrophy in both mouse models. These results suggest that KB is a potential therapeutic agent for the prevention and treatment of obesity. Further rigorous investigations, including human clinical trials, are necessary to fully elucidate the safety profile, optimal dosing regimens, and long-term effects of KB

Nelonemdaz Treatment for Patients With Out-of-Hospital Cardiac Arrest: A Randomized Clinical Trial

OBJECTIVES: Nelonemdaz is a N-methyl d-aspartate receptor subtype 2B-selective N-methyl-D-aspartate receptor antagonist and a potent free-radical scavenger that might ameliorate hypoxic-ischemic brain injury after out-of-hospital cardiac arrest (OHCA). We investigated the efficacy of nelonemdaz for patients with OHCA. DESIGN: A double-blind, placebo-controlled, randomized, multicenter phase II trial. SETTING: This trial enrolled 105 patients at five sites in South Korea between November 18, 2018, and February 23, 2023. PARTICIPANTS: OHCA patients undergoing targeted temperature management. INTERVENTIONS: Patients were randomly assigned to high-dose (5250 mg), low-dose (3250 mg), and placebo groups at a 1:1:1 ratio. MEASUREMENTS AND MAIN RESULTS: Patients with a median age of 61 years (82% male) were assigned to the high-dose (n = 37), low-dose (n = 35), and placebo (n = 33) groups. The primary outcome, the serum level of neuron-specific enolase (NSE) at 48-52 hours, was evaluated in 93 patients. There was no difference in serum NSE between high-dose (median and interquartile range; 23.7, 15.0-69.9) and placebo (17.5, 13.6-113.0) groups, or between low-dose (26.6, 16.2-83.4) and placebo groups (all p > 0.05). Brain MRI fractional anisotropy was significantly higher in the high-dose group compared with the placebo group (0.465, 0.449-0.485 vs. 0.441, 0.431-0.464; p = 0.028), but not between low-dose (0.462, 0.439-0.480) and placebo groups (p > 0.05). At day 90, the common odds ratio (95% CI) indicating a numerically favorable shift in the modified Rankin Scale was 1.25 (0.48-3.24) and 1.22 (0.47-3.20) in the high-dose and low-dose groups, respectively, compared with placebo group (all p > 0.05). No serious adverse events were reported. CONCLUSIONS: Nelonemdaz treatment of patients after OHCA did not reduce serum NSE levels compared with controls. Patients treated with high-dose nelonemdaz showed higher brain MRI fractional anisotropy suggesting less cerebral white matter damage

Understanding the Utilization of Tertiary Hospitals by Mild Disease Patients: Travel Cost Method Analysis

PURPOSE: Tertiary hospital utilization for patients with mild diseases creates inefficiencies in medical utilization for medical consumers and providers, collapses the healthcare delivery system, and has negative consequences for the public health system. This study aims to identify the factors that lead to the selection of tertiary hospitals and the medical needs of patients with mild diseases. We evaluate the value of using medical institutions by comparing and analyzing regional and individual patient characteristics. METHODS: The travel cost method based on the travel cost incurred according to the consumer's temporal choice, was used to evaluate the medical use. We considered data from Ajou University Hospital from 2017 to 2022. The variables used for travel costs are travel costs, time costs, and medical costs. The Quantum Geographic Information System(QGIS) network analysis was used to calculate travel costs and time costs, and independent sample t-tests and analysis of variance (ANOVA) were used to compare the evaluated values between groups. RESULTS: The analysis revealed that travel costs were the highest for patients with diabetes. Regarding personal characteristics, men exhibited higher rates than women, and individuals under 65 years of age and those receiving type 2 medical benefits demonstrated higher travel costs. Travel costs and outpatient visit rates for mild diseases exhibited a direct proportional relationship. We compared the total economic value assessed for each type of mild disease and found the highest value for diabetes patients with the highest number of outpatient visits. CONCLUSION: These findings highlight the importance of incorporating patient segmentation into policy formulation to alleviate the overcrowding of patients with mild diseases in tertiary care hospitals. Furthermore, they advocate adopting a primary care-centered approach to enhance the healthcare delivery system and address imbalances in community healthcare resources

Concurrent Fabry disease and IgA nephropathy in a patient with Crohn's disease: A case report

We present a unique case of concurrent Fabry disease (FD) and IgA nephropathy (IgAN) in a 27-year-old female with a 10-year history of Crohn's disease (CD). The patient presented to the nephrology clinic with microscopic haematuria and proteinuria on routine tests. A kidney biopsy revealed mesangial matrix widening, mesangial cell proliferation, and podocyte enlargement with prominent lacy and clear cytoplasm, as observed with haematoxylin and eosin staining. Immunofluorescence staining demonstrated diffuse immunoglobulin A deposits in the mesangium. Electron microscopy identified myelin-like figures in the cytoplasm of podocytes and electron-dense deposits in the mesangium, confirming IgAN and suggesting FD. Subsequent testing showed low alpha-galactosidase A (α-gal) enzyme activity in the patient's white blood cells, confirming the FD diagnosis. Enzyme replacement therapy was initiated following the diagnosis. To our knowledge, this is the first reported case of the coexistence of FD, IgAN, and CD in a single patient. This case highlights the importance of considering FD in patients with proteinuria, emphasising the need for comprehensive diagnostic evaluations in complex cases

Relationship between multiple unemployment spells and cardiovascular disease mortality in South Korean workers

BACKGROUND: It is necessary to explore the health problems of vulnerable workers who experience repeated unemployment spells. The number of unemployment spells should be considered in the relationship between unemployment and cardiovascular disease (CVD) mortality. Using nationwide data, we aimed to investigate the relationship between unemployment and CVD mortality and examine whether this effect varies depending on the number of unemployment spells. METHODS: Using data from Statistics Korea and employment insurance databases from 2018 to 2019, we identified an average of 1387 CVD deaths per year among 7.76 million workers who had at least one employment record prior to their death. The number of unemployment spells was calculated based on the employment history over the past 5 years. Crude mortality rates per 100 000 individuals and age-standardised mortality rates (SMRs) and sex-SMRs were calculated. RESULTS: The crude mortality rate due to CVD was 17.9 per 100 000 individuals among workers. Workers with one unemployment spell in the past 5 years had a significantly higher SMR than those without (2.01; 95% CI 1.87 to 2.16). Additionally, as unemployment spells increased, the SMR increased. The impact was more substantial among older workers than among younger workers. These findings remained consistent when CVD was divided into ischaemic heart disease and cerebrovascular disease. CONCLUSION: Repeated unemployment spells may be a risk factor for increased CVD mortality. These findings underscore the vulnerability of individuals facing repeated unemployment spells, highlighting the necessity for economic as well as health and psychological support

Risk of Contrast-Induced Acute Kidney Injury in Computed Tomography: A 16 Institutional Retrospective Cohort Study

OBJECTIVES: Concern about contrast-induced acute kidney injury (CI-AKI) may delay the timely administration of contrast media for computed tomography (CT). The precise causative effect of iodinated contrast media on CI-AKI and its relevant risk factors remains an area of ongoing investigation. Therefore, this study aimed to determine the risk of CI-AKI following contrast-enhanced CT and its predisposing risk factors. MATERIALS AND METHODS: This study employed a 1:1 propensity score matching analysis using electronic medical records gathered between January 2006 and December 2022 from 16 institutions in South Korea. Contrast-enhanced and nonenhanced CT scans in patients aged 18 years and above were matched for baseline estimated glomerular filtration rate (eGFR), demographic characteristics, and clinical variables to assess the risk of CI-AKI. Subgroup analyses were conducted to evaluate any significant risk factors for CI-AKI. RESULTS: A total of 182,170 CT scans with contrast were matched to 182,170 CT scans without contrast. The risk of CI-AKI in the entire study cohort was not statistically significant (odds ratio [OR], 1.036; 95% confidence interval [CI], 0.968-1.109; P = 0.34). Subgroup analyses revealed a significantly higher risk of CI-AKI in patients with eGFR <30 mL/min/1.73m 2 (OR, 1.176; 95% CI, 1.080-1.281; P = 0.011) or eGFR 30-45 mL/min/1.73m 2 (OR, 1.139; 95% CI, 1.043-1.244; P = 0.019), patients diagnosed with chronic kidney disease (OR, 1.215; 95% CI, 1.084-1.361; P = 0.011), and those administered with iso-osmolar contrast media (OR, 1.392; 95% CI, 1.196-1.622; P = 0.011). CONCLUSIONS: The risk of CI-AKI following CT was minimal in the general population. However, caution is warranted for patients with chronic kidney disease and eGFR lower than 45 mL/min/1.73m 2 , or those administered with iso-osmolar contrast media

A novel machine learning model for screening the risk of obstructive sleep apnea using craniofacial photography with questionnaires

STUDY OBJECTIVES: Undiagnosed or untreated moderate-to-severe obstructive sleep apnea (OSA) increases cardiovascular risks and mortality. Early and efficient detection is critical, given its high prevalence. We aimed to develop a practical and efficient approach for OSA screening, using simple facial photography and sleep questionnaires. METHODS: We retrospectively included 748 participants who completed polysomnography, sleep questionnaires (STOP-BANG), and facial photographs at a university hospital between 2012 and 2023. Owing to class imbalance, we randomly undersampled the participants, categorized into the moderate/severe or no/mild OSA group, based on an apnea-hypopnea index of 15 events/h. Using a validated convolutional neural network, we extracted the OSA probability scores from photographs, which were used as the input for the questionnaires. Four machine learning models were employed to classify the moderate/severe vs no/mild groups and evaluated in the test dataset. RESULTS: We analyzed 426 participants (213 each in the moderate/severe and no/mild groups). The mean (standard deviation) age was 44.6 (14.7) years; 80.8% were men. Logistic regression achieved the highest performance: the area under the receiver operator curve was 97.2%, and accuracy was 91.9%. Adding OSA probability, retrieved from facial photographs, to the questionnaires improved performance, compared with using questionnaires or photographs alone (the area under the receiver operating characteristic curve 97.2% using both, 85.7% for photographs alone, and 64% and 79.1% for questionnaire threshold STOP-BANG scores of 3 and 4, respectively). CONCLUSIONS: Using simple facial photographs and sleep questionnaires, a 2-stage approach (convolutional neural network + machine learning) accurately classified OSA into moderate/severe vs no/mild OSA groups. This method may facilitate optimal OSA treatment and avoid unnecessary costly evaluations. CITATION: Park J-Y, Shin H-R, Kim MH, et al. A novel machine learning model for screening the risk of obstructive sleep apnea using craniofacial photography with questionnaires. J Clin Sleep Med. 2025;21(5):843-854