Cerebral small vessel disease burden is associated with poststroke depressive symptoms: A 15-month prospective study

Objective: All types of cerebral small vessel disease (SVD) markers including lacune, white matter hyperintensities (WMH), cerebral microbleeds, and perivascular spaces were found to be associated with poststroke depressive symptoms (PDS). This study explored whether the combination of the four markers constituting an overall SVD burden was associated with PDS. Methods: A cohort of 563 patients with acute ischemic stroke were followed over a 15-month period after the index stroke. A score of _7 on the 15-item Geriatric Depression Scale was defined as clinically significant PDS. Scores of the four SVD markers ascertained on magnetic resonance imaging were summed up to represent total SVD burden. The association between SVD burden and PDS was assessed with generalized estimating equation models. Results: The study sample had a mean age of 67.0 _ 10.2 years and mild-moderate stroke [National Institutes of Health Stroke Scale score: 3, interquartile, 1–5]. PDS were found in 18.3%, 11.6%, and 12.3% of the sample at 3, 9, and 15 months after stroke, respectively. After adjusting for demographic characteristics, vascular risk factors, social support, stroke severity, physical and cognitive functions, and size and locations of stroke, the SVD burden was associated with an increased risk of PDS [odds ratio = 1.30; 95% confidence interval = 1.07–1.58; p = 0.010]. Other significant predictors of PDS were time of assessment, female sex, smoking, number of acute infarcts, functional independence, and social support. Conclusion: SVD burden was associated with PDS examined over a 15-month follow-up in patients with mild to moderate acute ischemic stroke

IoT-Based Indoor and Outdoor Self-Quarantine System for COVID-19 Patients

Even after two years since the declaration of the new virus Coronavirus Disease 19 (COVID-19), the reported cases are still considerably high in many countries, including Malaysia. The health authorities cannot monitor the health condition and track the location of every home-monitored patient at once due to many confirmed cases in a day. In order to overcome the shortage of manpower, an Internet of Things (IoT)-based self-quarantine system with Radio Frequency Identification (RFID) and Global Positioning System (GPS) tracking is proposed in this paper to monitor the health conditions of the Covid-19 patients and track their real-time location via mobile application. Biomedical sensors are used to measure health conditions such as temperature, pulse oximetry, and heart-rate monitor. In addition, the RFID readers are used to detect patients that intend to leave the quarantine area, and the GPS modules are used to track their actual geometrical location so that the authorities can take further action. The real-time data is automatically pushed to the cloud server for the authorities to remotely view the patient's health condition and location on the Google map using smart devices. Finally, a hardware prototype and a mobile application have been successfully developed in this project. The system is able to display the temperature, heartbeats, and blood oxygen saturation properly on a liquid crystal display (LCD) screen. All these measured values, together with the information from RFID detection and GPS location tracking, can be viewed on a smartphone

Risk stratification of sudden cardiac death in asymptomatic female Brugada syndrome patients: A literature review

Background and Objectives Risk stratification in Brugada syndrome remains a difficult problem. Given the male predominance of this disease and their elevated risks of arrhythmic events, affected females have received less attention. It is widely known that symptomatic patients are at increased risk of sudden cardiac death (SCD) than asymptomatic patients, while this might be true in the male population; recent studies have shown that this association might not be significant in females. Over the past few decades, numerous markers involving clinical symptoms, electrocardiographic (ECG) indices, and genetic tests have been explored, with several risk-scoring models developed so far. The objective of this study is to review the current evidence of clinical and ECG markers as well as risk scores on asymptomatic females with Brugada syndrome. Findings Gender differences in ECG markers, the yield of genetic findings, and the applicability of risk scores are highlighted. Conclusions Various clinical, electrocardiographic, and genetic risk factors are available for assessing SCD risk amongst asymptomatic female BrS patients. However, due to the significant gender discrepancy in BrS, the SCD risk amongst females is often underestimated, and there is a lack of research on female-specific risk factors and multiparametric risk scores. Therefore, multinational studies pooling female BrS patients are needed for the development of a gender-specific risk stratification approach amongst asymptomatic BrS patients

Turbulence in Focus: Benchmarking Scaling Behavior of 3D Volumetric Super-Resolution with BLASTNet 2.0 Data

Analysis of compressible turbulent flows is essential for applications related to propulsion, energy generation, and the environment. Here, we present BLASTNet 2.0, a 2.2 TB network-of-datasets containing 744 full-domain samples from 34 high-fidelity direct numerical simulations, which addresses the current limited availability of 3D high-fidelity reacting and non-reacting compressible turbulent flow simulation data. With this data, we benchmark a total of 49 variations of five deep learning approaches for 3D super-resolution - which can be applied for improving scientific imaging, simulations, turbulence models, as well as in computer vision applications. We perform neural scaling analysis on these models to examine the performance of different machine learning (ML) approaches, including two scientific ML techniques. We demonstrate that (i) predictive performance can scale with model size and cost, (ii) architecture matters significantly, especially for smaller models, and (iii) the benefits of physics-based losses can persist with increasing model size. The outcomes of this benchmark study are anticipated to offer insights that can aid the design of 3D super-resolution models, especially for turbulence models, while this data is expected to foster ML methods for a broad range of flow physics applications. This data is publicly available with download links and browsing tools consolidated at https://blastnet.github.io.Comment: Accepted in Advances in Neural Information Processing Systems 36 (NeurIPS 2023). 55 pages, 21 figures. v2: Corrected co-author name. Keywords: Super-resolution, 3D, Neural Scaling, Physics-informed Loss, Computational Fluid Dynamics, Partial Differential Equations, Turbulent Reacting Flows, Direct Numerical Simulation, Fluid Mechanics, Combustio

Incident heart failure and myocardial infarction in sodium-glucose cotransporter-2 vs. dipeptidyl peptidase-4 inhibitor users

Aims This study aimed to compare the rates of major cardiovascular adverse events in sodium-glucose cotransporter-2 inhibitors (SGLT2I) and dipeptidyl peptidase-4 inhibitors (DPP4I) users in a Chinese population. SGLT2I and DPP4I are increasingly prescribed for type 2 diabetes mellitus patients. However, few population-based studies are comparing their effects on incident heart failure or myocardial infarction. Methods and results This was a population-based retrospective cohort study using the electronic health record database in Hong Kong, including type 2 diabetes mellitus patients receiving either SGLT2I or DPP4I from 1 January 2015 to 31 December 2020. Propensity score matching was performed in a 1:1 ratio based on demographics, past comorbidities, and non-SGLT2I/DPP4I medications with nearest neighbour matching (caliper = 0.1). Univariable and multivariable Cox models were used to identify significant predictors for new-onset heart failure, new-onset myocardial infarction, cardiovascular mortality, and all-cause mortality. Sensitivity analyses with competing risk models and multiple propensity score matching approaches were conducted. A total of 41 994 patients (58.89% males, median admission age at 58 years old, interquartile range [IQR]: 51.2–65.3) were included with a median follow-up of 5.6 years (IQR: 5.32–5.82). In the matched cohort, SGLT2I use was significantly associated with lower risks of new-onset heart failure (hazard ratio [HR]: 0.73, 95% confidence interval [CI]: [0.66, 0.81], P < 0.0001), myocardial infarction (HR: 0.81, 95% CI: [0.73, 0.90], P < 0.0001), cardiovascular mortality (HR: 0.67, 95% CI: [0.53, 0.84], P < 0.001), and all-cause mortality (HR: 0.26, 95% CI: [0.24, 0.29], P < 0.0001) after adjusting for significant demographics, past comorbidities, and non-SGLT2I/DPP4I medications. Conclusions SGLT2 inhibitors are protective against adverse cardiovascular events including new-onset heart failure, myocardial infarction, cardiovascular mortality, and all-cause mortality. The prescription of SGLT2I is preferred when taken into consideration individual cardiovascular and metabolic risk profiles in addition to drug–drug interactions

Gender-specific clinical risk scores incorporating blood pressure variability for predicting incident dementia

Introduction: The present study examined the gender-specific prognostic value of blood pressure (BP) and its variability in the prediction of dementia risk and developed a score system for risk stratification. Materials and Methods This was a retrospective, observational population-based cohort study of patients admitted to government-funded family medicine clinics in Hong Kong between January 1, 2000 and March 31, 2002 with at least 3 blood pressure measurements. Gender-specific risk scores for dementia were developed and tested. Results The study consisted of 74 855 patients, of whom 3550 patients (incidence rate: 4.74%) developed dementia over a median follow-up of 112 months (IQR= [59.8–168]). Nonlinear associations between diastolic/systolic BP measurements and the time to dementia presentation were identified. Gender-specific dichotomized clinical scores were developed for males (age, hypertension, diastolic and systolic BP and their measures of variability) and females (age, prior cardiovascular, respiratory, gastrointestinal diseases, diabetes mellitus, hypertension, stroke, mean corpuscular volume, monocyte, neutrophil, urea, creatinine, diastolic and systolic BP and their measures of variability). They showed high predictive strengths for both male (hazard ratio [HR]: 12.83, 95% confidence interval [CI]: 11.15–14.33, P value &amp;lt; .0001) and female patients (HR: 26.56, 95% CI: 14.44–32.86, P value &amp;lt; .0001). The constructed gender-specific scores outperformed the simplified systems without considering BP variability (C-statistic: 0.91 vs 0.82), demonstrating the importance of BP variability in dementia development. Conclusion Gender-specific clinical risk scores incorporating BP variability can accurately predict incident dementia and can be applied clinically for early disease detection and optimized patient management

Information Communication Technology as Instrumental Activities of Daily Living for Aging-in-Place in Chinese Older Adults With and Without Cognitive Impairment: The Validation Study of Advanced Instrumental Activities of Daily Living Scale

Background: The capability in applying information communication technology (ICT) is crucial to the functional independence of older peoples of community living nowadays. The proper assessment of individuals' capability of ICT application is the corner stone for the future development of telemedicine in our aging population. Methods: With the recruitment of 300 participants of different functional and social background in home-living, hostel-living, and care-and-attention home living; and through assessing the ability of individuals in instrumental activities of daily living and cognitive assessments, this study aimed at capturing the content validity and construct validity of the Advanced Instrumental Activities of Daily Living (AIADL scale). In addition, this study assess the ability of older peoples in applying ICT and how the functional and social background affects their independence in aging-in-place. Results: The AIADL scale showed good test-retest reliability and good-to-excellent internal consistency. To determine if items of the AIADL scale measure various aspects of community living, exploratory factor analysis revealed a two-factor structure with “home living and management” and “community living”. Validity analysis with the known-groups method showed a high overall accuracy of prediction of individuals' capability of independent living in the community. Conclusions: The AIADL scale is a valid and reliable instrument to assess the ability of older adults in handling ICT as part of their instrumental activities in daily living. The scale can reflect capability of older peoples in applying ICT. This instrument can serve as a reference in measuring readiness of individuals in receiving telemedicine and their ability of aging-in-place