Impact of Pre-existing Type 2 Diabetes Mellitus and Cardiovascular Disease on Healthcare Resource Utilization and Costs in Patients With COVID-19.

The economic burden associated with type 2 diabetes mellitus (T2DM) and concurrent cardiovascular disease (CVD) among patients with COVID-19 is unclear. We compared healthcare resource utilization (HCRU) and costs in patients with COVID-19 and T2DM and CVD (T2DM + CVD), T2DM only, or neither T2DM nor CVD (T2DM/CVD). A retrospective observational study in COVID-19 patients using data from the Healthcare Integrated Research Database (HIRD®) was conducted.

Bilinear optimization of protein structure prediction: An exact approach via AB off-lattice model.

Protein structure prediction (PSP) remains a central challenge in computational biology due to its inherent complexity and high dimensionality. While numerous heuristic approaches have appeared in the literature, their success varies. The AB off-lattice model, which characterizes proteins as sequences of A (hydrophobic) and B (hydrophilic) beads, presents a simplified perspective on PSP.

Empagliflozin and Risk of Incident Gout: Analysis from the EMPagliflozin Comparative Effectiveness and SafEty (EMPRISE) Cohort Study.

Background: Hyperuricemia is frequently observed in patients with type 2 diabetes (T2D) and is associated with increased risk of gout and cardiovascular disease (CVD). Empagliflozin lowers serum urate levels by enhancing its urinary excretion.

Objective: To compare initiators of empagliflozin vs dipeptidyl peptidase-4 inhibitor (DPP4i) and initiators of empagliflozin vs glucagon-like peptide-1 receptor agonist (GLP-1RA) with respect to the risk of incident gout events.

Random Convolutional Kernel Transform with Empirical Mode Decomposition for Classification of Insulators from Power Grid.

The electrical energy supply relies on the satisfactory operation of insulators. The ultrasound recorded from insulators in different conditions has a time series output, which can be used to classify faulty insulators. The random convolutional kernel transform (Rocket) algorithms use convolutional filters to extract various features from the time series data.

Video-Based Human Activity Recognition Using Deep Learning Approaches.

Due to its capacity to gather vast, high-level data about human activity from wearable or stationary sensors, human activity recognition substantially impacts people's day-to-day lives. Multiple people and things may be seen acting in the video, dispersed throughout the frame in various places. Because of this, modeling the interactions between many entities in spatial dimensions is necessary for visual reasoning in the action recognition task.

Group Method of Data Handling Using Christiano-Fitzgerald Random Walk Filter for Insulator Fault Prediction.

Disruptive failures threaten the reliability of electric supply in power branches, often indicated by the rise of leakage current in distribution insulators. This paper presents a novel, hybrid method for fault prediction based on the time series of the leakage current of contaminated insulators. In a controlled high-voltage laboratory simulation, 15 kV-class insulators from an electrical power distribution network were exposed to increasing contamination in a salt chamber.

Machine Fault Detection Using a Hybrid CNN-LSTM Attention-Based Model.

The predictive maintenance of electrical machines is a critical issue for companies, as it can greatly reduce maintenance costs, increase efficiency, and minimize downtime. In this paper, the issue of predicting electrical machine failures by predicting possible anomalies in the data is addressed through time series analysis. The time series data are from a sensor attached to an electrical machine (motor) measuring vibration variations in three axes: X (axial), Y (radial), and Z (radial X).

Impact of pre-existing type 2 diabetes with and without cardiovascular disease on patients with COVID-19.

Aim: To compare adverse outcomes among COVID-19 patients with pre-existing type 2 diabetes (T2D) only, T2D and cardiovascular disease (CVD), or neither.

Methods: This retrospective cohort study used administrative claims, laboratory and mortality data from the HealthCore Integrated Research Database. Patients with COVID-19 were identified from 3 January 2020 to 31 May 2021 and stratified by the presence of T2D and CVD.

Optimized EWT-Seq2Seq-LSTM with Attention Mechanism to Insulators Fault Prediction.

Insulators installed outdoors are vulnerable to the accumulation of contaminants on their surface, which raise their conductivity and increase leakage current until a flashover occurs. To improve the reliability of the electrical power system, it is possible to evaluate the development of the fault in relation to the increase in leakage current and thus predict whether a shutdown may occur. This paper proposes the use of empirical wavelet transform (EWT) to reduce the influence of non-representative variations and combines the attention mechanism with a long short-term memory (LSTM) recurrent network for prediction.

Active Control System to Prevent Malfunctioning Caused by the Pressure Difference in Gasket Plate Heat Exchangers Applied in the Oil and Gas Industry.

In the oil and gas industry, heat exchangers are subject to loads that cause malfunctioning. These loads are divided into thermal and mechanical stresses; however, most efforts are focused on studying thermal stresses. The present work reduces mechanical stresses by mitigating pressure events in a gasket plate heat exchanger (GPHE).

An Energy-Aware Task Scheduling for Quality-of-Service Assurance in Constellations of Nanosatellites.

When managing a constellation of nanosatellites, one may leverage this structure to improve the mission's quality-of-service (QoS) by optimally distributing the tasks during an orbit. In this sense, this research proposes an offline energy-aware task scheduling problem formulation regarding the specifics of constellations, by considering whether the tasks are individual, collective, or stimulated to be redundant. By providing such an optimization framework, the idea of estimating an offline task schedule can serve as a baseline for the constellation design phase.

Static Attitude Determination Using Convolutional Neural Networks.

The need to estimate the orientation between frames of reference is crucial in spacecraft navigation. Robust algorithms for this type of problem have been built by following algebraic approaches, but data-driven solutions are becoming more appealing due to their stochastic nature. Hence, an approach based on convolutional neural networks in order to deal with measurement uncertainty in static attitude determination problems is proposed in this paper.

Use of diuretics and outcomes in patients with type 2 diabetes: findings from the EMPA-REG OUTCOME trial.

Aims: Loop diuretics (LD) relieve symptoms and signs of congestion due to heart failure (HF), but many patients prescribed LD do not have such a diagnosis. We studied the relationship between HF diagnosis, use of LD, and outcomes in patients with type 2 diabetes mellitus (T2DM) enrolled in the EMPA-REG OUTCOME trial.

Methods And Results: The relationship between HF diagnosis, use of LD, and outcomes was evaluated in four patient subgroups with T2DM: (i) investigator-reported HF on LD, (ii) investigator-reported HF not on LD, (iii) no HF on LD, and (iv) no HF and not on LD, and we assessed their risk of cardiovascular events.

Universal Verification Platform and Star Simulator for Fast Star Tracker Design.

Developing star trackers quickly is non-trivial. Achieving reproducible results and comparing different algorithms are also open problems. In this sense, this work proposes the use of synthetic star images (a simulated sky), allied with the standardized structure of the Universal Verification Methodology as the base of a design approach.

Heart failure documentation in outpatients with diabetes and volume overload: an observational cohort study from the Diabetes Collaborative Registry.

Background: Heart failure is a common and devastating complication of type 2 diabetes (T2D). Prompt recognition of heart failure may avert hospitalization, facilitate use of guideline-directed therapies, and impact choice of T2D medications. We sought to determine the rate and factors associated with heart failure documentation in T2D patients with evidence of volume overload requiring loop diuretics.

Improved resolution of mixed STR profiles using a fully automated differential cell lysis/DNA extraction method.

Sexual assault evidence often contains sperm cells, which are typically separated from nonsperm cells using manual differential lysis procedures. The goal of this study was to evaluate the automated QIAGEN QIAcube for this purpose and to compare it to manual QIAGEN and manual organic differential methods using DNA yields STR profile data for assessment. DNA yields were determined by qPCR, followed by multiplex STR amplification, CE analysis, and mixture interpretation.

Antihyperglycemic and Blood Pressure Effects of Empagliflozin in Black Patients With Type 2 Diabetes Mellitus and Hypertension.

Background: Empagliflozin, a sodium-glucose cotransporter 2 inhibitor indicated for type 2 diabetes mellitus (T2DM), can lower blood pressure (BP) and reduce cardiovascular mortality in patients with T2DM and preexisting cardiovascular disease. Its effects in blacks have been understudied.

Methods: In this 24-week study, 150 blacks with T2DM and hypertension had glycohemoglobin (primary end point), office and 24-hour ambulatory BP, body weight, and safety assessments.

Real-world opportunity of empagliflozin to improve blood pressure control in African American patients with type 2 diabetes: A National Cardiovascular Data Registry "research-to-practice" project from the diabetes collaborative registry.

The 1245.29 Trial recently showed that empaglifozin improved both blood pressure and glucose control in African American (AA) patients with type 2 diabetes (T2D) and hypertension. Using the Diabetes Collaborative Registry, a large-scale US registry of outpatients with diabetes recruited from primary care, cardiology and endocrinology practices, we sought to understand the potential impact of these observations in routine clinical practice.

Use of Intensive Glycemic Management in Older Adults with Diabetes Mellitus.

Objectives: To examine the proportion of older adults with diabetes mellitus treated with tight glucose control and the factors associated with this practice.

Design: Cross-sectional analysis.

Setting: Outpatient sites in the Diabetes Collaborative Registry (N=151).

Design of a 24-week trial of empagliflozin once daily in hypertensive black/African American patients with type 2 diabetes mellitus.

Objective: Black/African American individuals have a higher prevalence of type 2 diabetes mellitus (T2DM), diabetes-related complications and hypertension, but they are often underrepresented in clinical trials. The sodium-glucose co-transporter 2 inhibitor, empagliflozin, was associated with significant improvements in glucose control (via hemoglobin [Hb] A) and reductions in blood pressure (BP; via office and ambulatory BP monitoring) in a primarily white population with T2DM and hypertension. The aim of this ongoing study is to assess the safety and efficacy of empagliflozin in terms of glucose- and BP-lowering in a self-identified black/African American population with T2DM and hypertension.

Biotransformation and mass balance of the SGLT2 inhibitor empagliflozin in healthy volunteers.

1. The absorption, biotransformation and excretion of empagliflozin, an SGLT2 inhibitor, were evaluated in eight healthy subjects following a single 50 mg oral dose of empagliflozin containing ∼100 µCi [(14)C]-empagliflozin. 2.

Exposure-response modelling for empagliflozin, a sodium glucose cotransporter 2 (SGLT2) inhibitor, in patients with type 2 diabetes.

Aims: To provide model-based clinical development decision support including dose selection guidance for empagliflozin, an orally administered sodium glucose cotransporter 2 inhibitor, through developed exposure-response (E-R) models for efficacy and tolerability in patients with type 2 diabetes mellitus (T2DM).

Methods: Five randomized, placebo-controlled, multiple oral dose studies of empagliflozin in patients with T2DM (n = 974; 1-100 mg once daily, duration ≤12 weeks) were used to develop E-R models for efficacy (glycosylated haemoglobin [HbA1c ], fasting plasma glucose [FPG] and urinary glucose excretion). Two studies (n = 748, 12 weeks) were used to evaluate tolerability E-R.

Pharmacokinetics, pharmacodynamics, safety and tolerability of 4 weeks' treatment with empagliflozin in Japanese patients with type 2 diabetes mellitus.

Introduction: To evaluate the pharmacodynamics, pharmacokinetics, safety and tolerability of empagliflozin in Japanese patients with type 2 diabetes mellitus.

Materials And Methods: In this 4-week, multiple dose, randomized, parallel-group, double-blind, placebo-controlled trial, patients (n = 100) were randomized to receive 1, 5, 10 or 25 mg of empagliflozin, or placebo once daily. Key end-points were urinary glucose excretion (UGE), fasting plasma glucose (FPG) and eight-point glucose profile.

Population pharmacokinetics of empagliflozin, a sodium glucose cotransporter 2 inhibitor, in patients with type 2 diabetes.

Data from five randomized, placebo-controlled, multiple oral dose studies of empagliflozin in patients with type 2 diabetes mellitus (T2DM; N = 974; 1-100 mg q.d.; ≤12 weeks) were used to develop a population pharmacokinetic (PK) model for empagliflozin.

Efficacy and safety of empagliflozin, a sodium glucose cotransporter 2 (SGLT2) inhibitor, as add-on to metformin in type 2 diabetes with mild hyperglycaemia.

Aims: To evaluate the effects of the sodium glucose cotransporter 2 (SGLT2) inhibitor empagliflozin added to metformin for 12 weeks in patients with type 2 diabetes.

Methods: This dose-ranging, double-blind, placebo-controlled trial randomized 495 participants with type 2 diabetes inadequately controlled on metformin [haemoglobin A1c (HbA1c) >7 to ≤10%] to receive 1, 5, 10, 25, or 50 mg empagliflozin once daily (QD), or placebo, or open-label sitagliptin (100 mg QD), added to metformin for 12 weeks. The primary endpoint was change in HbA1c from baseline to week 12 (empagliflozin groups versus placebo).