Cardiac short term memory

BACKGROUND: The multi-tasking approach may be promising for cognitive rehabilitation in cardiac surgery patients due to a significant effect on attentional and executive functions. This study aimed to compare the neuropsychological changes in patients who have undergone two variants of multi-tasking training and a control group in the early postoperative period of coronary artery bypass grafting (CABG). METHODS: One hundred and ten CABG patients were divided into three groups: cognitive training (CT) I (a postural balance task with mental arithmetic, verbal fluency, and divergent tasks) ( n = 30), CT II (a simple visual-motor reaction with mental arithmetic, verbal fluency, and divergent tasks) ( n = 40), and control ( n = 40)...

BACKGROUND: Functional assessment of right ventricle (RV) using gated myocardial perfusion single-photon emission computed tomography (MPS) heavily relies on the precise extraction of right ventricular contours. PURPOSE: In this paper, we present a new deep-learning-based model integrating both the spatial and temporal features in gated MPS images to perform the segmentation of the RV epicardium and endocardium. METHODS: By integrating the spatial features from each cardiac frame of the gated MPS and the temporal features from the sequential cardiac frames of the gated MPS, we developed a Spatial-Temporal V-Net (ST-VNet) for automatic extraction of RV endocardial and epicardial contours...

IMPORTANCE: Perioperative neurocognitive disorder, particularly postoperative cognitive impairment, is common and associated with multiple medical and social adversities, although data from China are lacking. OBJECTIVE: To examine the incidence, trajectory, and risk factors for subjective cognitive and short-term memory impairment after surgery in the Chinese population. DESIGN, SETTING, AND PARTICIPANTS: This cohort study used data from the China Surgery and Anesthesia Cohort to assess surgical patients aged 40 to 65 years from 2 medical centers between July 15, 2020, and March 31, 2023, with active follow-up within 1 year after the surgery...

Atherosclerotic cardiovascular disease (ASCVD), which includes coronary heart disease (CHD) and ischemic stroke, is the leading cause of mortality globally. According to the European Society of Cardiology (ESC), 26 million people worldwide have heart disease, with 3.6 million diagnosed each year. Early detection of heart disease will aid in lowering the mortality rate. The lack of diversity in training data and the difficulty in comprehending the findings of complicated AI models are the key issues in current research for heart disease prediction using artificial intelligence...

Long-term remote patients monitoring implies minimal discomfort and reliability throughout the study period. These requirements are fulfilled by portable (wearable) patient devices, with low consumption, which transmit data wirelessly, at a short distance, to a mobile communication device (GSM) and through it, to a remote end recipient - doctor, medical center or a hospital server. The data transfer technology requires the monitored person to perform a sequence of actions, such as: selecting the appropriate application on the mobile phone, establishing a connection between the patient module and the phone, recording the data in the phone's memory, starting the data transfer from the phone to the final receiver...

Cardiovascular disorders are often diagnosed using an electrocardiogram (ECG). It is a painless method that mimics the cyclical contraction and relaxation of the heart's muscles. By monitoring the heart's electrical activity, an ECG can be used to identify irregular heartbeats, heart attacks, cardiac illnesses, or enlarged hearts. Numerous studies and analyses of ECG signals to identify cardiac problems have been conducted during the past few years. Although ECG heartbeat classification methods have been presented in the literature, especially for unbalanced datasets, they have not proven to be successful in recognizing some heartbeat categories with high performance...

This article presents a quasi-experiment (N = 79 university students) testing whether individual differences in action-state orientation moderate primed cognitive conflict's effects on sympathetically mediated cardiac response during task performance reflecting effort. Action control theory posits that action-oriented individuals are less receptive to distracting affective stimuli during goal pursuit than state-oriented individuals because action-orientation is related to higher volitional skills...

BACKGROUND: Early detection of clinical deterioration among hospitalized patients is a clinical priority for patient safety and quality of care. Current automated approaches for identifying these patients perform poorly at identifying imminent events. OBJECTIVE: Develop a machine learning algorithm using pager messages sent between clinical team members to predict imminent clinical deterioration. DESIGN: We conducted a large observational study using long short-term memory machine learning models on the content and frequency of clinical pages...

OBJECTIVES: To investigate the effects of remimazolam on postoperative cognitive function, intraoperative hemodynamics, and oxygenation in older patients undergoing lobectomy. DESIGN: A prospective, double-blind, randomized, controlled study. SETTING: A university hospital. PARTICIPANTS: Eighty-four older patients with lung cancer who underwent lobectomy, aged ≥65 years. INTERVENTIONS: Patients were divided randomly into the remimazolam (group R) and propofol (group P) groups...

We sought to determine the cardiac ultrasound view of greatest quality using a machine learning (ML) approach on a cohort of transthoracic echocardiograms (TTE) with abnormal left ventricular (LV) systolic function. We utilize an ML model to determine the TTE view of highest quality when scanned by sonographers. A random sample of TTEs with reported LV dysfunction from 09/25/2017-01/15/2019 were downloaded from the regional database. Component video files were analyzed using ML models that jointly classified view and image quality...

Phenotypic plasticity, or adaptability, of a cell determines its ability to survive and function within changing cellular environments. Changes in the mechanical environment, ranging from stiffness of the extracellular matrix (ECM) to physical stress such as tension, compression, and shear, are critical environmental cues that influence phenotypic plasticity and stability. Furthermore, an exposure to a prior mechanical signal has been demonstrated to play a fundamental role in modulating phenotypic changes that persist even after the mechanical stimulus is removed, creating stable mechanical memories...

Cardiovascular and cerebrovascular diseases are prevalent in individuals with type 2 diabetes (T2D). Among people with T2D aged over 70 years, up to 45% might have cognitive dysfunction. Cardiorespiratory fitness (V˙O2 max) correlates with cognitive performances in healthy younger and older adults, and individuals with cardiovascular diseases (CVD). The relationship between cognitive performances, V˙O2 max, cardiac output and cerebral oxygenation/perfusion responses during exercise has not been studied in patients with T2D...

Fipronil (FPL), an insecticide belonging to the class of phenylpyrazoles, is associated with the widespread mortality of pollinator insects worldwide. Based on studies carried out on residual concentrations of FPL commonly found in the environment, in this work, we evaluated the sublethal effects of FPL on behavior and other neurophysiological parameters using the cockroach Nauphoeta cinerea as a biological model. Sublethal doses of FPL (0.1-0.001 µg/g) increased the time spent grooming and caused dose-dependent inhibition of exploratory activity, partial neuromuscular blockade in vivo, and irreversible negative cardiac chronotropism...

INTRODUCTION: Ischaemic anterior thalamic lesions are rare and can present with disturbances of behaviour and memory. We describe a patient with post-cardiac arrest thalamic stroke. CASE DESCRIPTION: A 63-year-old man presented with cardiac arrest, was resuscitated after receiving life support, and showed no lesions on computed tomography. Three days later, he presented with short-term memory disturbance and disorientation, with a de novo anterior thalamic lesion...

BACKGROUND: Females with cardiovascular disease seem more vulnerable to develop concomitant mental problems, such as depression and cognitive decline. Although exercise is shown beneficial in cardiovascular disease as well as in mental functions, these patients may be incapable or unmotivated to perform exercise. Whole body vibration (WBV) could provide a passive alternative to exercise. Aim of the present study was to compare WBV to exercise after isoproterenol (ISO)-induced myocardial damage in female rats, regarding effects on heart, brain and behavior...

Cardiac arrhythmia is an abnormal rhythm of the heartbeat and can be life-threatening Electrocardiogram (ECG) is a technology that uses an electrocardiograph machine to record a graph of the changes in electrical activity produced by the heart at each cardiac cycle. ECG can generally be used to check whether the examinee has arrhythmia, ion channel disease, cardiomyopathy, electrolyte disorder and other diseases. To reduce the workload of doctors and improve the accuracy of ECG signal recognition, a novel and lightweight automatic ECG classification method based on Convolutional Neural Network (CNN) is proposed...

Motivated by potential applications in cardiac research, we consider the task of reconstructing the dynamics within a spatiotemporal chaotic 3D excitable medium from partial observations at the surface. Three artificial neural network methods (a spatiotemporal convolutional long-short-term-memory, an autoencoder, and a diffusion model based on the U-Net architecture) are trained to predict the dynamics in deeper layers of a cube from observational data at the surface using data generated by the Barkley model on a 3D domain...

Cardiac abnormality detection from Electrocardiogram (ECG) signals is a common task for cardiologists. To facilitate efficient and objective detection, automated ECG classification by using deep learning based methods have been developed in recent years. Despite their impressive performance, these methods perform poorly when presented with cardiac abnormalities that are not well represented, or absent, in the training data. To this end, we propose a novel one-class classification based ECG anomaly detection generative adversarial network (GAN)...

BACKGROUND: Long-term follow-up of isolated rapid eye movement (REM) sleep behavior disorder (IRBD) patients reveals a high risk of α-synucleinopathies. OBJECTIVE: We explored the early clinical predictive factors of phenoconversion from IRBD to Parkinson's disease (PD) or dementia with Lewy bodies (DLB). METHODS: We assessed baseline office-based cognitive test scores (Montreal Cognitive Assessment [MoCA-J], Mini-Mental State Examination [MMSE], and Frontal Assessment Battery [FAB]), motor function, and olfactory function in 36 consecutive polysomnography (PSG)-confirmed IRBD patients with reduced metaiodobenzylguanidine (MIBG) accumulation...

As one of the most remarkable indicators of physiological health, heart rate (HR) has become an unfailing investigation for researchers. Unlike many existing methods, this article proposes an approach to implement short-time HR estimation from electrocardiography in time series missing patterns. Benefiting from the rapid development of deep learning, we adopted a bidirectional long short-term memory model (Bi-LSTM) and temporal convolution network (TCN) to recover complete heartbeat signals from those with durations are less than one cardiac cycle, and the estimated HR from recovered segment combining the input and the predicted output...