Filtered By:
Condition: Heart Failure
Education: Learning

This page shows you your search results in order of date. This is page number 5.

Order by Relevance | Date

Total 162 results found since Jan 2013.

Vascular adhesion protein-1 (VAP-1) in vascular inflammatory diseases
Vasa. 2022 Oct 6. doi: 10.1024/0301-1526/a001031. Online ahead of print.ABSTRACT Vascular adhesion protein-1 (VAP-1) also known as amino oxidase copper containing 3 (AOC3) is a pro-inflammatory and versatile molecule with adhesive and enzymatic properties. VAP-1 is a primary amine oxidase belonging to the semicarbazide-sensitive amine oxidase (SSAO) family, which catalyzes the oxidation of primary amines leading to the production of ammonium, formaldehyde, methylglyoxal, and hydrogen peroxide. VAP-1 is mainly expressed by endothelial cells, smooth muscle cells, adipocytes and pericytes. It is involved in a repertoire of bi...
Source: VASA. Zeitschrift fur Gefasskrankheiten. Journal for Vascular Diseases - October 6, 2022 Category: Surgery Authors: Marianna Danielli Roisin Clare Thomas Lauren Marie Quinn Bee Kang Tan Source Type: research

Clinical code usage in UK general practice: a cohort study exploring 18 conditions over 14 years
Conclusions This is an under-reported research area and the findings suggest the codes’ usage diversity for most conditions remained overall stable throughout the study period. Generated mental health code lists can last for a long time unlike cardiometabolic conditions and cancer. Adopting more consistent and less diverse coding would help improve data quality in primary care. Future research is needed following the transfer to the Systematised Nomenclature of Medicine Clinical Terms (SNOMED CT) coding.
Source: BMJ Open - July 25, 2022 Category: General Medicine Authors: Zghebi, S. S., Reeves, D., Grigoroglou, C., McMillan, B., Ashcroft, D. M., Parisi, R., Kontopantelis, E. Tags: Open access, General practice / Family practice Source Type: research

Prediction of incident atrial fibrillation in community-based electronic health records: a systematic review with meta-analysis
Conclusions Models externally validated for prediction of incident AF in community-based EHR demonstrate moderate predictive ability and high risk of bias. Novel methods may provide stronger discriminative performance. Systematic review registration PROSPERO CRD42021245093.
Source: Heart - June 10, 2022 Category: Cardiology Authors: Nadarajah, R., Alsaeed, E., Hurdus, B., Aktaa, S., Hogg, D., Bates, M. G. D., Cowan, C., Wu, J., Gale, C. P. Tags: Open access Arrhythmias and sudden death Source Type: research

Sensors, Vol. 22, Pages 4310: Cardiovascular Disease Diagnosis from DXA Scan and Retinal Images Using Deep Learning
In this study, we aimed at diagnosing CVD using a novel approach integrating information from retinal images and DXA data. We considered an adult Qatari cohort of 500 participants from Qatar Biobank (QBB) with an equal number of participants from the CVD and the control groups. We designed a case-control study with a novel multi-modal (combining data from multiple modalities—DXA and retinal images)—to propose a deep learning (DL)-based technique to distinguish the CVD group from the control group. Uni-modal models based on retinal images and DXA data achieved 75.6% and 77.4% accuracy, respective...
Source: Sensors - June 7, 2022 Category: Biotechnology Authors: Hamada R. H. Al-Absi Mohammad Tariqul Islam Mahmoud Ahmed Refaee Muhammad E. H. Chowdhury Tanvir Alam Tags: Article Source Type: research

Questionnaire-based exposome-wide association studies (ExWAS) reveal expected and novel risk factors associated with cardiovascular outcomes in the Personalized Environment and Genes Study
In conclusion, using statistics and machine learning, these findings identify novel potential risk factors for CVD, enable hypothesis generation, provide insights into the complex relationships between risk factors and CVD, and highlight the importance of considering multiple exposures when examining CVD outcomes.PMID:35605674 | DOI:10.1016/j.envres.2022.113463
Source: Environmental Research - May 23, 2022 Category: Environmental Health Authors: Eunice Y Lee Farida Akhtari John S House Ross J Simpson Charles P Schmitt David C Fargo Shepherd H Schurman Janet E Hall Alison A Motsinger-Reif Source Type: research

Risk of Chronic Conditions Found Higher Among Certain Groups With Depression, Anxiety
Women aged 20 to 60 with depression or anxiety were more likely to develop multiple chronic conditions over time compared with similarly aged women without depression or anxiety, according to areport published this week in JAMA Network Open. Women with comorbid anxiety and depression had an even greater risk of developing chronic conditions.Similarly, men with depression and/or anxiety at age 20 were more likely than those without depression or anxiety to develop chronic conditions.“Our findings support the need for managing comorbid depression and anxiety, which may help lower the risk of premature mortality associated ...
Source: Psychiatr News - May 5, 2022 Category: Psychiatry Tags: anxiety asthma cancer chronic conditions coronary artery disease depression diabetes hypertension JAMA Network Open men risk stroke women Source Type: research

Po-661-03 use of a deep learning algorithm to predict paroxysmal atrial fibrillation based on printed electrocardiographic records acquired during sinus rhythm
Atrial fibrillation (AF) is a common type of sustained arrhythmia worldwide. Asymptomatic AF, which occurs frequently, is associated with an increased incidence of ischemic stroke, heart failure, and mortality. A large number of patients with paroxysmal atrial fibrillation (PAF) remain undiagnosed due to the absence of electrocardiographic evidence of AF (AF-ECGs). If PAF could be predicted, targeted screening could improve early detection and treatment of this condition.
Source: Heart Rhythm - April 29, 2022 Category: Cardiology Authors: Yang Zhou, Yu Chen, Deyun Zhang, Shijia Geng, Guodong Wei, Ying Tian, Shenda Hong, XINGPENG LIU Source Type: research

A proteomic model shows potential as a surrogate end point for CVD risk
Nature Reviews Cardiology, Published online: 20 April 2022; doi:10.1038/s41569-022-00716-7A model generated using proteomics and machine learning that included 27 proteins was able to predict the 4-year risk of myocardial infarction, heart failure, stroke or all-cause death better than a clinical model and was sensitive to the adverse and beneficial changes in outcome.
Source: Nature Reviews Cardiology - April 20, 2022 Category: Cardiology Authors: Irene Fern ández-Ruiz Source Type: research

IJERPH, Vol. 19, Pages 4014: Automated Detection of Hypertension Using Continuous Wavelet Transform and a Deep Neural Network with Ballistocardiography Signals
Acharya Managing hypertension (HPT) remains a significant challenge for humanity. Despite advancements in blood pressure (BP)-measuring systems and the accessibility of effective and safe anti-hypertensive medicines, HPT is a major public health concern. Headaches, dizziness and fainting are common symptoms of HPT. In HPT patients, normalcy may be observed at one instant and abnormality may prevail during a long duration of 24 h ambulatory BP. This may cause difficulty in identifying patients with HPT, and hence there is a possibility that individuals may be untreated or administered insufficiently. Most importantly, u...
Source: International Journal of Environmental Research and Public Health - March 28, 2022 Category: Environmental Health Authors: Jaypal Singh Rajput Manish Sharma T. Sudheer Kumar and U. Rajendra Acharya Tags: Article Source Type: research

IJERPH, Vol. 19, Pages 3182: Predictive Model and Mortality Risk Score during Admission for Ischaemic Stroke with Conservative Treatment
Conclusions: It is possible to create a predictive model of mortality for patients with ischaemic stroke from which important advances can be made towards optimising the quality and efficiency of care. The model results are available within a few minutes of admission and would provide a valuable complementary resource for the neurologist.
Source: International Journal of Environmental Research and Public Health - March 8, 2022 Category: Environmental Health Authors: Mar ía Carmen Lea-Pereira Laura Amaya-Pascasio Patricia Mart ínez-Sánchez Mar ía del Mar Rodríguez Salvador Jos é Galván-Espinosa Luis T éllez-Ramírez Fernando Reche-Lorite Mar ía-José Sánchez Juan Manuel Garc ía-Torrecillas Tags: Article Source Type: research

Sensors, Vol. 22, Pages 1776: Compressed Deep Learning to Classify Arrhythmia in an Embedded Wearable Device
In conclusion, Mobilenet would be a more efficient model than Resnet to classify arrhythmia in an embedded wearable device.
Source: Sensors - February 24, 2022 Category: Biotechnology Authors: Kwang-Sig Lee Hyun-Joon Park Ji Eon Kim Hee Jung Kim Sangil Chon Sangkyu Kim Jaesung Jang Jin-Kook Kim Seongbin Jang Yeongjoon Gil Ho Sung Son Tags: Article Source Type: research

New ERLEADA ® (apalutamide) Analysis Demonstrates Rapid, Deep Prostate-Specific Antigen (PSA) Response in Patients with Metastatic Castration-Sensitive Prostate Cancer (mCSPC)
SAN FRANCISCO, Feb. 14, 2022 – The Janssen Pharmaceutical Companies of Johnson & Johnson today announced new real-world evidence data showing the initiation of ERLEADA® (apalutamide) results in high rates of rapid and deep prostate-specific antigen (PSA) response among patients with metastatic castration-sensitive prostate cancer (mCSPC). In a separate post-hoc analysis of the registrational Phase 3 SPARTAN and TITAN studies, rapid and deep PSA responses with ERLEADA® were associated with improvement in patient-reported outcomes (PROs) related to quality of life, physical wellbeing, pain, and fatigue intensity. The...
Source: Johnson and Johnson - February 14, 2022 Category: Pharmaceuticals Tags: Innovation Source Type: news