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1
Lazoryshynets, Vasyl, Igor Ditkivsky, Yaroslav Truba, Maksym Petrov, Oleksandra Mazur, and Iryna Perepeka. "Tendencies congenital heart diseases surgical correction. Ten years experience of Amosov National Institute of Cardiovascular Surgery." JOURNAL OF THE NATIONAL ACADEMY OF MEDICAL SCIENCES OF UKRAINE, no. 4 2021 (December 20, 2021): 271–78. http://dx.doi.org/10.37621/jnamsu-2021-4-6.
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Aim: To analyze the experience of treatment of congenital heart disease. Identify the proportions and ratios of surgical and endovascular treatments. Development of diagnostic service. To determine the impact of industry funding mechanisms on the development of endovascular surgery for congenital heart disease. Materials and methods: The tendencies of cardiac surgery development of congenital heart defects on the basis of the analysis of endovascular and surgical methods of treatment are considered. Own results of 10 years of experience in the treatment of congenital heart disease are presented. Results: An increase in the proportion of endovascular methods and a decrease in surgical treatments. The obtained data show a rapid increase in the share of medical procedures (from 48.9% to 89.4%) and a sharp decline in the share of diagnostic procedures (from 51.1% to 10.6%) in endovascular surgery. Early mortality after cardiac surgery in children is <5%, mortality after edovascular interventions - <1%. Ultrasound examination (ultrasound) of the heart - allows to detect 95% of all congenital heart defects and is shown to every citizen as a screening method. The influence of industry financing mechanisms on the development of endovascular surgery of congenital heart defects is shown. Expensive equipment began to be purchased at public expense, the number of equipment representatives on the market increased and, as a result, the number of endovascular procedures increased. Over the past 5 years, public funding for the needs of the industry has increased from 16 to 75%. Conclusions: Today, pediatric cardiology and cardiac surgery are reaping the fruits of the golden age in medical science. With the development of cardiac surgery, the number of operated patients increases every year. The successful outcome of treatment of patients with CHD depends on a comprehensive multidisciplinary team (Heart Team). New evidence-based approaches in resuscitation management allow to recover as soon as possible after the intervention. We see further development of the industry in the development of multidisciplinary teams to help patients with the CHD. Finally, we expect an increase in the regulatory burden and the cost of developing new treatments and diagnostics. Key words: congenital heart defects, endovascular methods, open heart operations, minimally invasive interventions, critical heart defects.
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Bartosh-Zelenaya, S. Yu. "Instrumental diagnostic methods for chronic coronary heart disease." Medical alphabet, no. 32 (January 13, 2021): 14–23. http://dx.doi.org/10.33667/2078-5631-2020-32-14-23.
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The review provides modern insights into methods for identifying a variety of scenarios that are currently classified as chronic coronary syndrome and involve different risks for subsequent cardiovascular events. The assessment of pre-test probability and determinants that enhance and reduce the possibility of diagnosing coronary heart disease are considered. The necessity and sequence of application of both simple instrumental methods of diagnostics of chronic coronary disease (electrocardiography, ambulatory electrocardiogram monitoring, exercise electrocardiogram, echocardiography) and more complex ones requiring specially trained personnel and modern equipment (stress echocardiography, computed tomography and invasive coronary angiography) are discussed. The recommended modern diagnostic algorithm in symptomatic patients with suspected coronary heart disease is presented.
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Ravi Shankar Kumar, Atinder Pal Singh, Loveleen, and Amrinder Singh. "A Meta Analysis on Cardiac Vascular Disease with Obesity." Journal for Research in Applied Sciences and Biotechnology 1, no. 3 (August 19, 2022): 78–85. http://dx.doi.org/10.55544/jrasb.1.3.10.
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Increasing evidence suggests that inflammatory and immunological factors present in the general population play a role in the pathogenesis of cardiovascular disease in RA. More than that, RA is treated with a wide range of drugs, many of which have the potential to alter cardiovascular function. Non-steroidal anti-inflammatory medicines (NSAIDs) have been linked to an increased risk, whereas some treatments, like methotrexate and TNF inhibitors, have been linked to a reduced risk. Cardiac catheterization is just one of several possible procedures that can be done on the heart. More than a million people in the United States get cardiac catheterization each year. [1] Any time a surgeon makes incisions into a patient, they must be ready for the possibility of complications, whether they arise from the patient or the surgery itself. Fortunately, the prevalence of these issues has decreased considerably in recent years thanks to developments in cardiac catheterization equipment, advances in the experience of the operators, and the introduction of novel methods. The term "cardiac catheterization" can refer to either a right heart or a left heart catheterization, or both. Depending on the patient's condition, interventional cardiologists can do either diagnostic or therapeutic operations. The dangers and difficulties that can arise during a diagnostic cardiac catheterization are briefly discussed in this article.
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Oluyemi, Aderemi Omololu, Hammed Ninalowo, Chris Iwuchukwu, and Evaristus Chukwudike. "Successful minimal invasive treatment of massive colonic bleeding from a pseudoaneurysm in a Nigerian with end-stage kidney disease: A case report." Calabar Journal of Health Sciences 6 (April 29, 2022): 51–53. http://dx.doi.org/10.25259/cjhs_16_2021.
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Emergency presentation of some rare causes of massive colonic bleeding with clinical hemodynamic instability often presents challenging diagnostic and therapeutic dilemmas. This is more so in a resource-limited locality such as ours where there is a dearth of technical expertise and equipment available to handle such unusual cases. This report presents a case of massive colonic bleed from a pseudoaneurysm of a branch of the ileocolic artery which had a fistulous communication with the cecum and was successfully treated with minimally invasive interventional radiology procedure in Lagos, Nigeria.
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Meiliana, Anna, and Andi Wijaya. "Novel Biomarkers in Cardiovascular Disease: A Review." Indonesian Biomedical Journal 2, no. 3 (December 1, 2010): 66. http://dx.doi.org/10.18585/inabj.v2i3.122.
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BACKGROUND: The investigation of novel circulating serum and plasma biomarkers in patients with cardiovascular disease has been accelerating at a remarkable pace. New markers or tests are often presented too early to the medical profession, potentially leading to overuse and, thus, extra burden and costs to patients, the healthcare industry, and the economy. The challenge for clinicians and medical researchers is how to optimally apply existing and new markers/tests.CONTENT: Biomarkers are biological parameters that can be objectively measured and quantified as indicators of normal biologic processes, pathogenic processes, or responses to a therapeutic intervention. Typically thought of as disease process screening, diagnosing, or monitoring tools, biomarkers may also be used to determine disease susceptibility and eligibility for specific therapies. Cardiac biomarkers are protein components of cell structures that are released into circulation when myocardial injury occurs. They play a pivotal role in the diagnosis, risk stratification, and treatment of patients with chest pain and suspected acute coronary syndrome (ACS) as well as those with acute exacerbations of heart failure.SUMMARY: Active investigation has brought forward an increasingly large number of novel candidate markers but few have withstood the test of time and become integrated into contemporary clinical care because of their readily apparent diagnostic, prognostic, and/or therapeutic utility. With regard to the more novel biomarkers, careful thought is needed with regard to the appropriate target populations for discovery and validation, as well as the criteria used to sort out the contenders from the pretenders.KEYWORDS: biomarker, cardiovascular disease, atherosclerosis, acute myocardial infarction, heart failure, risk stratification, diagnosis, prognosis
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Amin, Elena K., Adrienne Campbell-Washburn, and Kanishka Ratnayaka. "MRI-Guided Cardiac Catheterization in Congenital Heart Disease: How to Get Started." Current Cardiology Reports 24, no. 4 (February 2, 2022): 419–29. http://dx.doi.org/10.1007/s11886-022-01659-8.
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Abstract Purpose of Review Cardiac magnetic resonance imaging provides radiation-free, 3-dimensional soft tissue visualization with adjunct hemodynamic data, making it a promising candidate for image-guided transcatheter interventions. This review focuses on the benefits and background of real-time magnetic resonance imaging (MRI)-guided cardiac catheterization, guidance on starting a clinical program, and recent research developments. Recent Findings Interventional cardiac magnetic resonance (iCMR) has an established track record with the first entirely MRI-guided cardiac catheterization for congenital heart disease reported nearly 20 years ago. Since then, many centers have embarked upon clinical iCMR programs primarily performing diagnostic MRI-guided cardiac catheterization. There have also been limited reports of successful real-time MRI-guided transcatheter interventions. Growing experience in performing cardiac catheterization in the magnetic resonance environment has facilitated practical workflows appropriate for efficiency-focused cardiac catheterization laboratories. Most exciting developments in imaging technology, MRI-compatible equipment and MRI-guided novel transcatheter interventions have been limited to preclinical research. Many of these research developments are ready for clinical translation. Summary With increasing iCMR clinical experience and translation of preclinical research innovations, the time to make the leap to radiation-free procedures is now.
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Bhardwaj, Tanu, Lakshmi Ramana, and Tarun Sharma. "Current Advancements and Future Road Map to Develop ASSURED Microfluidic Biosensors for Infectious and Non-Infectious Diseases." Biosensors 12, no. 5 (May 20, 2022): 357. http://dx.doi.org/10.3390/bios12050357.
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Better diagnostics are always essential for the treatment and prevention of a disease. Existing technologies for detecting infectious and non-infectious diseases are mostly tedious, expensive, and do not meet the World Health Organization’s (WHO) ASSURED (affordable, sensitive, specific, user-friendly, rapid and robust, equipment-free, and deliverable to end user) criteria. Hence, more accurate, sensitive, and faster diagnostic technologies that meet the ASSURED criteria are highly required for timely and evidenced-based treatment. Presently, the diagnostics industry is finding interest in microfluidics-based biosensors, as this integration comprises all qualities, such as reduction in the size of the equipment, rapid turnaround time, possibility of parallel multiple analysis or multiplexing, etc. Microfluidics deal with the manipulation/analysis of fluid within micrometer-sized channels. Biosensors comprise biomolecules immobilized on a physicochemical transducer for the detection of a specific analyte. In this review article, we provide an outline of the history of microfluidics, current practices in the selection of materials in microfluidics, and how and where microfluidics-based biosensors have been used for the diagnosis of infectious and non-infectious diseases. Our inclination in this review article is toward the employment of microfluidics-based biosensors for the improvement of already existing/traditional methods in order to reduce efforts without compromising the accuracy of the diagnostic test. This article also suggests the possible improvements required in microfluidic chip-based biosensors in order to meet the ASSURED criteria.
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Khan, Ali Haider, Muzammil Hussain, and Muhammad Kamran Malik. "Cardiac Disorder Classification by Electrocardiogram Sensing Using Deep Neural Network." Complexity 2021 (March 23, 2021): 1–8. http://dx.doi.org/10.1155/2021/5512243.
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Cardiac disease is the leading cause of death worldwide. Cardiovascular diseases can be prevented if an effective diagnostic is made at the initial stages. The ECG test is referred to as the diagnostic assistant tool for screening of cardiac disorder. The research purposes of a cardiac disorder detection system from 12-lead-based ECG Images. The healthcare institutes used various ECG equipment that present results in nonuniform formats of ECG images. The research study proposes a generalized methodology to process all formats of ECG. Single Shoot Detection (SSD) MobileNet v2-based Deep Neural Network architecture was used to detect cardiovascular disease detection. The study focused on detecting the four major cardiac abnormalities (i.e., myocardial infarction, abnormal heartbeat, previous history of MI, and normal class) with 98% accuracy results were calculated. The work is relatively rare based on their dataset; a collection of 11,148 standard 12-lead-based ECG images used in this study were manually collected from health care institutes and annotated by the domain experts. The study achieved high accuracy results to differentiate and detect four major cardiac abnormalities. Several cardiologists manually verified the proposed system’s accuracy result and recommended that the proposed system can be used to screen for a cardiac disorder.
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.., Abedallah Z., Rasha .., and Saleh A. Almutairi. "Early Detection of Cardiovascular Diseases using Deep Learning Feature Fusion and MRI Image Analysis." Fusion: Practice and Applications 8, no. 2 (2022): 16–24. http://dx.doi.org/10.54216/fpa.080202.
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Deaths from cardiovascular disease (CVD) are more common than any other kind of mortality in the world. Electrocardiograms, two-dimensional echocardiograms, and stress tests are only a few of the diagnostic tools available to combat the rising incidence of cardiovascular disease. Since the electrocardiogram (ECG) is a clinical therapeutic agent that does not need any intrusive procedures, it may be used to diagnose cardiovascular disease (CVD) early and prescribe the appropriate treatment to prevent its fatal consequences. However, it may be time-consuming and demanding for a physical examination to interpret all these signals from various pieces of equipment, especially if they are non-stationary and repeating. It is necessary to use a computer-assisted model for rapid and precise prediction of CVDs since the Heart Signal from an ECG machine is not a stationary sign, the differences may not be repeated and may manifest at different intervals. In this paper, we offer a fully deep convolutional neural network-based automated diagnosis technique for cardiovascular illness. In order to extract those form characteristics from the Kaggle cardio-vascular disease dataset, CVD-MRI is employed in this detection method. In this case, the risk of cardiovascular disease is estimated using a completely deep convolution neural network and deep learning convolution filters (CVD). The suggested operation's main goal is to improve the accuracy of completely deep convolution neural network while simultaneously reducing the complexity of the computation and the cost function. Accuracy of 88 percent is achieved by the proposed fully deep convolutional neural network.
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Mukasheva, Gulbarshyn, Tolkyn Bulegenov, Vladimir Kolyado, and Altynai Kazyeva. "Rural-urban Health Disparities for Cardiovascular Disease in the Republic of Kazakhstan." Open Access Macedonian Journal of Medical Sciences 9, E (November 25, 2021): 1331–37. http://dx.doi.org/10.3889/oamjms.2021.7598.
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BACKGROUND: An important global public health problem in many economically developed countries, in particular Kazakhstan, is the leading cause of incidence of and mortality from cardiovascular disease (CVD). AIM: The purpose of our study was to compare incidence and mortality from CVD in urban and rural areas of the Republic of Kazakhstan in 2019 based on statistics. METHODS: We conducted a descriptive study, which based on secondary data from the statistical reports on the Republic of Kazakhstan «Health of the Republic of Kazakhstan and the activities of health care organizations». Information from this database were generated by 14 provinces, three cities of republican significance and whole Kazakhstan. In addition, these indicators were divided for rural and urban settlements. RESULTS: Data from our epidemiological study of the incidence of and mortality from cardiovascular disease (CVD) in all provinces indicate a relatively high incidence of and mortality from CVD among urban population of the Republic of Kazakhstan. Among urban residents (per 100,000 population), the highest incidence rates of CVD was in Akmola province (3771.7), the ischemic heart disease (IHD) was in Almaty city (850.8), arterial hypertension (AH) was in Akmola province (2623.8), acute myocardial infarction was in the North Kazakhstan province (212.9), the highest mortality from CVD was in Karaganda province (365), the IHD was in East Kazakhstan province (135.4). Among rural residents (per 100,000 population), there are high incidence rates of CVD in the East Kazakhstan province (3452.8), the IHD in Zhambyl province (713.1), AH in the East Kazakhstan province (1871.4), acute myocardial infarction in Atyrau province (148.3), the highest mortality from CVD was in East Kazakhstan province (201.9), and the IHD also in East Kazakhstan province (77.3). CONCLUSIONS: There is rural-urban health inequality in many countries and CVD is not the exclusion. In the Republic of Kazakhstan, the rural population has got lower rates of incidence and mortality. This may be due to the bad access to medical facilities that are typical for rural areas of Kazakhstan and the shortage of modern diagnostic equipment which may interfere with timely diagnosis.
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Islam, Mohammad Rashemdul, Shamima Parvin Laskar, and Darryl Macer. "A Study on Service Availability and Readiness Assessment of Non-Communicable Diseases Using the WHO Tool for Gazipur District in Bangladesh." Bangladesh Journal of Bioethics 7, no. 2 (July 23, 2016): 1–13. http://dx.doi.org/10.3329/bioethics.v7i2.30785.
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Non-communicable diseases (NCDs) disproportionately affect low and middle-income countries where nearly three quarters of NCD deaths occur. Bangladesh is also in NCD burden. This cross-sectional study was done on 50 health facilities centres at Gazipur district in Bangladesh from July 2015 to December 2015 to introduce SARA for better monitoring and evaluation of non-communicable diseases health service delivery. The General Service readiness index score was 61.52% refers to the fact that about 62% of all the facilities were ready to provide general services like basic amenities, basic equipment, standard precautions for infection prevention, and diagnostic capacity and essential medicines to the patients. But in case of non-communicable diseases, among all the health facilities 40% had chronic respiratory disease and cardiovascular diseases diagnosis/ management and only 32% had availability of diabetes diagnosis/management. Overall readiness score was 52% in chronic respiratory disease, 73% in cardiovascular disease and 70% in diabetes. Therefore, service availability and readiness of the health facilities to provide NCD related health services were not up to the mark for facing future targets. A full-scale census survey of all the facilities of the study area would give a better understanding of the availability and service readiness.
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Gaudry, Marine, Donato Vairo, Marion Marlinge, Melanie Gaubert, Claire Guiol, Giovanna Mottola, Vlad Gariboldi, et al. "Adenosine and Its Receptors: An Expected Tool for the Diagnosis and Treatment of Coronary Artery and Ischemic Heart Diseases." International Journal of Molecular Sciences 21, no. 15 (July 27, 2020): 5321. http://dx.doi.org/10.3390/ijms21155321.
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Adenosine is an endogenous nucleoside which strongly impacts the cardiovascular system. Adenosine is released mostly by endothelial cells and myocytes during ischemia or hypoxia and greatly regulates the cardiovascular system via four specific G-protein-coupled receptors named A1R, A2AR, A2BR, and A3R. Among them, A2 subtypes are strongly expressed in coronary tissues, and their activation increases coronary blood flow via the production of cAMP in smooth muscle cells. A2A receptor modulators are an opportunity for intense research by the pharmaceutical industry to develop new cardiovascular therapies. Most innovative therapies are mediated by the modulation of adenosine release and/or the activation of the A2A receptor subtypes. This review aims to focus on the specific exploration of the adenosine plasma level and its relationship with the A2A receptor, which seems a promising biomarker for a diagnostic and/or a therapeutic tool for the screening and management of coronary artery disease. Finally, a recent class of selective adenosine receptor ligands has emerged, and A2A receptor agonists/antagonists are useful tools to improve the management of patients suffering from coronary artery disease.
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Lei, Lei, Fan Liao, Lei Tan, Deyong Duan, Yang Zhan, Naidong Wang, Yuge Wang, et al. "LAMP Coupled CRISPR-Cas12a Module for Rapid, Sensitive and Visual Detection of Porcine Circovirus 2." Animals 12, no. 18 (September 14, 2022): 2413. http://dx.doi.org/10.3390/ani12182413.
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Porcine circovirus 2 (PCV2) is the main pathogen of porcine circovirus-associated disease (PCVAD), which can cause considerable economic loss to the pig industry. The diagnosis of PCVAD is complicated and requires a series of clinical, pathological, and virological methods. Therefore, a rapid, highly sensitive, on-site, and visual diagnostic approach would facilitate dealing with the spread of PCV2. In this study, we intended to establish a new and effective PCV2 detection method through combining the no specific equipment requirement advantage of loop-mediated isothermal amplification (LAMP) with the property of clustered regular interspaced short palindromic repeats (CRISPR)/Cas12a system possessing the huLbCas12a collateral cleavage activity able to cleave single-stranded DNA fluorophore quencher probe sensor (designed as LAPM-CRISPR). Following a series of optimizations of its reaction conditions, this LAMP-CRISPR-based PCV2 detection could be conducted in constant temperature equipment, with the result reflected in a direct visual readout way. This established PCV2 detection approach presented fine sensitivity, rapidity, specificity, and reliability, as demonstrated by a low detectable limit of 1 copy/μL, completed within an hour, no cross-reaction with main porcine DNA or RNA viruses like PCV1, PCV3, and PEDV, and a 100% coincidence rate with that of the quantitative PCR (qPCR) method in the evaluation of 30 clinical blood samples, respectively. Therefore, this novel method makes rapid, on-site, visual, highly sensitive, and specific detection of PCV2 possible, facilitating the prevention of this pathogen in the field.
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Nastenko, Ievgen, Vitaliy Maksymenko, Sergiy Potashev, Volodymyr Pavlov, Vitalii Babenko, Sergiy Rysin, Oleksandr Matviichuk, and Vasil Lazoryshinets. "Random Forest Algorithm Construction for the Diagnosis of Coronary Heart Disease Based on Echocardiography Video Data Streams." Innovative Biosystems and Bioengineering 5, no. 1 (April 6, 2021): 61–69. http://dx.doi.org/10.20535/ibb.2021.5.1.225794.
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Background. Recent studies show that cardiovascular diseases, including coronary heart disease, are the leading causes of death and one of the main factors of disability worldwide. The detection of cases of this type of disease over the past 30 years has increased from 271 million to 523 million and the number of deaths – from 12.1 million to 18.6 million. Cardiovascular diseases are the main cause of death among the population of Ukraine and, according to this indicator, the country remains one of the world leaders. Coronary heart disease is the leading factor in the loss of health in Ukraine and modern diagnostic methods, including machine learning algorithms, are increasingly being used for timely detection. Objective. According to the data of speckle-tracking echocardiography using the random forest method, construct classification algorithms for diagnosing violations of the kinematics of left ventricular contractions in patients with coronary heart disease at rest, and when using an echostress test with a dobutamine test. Methods. Speckle-tracking echocardiography was used to examine 40 patients with coronary heart disease and 16 in whom no cardiac pathology was found. Echocardiography was recorded in B mode in three positions: along the long axis, in 4-chamber, and 2-chamber positions. In total, 6245 frames of the video stream were used: 1871 – without cardiac abnormalities, and 4374 – in the presence of pathology during the examination. 56 patients (2509 frames of video data) were examined without the use of a dobutamine test and 38 patients (3736 frames of video data) – using an echostress test with a dobutamine test if no disturbances were found at rest. Dobutamine doses of 10, 20, and 40 mcg were administered under the supervision of an anesthesiologist. The data of texture analysis of images were used as informative features. To build an algorithm for detecting coronary heart disease the random forest algorithm was applied. Results. At the first stage of the study, the diagnostic algorithms norma–pathology for the state of rest and dobutamine doses of 10, 20, and 40 mcg were constructed. Before applying the algorithm the samples were randomly divided into training (70%) and test (30%). The classifiers were evaluated for accuracy, sensitivity, and specificity. According to the test samples, the accuracy of diagnostic conclusions varied from 97 to 99%. At the second stage of the study, to increase the versatility of the models, the classifier was built for all images, without dividing them into dobutamine doses. The accuracy for the test samples also ranged from 96.6 to 97.8%. To construct diagnostic algorithms by the random forest method the data of texture analysis of images were used. Conclusions. High-precision classification models were obtained using the random forest algorithm. The developed models can be applied to the analysis of echocardiograms obtained in B mode on equipment that is not equipped with the speckle tracking technology.
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Flores, Nellyzeth, Marco A. Reyna, Roberto L. Avitia, Jose Antonio Cardenas-Haro, and Conrado Garcia-Gonzalez. "Non-Invasive Systems and Methods Patents Review Based on Electrocardiogram for Diagnosis of Cardiovascular Diseases." Algorithms 15, no. 3 (February 28, 2022): 82. http://dx.doi.org/10.3390/a15030082.
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Cardiovascular disease (CVD) is a global public health problem. It is a disease of multifactorial origin, and with this characteristic, having an accurate diagnosis of its incidence is a problem that health personnel face every day. That is why having all the indispensable tools to achieve optimal results is of utmost importance. Time is an essential factor when identifying heart problems, specialists look for and develop options to improve this aspect, which requires a thorough analysis of the patient, electrocardiograms being the factor standard for diagnosis and monitoring of patients. In this paper, we review patents and combined systems for the analysis of existing electrocardiogram signals, specific to cardiovascular diseases. All these methods and equipment have the purpose of giving an accurate diagnosis and a prediction of the presence of CVD in patients with positive risk factors. These are considered as the first diagnostic option, based on the guidelines already established in the field of preventive cardiology. The methodology consists of the searching of specific electrocardiography and cardiovascular disease subjects, taking as a reference the use of various patent databases. A total of 2634 patents were obtained in the consulted databases. Of that total, only 30 patents that met all the previous criteria were considered; furthermore, a second in-depth review of their information was conducted. It is expected that studying and reviewing these patents will allow us to know the variety of tools available for the different pathologies that make up CVD, not only for its immediate diagnosis because, as mentioned, the time factor is decisive for the best forecast but also to allow us to follow up on all the cases that arise, being able to provide a better quality of life to patients with CVD or even being able to lead them to a full recovery.
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Hopkins, Joshua, and Datonye B. Omunguye-George. "AI Powered Echocardiography." International Journal on Bioinformatics & Biosciences 14, no. 1 (March 10, 2024): 01–08. http://dx.doi.org/10.5121/ijbb.2024.14101.
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The purpose of this paper is to discuss the current technological developments in diagnostic cardiovascular care. Echocardiography, a widely known imaging tool, extracts insights about a patients’ cardiac anatomy and perform necessary treatments or procedures based on their diagnoses. AI models respond to vast amounts of raw cardiac data and use Deep Learning algorithms to identify images with remarkable speed and accuracy. AI applications in computer vision offer key benefits in the healthcare industry. Companies such as Siemens are the key players – the commercialization of new AI technology has enabled healthcare organizations to streamline workflows, reduce errors, and lower costs.Potentially, there will be no reproducibility issues thereby redirecting clinical efforts towards patient treatment planning and research to prevent uptrends of heart disease.
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Luo, Yifan, Chen Gao, Wujie Chen, Kefeng Zhou, and Maosheng Xu. "Molecular Magnetic Resonance Imaging with Contrast Agents for Assessment of Inflammatory Bowel Disease: A Systematic Review." Contrast Media & Molecular Imaging 2020 (May 6, 2020): 1–9. http://dx.doi.org/10.1155/2020/4764985.
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Background and Aims. Magnetic resonance imaging (MRI) has taken an important role in the diagnosis of inflammatory bowel diseases (IBD). In the wake of current advances in nanotechnology, the drug delivery industry has seen a surge of nanoparticles advertising high specificity in target imaging. Given the rapid development of the field, this review has assembled related articles to explore whether molecular contrast agents can improve the diagnostic capability on gastrointestinal imaging, especially for IBD. Methods. Relevant articles published between 1998 and 2018 from a literature search of PubMed and EMBASE were reviewed. Data extraction was performed on the studies’ characteristics, experimental animals, modelling methods, nanoparticles type, magnetic resonance methods, and means of quantitative analysis. Results. A total of 8 studies were identified wherein the subjects were animals, and all studies employed MR equipment. One group utilized a perfluorocarbon solution and the other 7 groups used either magnetic nanoparticles or gadolinium- (Gd-) related nanoparticles for molecular contrast. With ultrasmall superparamagnetic iron oxide (USPIO) particles and Gd-related nanoparticles, signal enhancements were found in the mucosa or with focal lesion of IBD-related model in T1-weighted images (T1WI), whereas superparamagnetic iron oxide (SPIO) particles showed a signal decrease in the intestinal wall of the model in T1WI or T2-weighted images. The signal-to-noise ratio (SNR) was employed to analyze bowel intensity in 3 studies. And the percentage of normalized enhancement was used in 1 study for assessing the severity of inflammation. Conclusion. Molecular MRI with contrast agents can improve the early diagnosis of IBD and quantitate the severity of inflammation in experimental studies.
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Zu, Haoyu, Rongkuan Sun, Jiaxin Li, Xing Guo, Min Wang, Wei Guo, and Xiaojun Wang. "Development of a Real-Time Recombinase-Aided Amplification Method for the Rapid Detection of Streptococcus equi subsp. equi." Microorganisms 12, no. 4 (April 11, 2024): 777. http://dx.doi.org/10.3390/microorganisms12040777.
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Streptococcus equi subspecies equi (S. equi) is the causative pathogen of strangles in horses, donkeys, and other equine animals. Strangles has spread globally and causes significant losses to the horse industry. In response to the urgent need for effective disease control, this study introduces a novel nucleic acid diagnostic method known as a real-time recombinase-assisted amplification (RAA) assay, developed based on the eqbE gene, for the rapid detection of S. equi nucleic acid. The real-time RAA method employs specifically designed probes and primers targeting the eqbE gene, enhancing the overall specificity and sensitivity of the detection. After efficiency optimization, this real-time RAA method can detect 10 or more copies of nucleic acid within 20 min. The method demonstrates high specificity for S. equi and does not cross-react with other clinically relevant pathogens. Real-time RAA diagnostic performance was evaluated using 98 nasal swab samples collected from horses and compared with the real-time PCR detection method. Results revealed that 64 and 65 samples tested positive for S. equi using real-time RAA and real-time PCR, respectively. The overall agreement between the two assays was 96.94% (95/98), with a kappa value of 0.931 (p < 0.001). Further linear regression analysis indicated a significant correlation in the detection results between the two methods (R2 = 0.9012, p < 0.0001), suggesting that the real-time RAA assay exhibits a detection performance comparable to that of real-time PCR. In conclusion, the real-time RAA assay developed here serves as a highly specific and reliable diagnostic tool for the detection of S. equi in equine samples, offering a potential alternative to real-time PCR methods. In conclusion, the real-time RAA nucleic acid diagnostic method, based on the eqbE gene, offers rapid and accurate diagnosis of S. equi, with the added advantage of minimal equipment requirements, thus contributing to the efficient detection of strangles in horses.
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Moshawrab, Mohammad, Mehdi Adda, Abdenour Bouzouane, Hussein Ibrahim, and Ali Raad. "Smart Wearables for the Detection of Cardiovascular Diseases: A Systematic Literature Review." Sensors 23, no. 2 (January 11, 2023): 828. http://dx.doi.org/10.3390/s23020828.
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Background: The advancement of information and communication technologies and the growing power of artificial intelligence are successfully transforming a number of concepts that are important to our daily lives. Many sectors, including education, healthcare, industry, and others, are benefiting greatly from the use of such resources. The healthcare sector, for example, was an early adopter of smart wearables, which primarily serve as diagnostic tools. In this context, smart wearables have demonstrated their effectiveness in detecting and predicting cardiovascular diseases (CVDs), the leading cause of death worldwide. Objective: In this study, a systematic literature review of smart wearable applications for cardiovascular disease detection and prediction is presented. After conducting the required search, the documents that met the criteria were analyzed to extract key criteria such as the publication year, vital signs recorded, diseases studied, hardware used, smart models used, datasets used, and performance metrics. Methods: This study followed the PRISMA guidelines by searching IEEE, PubMed, and Scopus for publications published between 2010 and 2022. Once records were located, they were reviewed to determine which ones should be included in the analysis. Finally, the analysis was completed, and the relevant data were included in the review along with the relevant articles. Results: As a result of the comprehensive search procedures, 87 papers were deemed relevant for further review. In addition, the results are discussed to evaluate the development and use of smart wearable devices for cardiovascular disease management, and the results demonstrate the high efficiency of such wearable devices. Conclusions: The results clearly show that interest in this topic has increased. Although the results show that smart wearables are quite accurate in detecting, predicting, and even treating cardiovascular disease, further research is needed to improve their use.
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Cherkashin, D. V., and A. V. Lyubimov. "The molecular marker of the preconditioning phenomenon HIF1α is a new pathway for early detection of visceral hypoxic conditions." Terapevticheskii arkhiv 92, no. 4 (May 19, 2020): 121–26. http://dx.doi.org/10.26442/00403660.2020.04.000473.
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Improvement and development of technologies for laboratory and instrumental examination of patients in recent years have greatly facilitated the diagnosis of ischemic myocardial damage. However, a decrease in the rating of cardiovascular diseases is not expected in the short term. This is due to an increase in the life expectancy of the population, general aging of the population and improving diagnostic capabilities and the provision of medical care. The time for verification of the diagnosis of ischemic disease, simplified the decision on treatment tactics were significantly reduced by introduction of X-ray contrast visualization examination methods such as angiography, quantitative and qualitative laboratory tests, development of diagnostic criteria based on the results of ultrasound and electrophysiological examination methods. Unfortunately, all these techniques are secondary in nature and are applied, when organ damage is for the most part already irreversible. Full restoration of organs is possible only if the patient is successfully evacuated to the hospital and there are specialists of the appropriate level of experiebce, X-ray surgical equipment with suitable supplies or pharmacological agents, usefull for quickly restoration the patency of the great vessels and normal blood flow. A large number of studies appear on the phenomenon of preconditioning at the present stage of development of fundamental medical science. The purpose of this article is to reveal the possibilities of using molecular markers of the phenomenon of preconditioning in the framework of the early detection of hypoxic conditions, the assessment of their diagnostic use in the clinic and the prevention of hypoxia-associated diseases.
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MA, Taylor, Bennett CL, Schoen MW, and Hoque S. "Advances in artificial neural networks as a disease prediction tool." Journal of Cancer Research & Therapy 9, no. 1 (June 2, 2021): 1–11. http://dx.doi.org/10.14312/2052-4994.2021-1.
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Throughout the last decade, utilization of machine learning has seen a sharp rise in fields such as computing, transportation, engineering, and medicine. Artificial neural networks (ANNs) have demonstrated increased application due to their versatility and ability to learn from large datasets. The emergence of electronic health records has propelled healthcare into an era of personalized medicine largely aided by computers. This review summarizes the current state of ANNs as a predictive tool in medicine and the downfalls of reliance on a self-adjusting computer network to make healthcare decisions. Medical ANN studies can be grouped into three categories - diagnosis, classification, and prediction, with diagnostic studies currently dominating the field. However, recent trends show prediction studies may soon outnumber the remaining categories. ANN prediction studies dominate in fields such as cardiovascular disease, neurologic disease, and osteoporosis. Neural networks consistently show higher predictive accuracy than industry standards. But several pitfalls are preventing mainstream adoption. Clinicians often rely on situational pearls to make complex healthcare decisions, ANNs often do not account for intuitive variables during their analysis. Instead, ANNs rely on incomplete patient data and ‘black box’ computing to make decisions that are not completely transparent to the end-user. This has led to ‘runaway’ networks that may ultimately make inaccurate and harmful decisions. This review emphasizes the extensive potential of machine learning in medicine and the obstacles that must be overcome to utilize its full potential.
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Valente, Serafina, Furio Colivicchi, Maura Giuseppina Francese, Andrea Di Lenarda, Loris Roncon, Adriano Murrone, Pasquale Caldarola, et al. "ANMCO POSITION PAPER: The cardiological clinical activities in the transition phase of the COVID-19 pandemic." European Heart Journal Supplements 22, Supplement_G (August 1, 2020): G233—G238. http://dx.doi.org/10.1093/eurheartj/suaa113.
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Abstract Infections by SARS CoV2 - COVID-19 became in a short time a worldwide health emergency. The present SARS-CoV-2 pandemic induced in a short time, an unprecedented impact on public health and on the pre-existing care pathways. In order to appropriately address this epidemiological emergency, urgent solutions were needed, such as remodelling or stopping hospitalization and deferrable clinical activities to avoid spreading the SARS-CoV-2 infection. After the first emergency lockdown phase, care pathways must guarantee healthcare to patients and preserve the safety of the healthcare personnel and of all the other subjects that refer to the cardiological surgeries. Rigorous prescriptive appropriateness of the requested exams with consequent reduction of unnecessary examinations is an essential requirement to preserve prioritized diagnostic and care pathways to patients in need, minimizing the risks connected to the SARS-CoV-2 contagion in hospitals. Telemedicine services represent a valid answer to cardiovascular disease patients’ need for care and assistance, including those in quarantine and voluntary isolation. These services successfully contribute to fight the spread of the virus guaranteeing at the same time therapy and support through remote services that must therefore be considered a resource to be implemented and enhanced. This document has to be used by the healthcare personnel working in hospitals and in district offices, if applicable, and aims at managing patients, in complete safety and considered not suspect/not probable (‘not at risk’) of SARS-CoV-2 infection, eligible for diagnostic activity and subsequent therapy in outpatient surgeries. In particular, this document provides indications for patient evaluation to prevent COVID-19 exposure, gives general indications on managing appointments and waiting rooms, on how to strictly adhere to environmental safety measures, on the proper use of Individual Protective Equipment (IPE). It also provides specific indications for outpatient service procedures, like electrocardiogram, cardiologic examination, cardiologic checkup, Dynamic Holter Electrocardiogram, Transthoracic Echocardiography, Echo Stress, Transoesophageal Echocardiography, Bike Ergometer stress test, Ergospirometry, Outpatient Checkup of implantable electronic cardiac devices.
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Gempur Santoso. "The Industrial Ergonomics Approach Influences Workforce Fatigue and Health and Increases Productivity." International Journal of Integrative Sciences 2, no. 11 (November 30, 2023): 1629–38. http://dx.doi.org/10.55927/ijis.v2i11.6655.
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Work should remain safe, comfortable and not tiring, but should result in good work results or good productivity. To achieve this, we need an ergonomic approach in industry so that work is not tiring and productivity increases. In this paper it is planned in a descriptive manner. Data is taken from various opinions in literature or called literature studies. Analysis was also carried out descriptively. Conclusion, Equipment adapted to the user's anthropometry will make the work posture and work range better, and work without bending over, so that work does not get tired quickly. The physical environment of the floor and ventilation that meet the requirements will be free from the occurrence of dizziness and headaches for workers; environment many biological microorganisms especially bacteria, fungi and viruses some occupations are particularly susceptible to contracting pneumonia while carrying out work duties; chemical environment exposure to polluting gases in the form of NOx, Sox, HC, and greenhouse gas particles will affect the health of workers such as damaging blood hemoglobin composition, upper respiratory tract infections, throat irritation, pneumococcal disease, cardiovascular disease and cancer, and exposure to benzene has an effect on hemoglobin and erythrocyte abnormalities. Therefore, if the industrial environment is healthy, the workforce will also be healthy
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García, Emilio Ignacio, Mercedes Guilabert, Rubén Queiro, Irene Carrillo, and José Joaquín Mira. "Evaluating standards of care in psoriatic arthritis of the QUANTUM project (qualitative initiative to improve outcomes): results of an accreditation project in Spain." Rheumatology International 40, no. 11 (June 25, 2020): 1817–23. http://dx.doi.org/10.1007/s00296-020-04632-2.
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Abstract In Spain, the QUANTUM project has been promoted to reduce variability in clinical practice and improve the care and quality of life of people with psoriatic arthritis (PsA) by accrediting PsA units throughout the Spanish national health system. To present the results of this approach which sought to ensure an optimum level of quality for patients with PsA. Descriptive analysis of the self-assessments that the PsA units have carried out assessing their degree of compliance with the quality standards established in the QUANTUM project grouped into four blocks: shortening time to diagnosis; optimizing disease management; improving multidisciplinary collaboration; and improving patient monitoring. A total of 41 PsA units were self-evaluated. They met 64.1% of the defined quality standards. Optimize disease management obtained a higher level of standards compliance (72%) and improve multidisciplinary collaboration the lesser (63.9%). Accessibility to the treatments available for PsA in all hospitals was guaranteed (100%). Appropriate diagnostic equipment is available (97.6%). Compliance with specific quality standards leads to detect actions that should be implemented: quality of life assessment (9.8%), locomotor system assessment (12.2%), physical examination data record (14.6%), periodic cardiovascular risk assessment (17.1%). The QUANTUM project results make it possible to visualise how to care for patients with PsA is being developed in Spain. Problems identified in recent multinational reports are also identified in Spain.
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Samuneva-Zhelyabova, Marina, Ivan Spiroski, and Rositsa Markova. "P-541 WORK-RELATED DISEASES IN THE CONSTRUCTION SECTOR." Occupational Medicine 74, Supplement_1 (July 1, 2024): 0. http://dx.doi.org/10.1093/occmed/kqae023.1323.
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Abstract Introduction Technological processes in the construction industry accompanied by heavy construction equipment are risks for occupational accidents and work-related diseases. The aim of the present study is to set up the correlation between risk factors and the incidence of socially significant diseases. Materials and methods For the purpose of the study 362 workers in the construction sector were surveyed. The information obtained was processed using a descriptive and analytical methods. The descriptive statistics and analysis of relationships between individual statistical series were conducted throughout the Pearson 2 test for attributive data, i.e. T--test and Pearson correlation test for numerical series. Results All surveyed participants were Male and the mean age of the respondents was 51.1±9.3 years. The working experience of the position held was 26.1±8.2 years. The distribution by job title shows that 278 of the respondents were construction workers and those working in administration were 84. A correlation was established - the higher the prevalence of cardiovascular diseases and arterial hypertension diagnosed by a physician, the higher the blood pressure values among registered construction workers Discussion The most common risk factors for the respondents from both groups indicated were the cardiovascular diseases with the possible key role of the work environment factors in the multicausal etiology of the disease. Conclusion Measures need to be taken at all levels to reduce cardiovascular diseases among construction workers such as: introducing health promotion programmes aimed at eradicating harmful habits and conducting regular preventive check-ups.
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Winkert, K., and J. Kirsten. "Cardiopulmonary exercise testing – methodological aspects." Deutsche Zeitschrift für Sportmedizin/German Journal of Sports Medicine 73, no. 5 (September 1, 2022): 184–88. http://dx.doi.org/10.5960/dzsm.2022.538.
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Cardiopulmonary exercise testing (CPET) allows for a non-invasive assessment of the integrative response of the pulmonary, cardiovascular, and skeletal muscle system during exercise. Therefore CPET in sports medicine covers a wide spectrum, ranging from diagnosis of disease, preoperative assessment, to athlete monitoring. High standards of reliability and validity are needed to ensure high-quality and diagnostically conclusive CPET data, necessitating a systematic process of quality assurance and control in the daily application of CPET. Therefore, methodological aspects such as CPET equipment principles, calibration, verification, maintenance, preparation, and plausibility checks need to be considered. As inter-technology, inter-device, and inter-unit differences in reliability and validity are reported for automated metabolic analyzers, the choice of the appropriate device should follow the purpose of use and comprehensible data on reliability and validity. To ensure high-quality measurements, careful calibration, and verification of all sensors, the integrated overall measurement performance, and maintenance of all equipment need to be performed and monitored longitudinally. Further, standardized ambient conditions, with adequate circulation and exchange of room air are essential. As the choice of the ergometer and protocol influences various target values in CPET, appropriateness for the selected diagnostic objective as well as a corresponding standardization is needed. While patients should receive pretest information that clearly outlines the test procedure, the correct attachment of the CPET equipment is of utmost importance. To detect and correct malfunctions of the metabolic analyzer and equipment, plausibility checks of the outcome measures validity should be performed during the resting, unloaded, loaded, and recovery test phase. A basic plausibility check should include adequate rest values and increases for a given workload rate of minute ventilation ( ˙VE), oxygen consumption ( ˙VO2) and respiratory exchange ratio (RER), using rules of thumb by Rühle. Before the final data interpretation is performed, e.g. ventilatory threshold or maximum oxygen consumption (˙VO2max) or ˙VO2peak determination, again a plausibility check should be performed and the patient‘s effort whether or not maximal should be determined. Consequently, a standard operating procedure for quality assurance and control, including an intuitive data visualization with thresholds for “pass”, “fail” or outliers and trends of concerns should be specifically defined, taught, and implemented in each facility. Key Words: CPET, Exercise Testing, Physical Fitness
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Gimaeva, Zulfiya F., I. V. Bukhtiyarov, A. B. Bakirov, V. A. Kaptsov, and L. K. Karimova. "Cardiovascular risk in petrochemical workers." Hygiene and sanitation 99, no. 5 (July 7, 2020): 498–503. http://dx.doi.org/10.47470/0016-9900-2020-99-5-498-503.
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Introduction. The high prevalence of diseases of the circulatory system of workers in various sectors of the economy, the lack of data on the effects of harmful production factors on the formation of cardiovascular diseases in petrochemical industry workers justify the importance of conducting special studies on these petrochemical complex plants with the aim of assessing cardiovascular risk with the subsequent development of preventive measures. Material and methods. The objects of the study were workers in the production of monomers (ethylene, propylene, ethylbenzene, isoprene, divinyl) of petrochemical enterprises. Hygienic studies of the working conditions of workers included an assessment of the factors of the working environment and the labor process using generally accepted methods. Comprehensive clinical examination of workers included periodic examinations (n = 2634) with calculation of total and relative cardiovascular risk using the SCORE system, using questionnaire data, a Reeder L questionnaire and an in-depth clinical diagnostic medical examination (n = 101) with the definition total cardiovascular risk. Results. The most significant occupational factors of the labor process for workers in the main profession - panmen were established to include the combination of a chemical factor with the occupational noise and labor intensity, with an overall assessment of working conditions 3.2. The class of working conditions of workers of the comparison group (locksmith in instrumentation and automation corresponds to the permissible). There were revealed a high prevalence of arterial hypertension and other factors of cardiovascular risk. A higher dependence of the arterial hypertension level on age and length of service in the group of panmen was established when compared to the mechanicians of instrumentation and automation. Using mathematical models of multiple regression, the likely dynamics of the level of arterial hypertension and the left ventricular myocardial mass index were calculated under the influence of increasing age and other risk predictors. Conclusion. The results of a clinical study showed workers with severe arterial hypertension, a high and very high risk of death from cardiovascular disease on the SCORE scale, a high and very high overall cardiovascular risk, signs of dyslipidemia, obesity, high stress levels to require close attention. It is important to timely diagnose lesions of target organs, to conduct rational prevention aimed at reducing risk factors. According to the results of the study, there were developed preventive measures aimed at reducing cardiovascular morbidity and cardiovascular risk, prolonging the longevity of workers in petrochemical industries.
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Gimaeva, Zulfiya F., I. V. Bukhtiyarov, A. B. Bakirov, V. A. Kaptsov, and L. K. Karimova. "Cardiovascular risk in petrochemical workers." Hygiene and sanitation 99, no. 5 (July 7, 2020): 498–503. http://dx.doi.org/10.33029/0016-9900-2020-99-5-498-503.
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Introduction. The high prevalence of diseases of the circulatory system of workers in various sectors of the economy, the lack of data on the effects of harmful production factors on the formation of cardiovascular diseases in petrochemical industry workers justify the importance of conducting special studies on these petrochemical complex plants with the aim of assessing cardiovascular risk with the subsequent development of preventive measures. Material and methods. The objects of the study were workers in the production of monomers (ethylene, propylene, ethylbenzene, isoprene, divinyl) of petrochemical enterprises. Hygienic studies of the working conditions of workers included an assessment of the factors of the working environment and the labor process using generally accepted methods. Comprehensive clinical examination of workers included periodic examinations (n = 2634) with calculation of total and relative cardiovascular risk using the SCORE system, using questionnaire data, a Reeder L questionnaire and an in-depth clinical diagnostic medical examination (n = 101) with the definition total cardiovascular risk. Results. The most significant occupational factors of the labor process for workers in the main profession - panmen were established to include the combination of a chemical factor with the occupational noise and labor intensity, with an overall assessment of working conditions 3.2. The class of working conditions of workers of the comparison group (locksmith in instrumentation and automation corresponds to the permissible). There were revealed a high prevalence of arterial hypertension and other factors of cardiovascular risk. A higher dependence of the arterial hypertension level on age and length of service in the group of panmen was established when compared to the mechanicians of instrumentation and automation. Using mathematical models of multiple regression, the likely dynamics of the level of arterial hypertension and the left ventricular myocardial mass index were calculated under the influence of increasing age and other risk predictors. Conclusion. The results of a clinical study showed workers with severe arterial hypertension, a high and very high risk of death from cardiovascular disease on the SCORE scale, a high and very high overall cardiovascular risk, signs of dyslipidemia, obesity, high stress levels to require close attention. It is important to timely diagnose lesions of target organs, to conduct rational prevention aimed at reducing risk factors. According to the results of the study, there were developed preventive measures aimed at reducing cardiovascular morbidity and cardiovascular risk, prolonging the longevity of workers in petrochemical industries.
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Haughan, J., M. Manriquez, N. D. Cohen, M. A. Robinson, and C. Navas de Solis. "Comparison of novel wearable cardiac monitors to yield accurate exercising ECG and heart rate data in horses." Comparative Exercise Physiology 17, no. 5 (September 14, 2021): 457–65. http://dx.doi.org/10.3920/cep200080.
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Exercise associated deaths (EADs) in horses are a problem for the equestrian industry. Sudden death (SD) is responsible for approximately 20% of EADs. The underlying cause of SD is suspected to be cardiovascular disease but often cannot be determined post-mortem. User-friendly cardiac monitors are needed for large scale investigations of arrhythmias associated with SD in horses. We hypothesised that novel wearable devices would provide exercising electrocardiograms (ECGs) of sufficient diagnostic quality for this purpose. Diagnostic quality of ECGs generated by two wearable devices (W2nd™ and Polar Equine™) were compared to simultaneous recordings with a telemetry unit (Televet™) in 5 Thoroughbreds completing 43 separate submaximal exercise tests on a high-speed treadmill. Maximal heart rate (HRmax) generated by mobile applications (HRmaxapp), HRmax after manual correction (HRmaxcorr), percentage of diagnostic ECGs (%diag) at the gallop, and overall quality assessed by visual analogue scale (VAS) were assessed by a blinded observer. HRmaxcorr did not differ significantly between groups. HRmaxapp was significantly lower for W2nd (166.8/min, 95% confidence interval (CI): 160.5-173.1/min) but did not differ significantly between Televet (178.8/min 95% CI: 165.8-191.1/min) and Polar (181.3/min, 95% CI: 174.5-188.1/min). HRmaxcorr was accurate and precise in all runs. HRmaxapp was within a priori limits of agreement in 16/23 W2nd and 18/19 Polar recordings. %diag was significantly lower (77.1%, 95% CI: 67.4-86.8) for W2nd than Polar (100%, 95% CI: 89.9-110.3). VAS was lower for W2nd (46.2, 95% CI: 35.5-57.0) than Polar (90.6, 25% CI: 79.4-101.9). In conclusion, wearable devices appear to be promising tools for investigation of equine exercising arrhythmias in large-scale studies.
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Yadykina, Tatyana K., Olga Yu Кorotenko, Elena A. Semenova, Maria S. Bugaeva, and Anna G. Zhukova. "Study of glutathione-S-transferase (GST) T1 and M1 genes in aluminum industry workers with comorbid cardiovascular pathology." Russian Journal of Occupational Health and Industrial Ecology 63, no. 8 (September 5, 2023): 519–27. http://dx.doi.org/10.31089/1026-9428-2023-63-8-519-527.
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Introduction. Employees of the main professions of aluminum production have a high level of professional and production-related pathology, primarily diseases of the circulatory system associated with the long-term influence of vasotoxic factors on the body. The pathogenetic course of angiopathies does not proceed in isolation, it is predetermined by chronic fluoride intoxication and hereditary component. The establishment of associations determined on the basis of studying the polymorphism of glutathione-S-transferase genes with the risk of developing comorbid cardiovascular pathology makes it possible to use genetic analysis in its early diagnosis.
The study aims to explore the polymorphism of GST genes in aluminum industry workers with comorbid cardiovascular pathology.
Materials and methods. The authors have carried out the study using clinical and molecular genetic diagnostic methods in workers of the main professions engaged in the production of aluminum, with chronic occupational intoxication with fluorine compounds and persons with individual signs of fluoride exposure to the skeleton (comparison group). By detecting extended deletions in the loci of the GSTT1 and GSTM1 genes, the researchers have assessed the association of the studied genotypes with the risk of chronic intoxication and atherosclerosis.
Results. In the cohort of patients (36.58%) and in the comparison group (16.98%), the authors have revealed a combined form of cardiomyopathy complicated by coronary atherosclerosis, coronary heart disease. Also, scientists have established significant differences in the frequency distribution of genotypes of GST genes. Homozygous polymorphism GSTT1 0/0 is a risk factor for the development of occupational pathology against the background of the predominance of the normal genotype GSTM1+. Predictors (GSTT1 0/0, GSTM1 0/0) of the risk of atherosclerosis associated with hypertension in persons with chronic fluoride intoxication were determined.
Conclusion. The association of GST genes with the development of comorbid cardiovascular pathology was determined in the structure of professional and production-related pathology in aluminum industry workers.
Ethics. We have conducted the study of employees at the aluminum plant on a voluntary basis with the written consent of the examined persons on the basis of a specialized clinic of the Research Institute of Complex Problems of Hygiene and Occupational Diseases in accordance with the Ethical principles of conducting scientific and medical research with human participation ("Rules of Clinical Practice in the Russian Federation", Order of the Ministry of Health of the Russian Federation No. 266, 2003; Helsinki Declaration of the World Medical Association "Ethical principles of conducting scientific medical research with human participation", 2013).
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Gurev, A. V., A. R. Tukov, and I. V. Alexandrova. "Occupational and medical aspects of occupational morbidity in men with neurosensory hearing loss." Ural Medical Journal 21, no. 6 (December 8, 2022): 102–9. http://dx.doi.org/10.52420/2071-5943-2022-21-6-102-109.
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Introduction. Occupational neurosensory hearing loss is one of the most common occupational diseases. So far, there have been no studies in the scientific literature devoted to a retrospective analysis of professional conditions and conditions of medical care organization in case this pathology is detected in workers served by the system of health care institutions of FMBA of Russia.Materials and methods The study used data from the "Industry register of persons with occupational diseases", accounting documents and regulations that allow an analysis of working conditions and medical care.Results The rate of neurosensory hearing loss was 31.3 % in the structure of occupational diseases among employees of enterprises and organizations served by FMBA health care institutions of Russia in 2010-2020. The frequency of continuous use of anti-noise personal protective equipment decreased from 77.8 % (2010–2015) to 75.4 % (2016–2020). Occupational neurosensory hearing loss was diagnosed in 79.4 % of workers based on periodic medical examinations and in 20.6 % of workers based on self-referrals. The decision to refer an employee for determination of the degree of disability was made in 16.5 % of cases.Discussion On the basis of the scientific literature and the results of our study, a proposal to take into account not only physical, but also chemical occupational hazards that aggravate the impact of industrial noise on employee health, as well as the anamnesis of tobacco smoking, cardiovascular disease, diabetes mellitus and atherosclerosis.Conclusion The risk group for occupational neurosensory hearing loss is men over 50 years of age. The duration of formation of this pathology is 34,1 ± 1,1 years at the PS level of 90,6 ± 1,0 dB. The importance of optimal organization of periodic medical examinations and the need to control the use of anti-noise personal protective equipment in the workplace is noted.
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Jahan, Farhana, Anisuddin Ahmed, Faroque Md Mohsin, Sorforajur Rahman, Abu Sayeed, Lailatun Nahar, and Diapk Kumar Mitra. "Changes in the readiness of healthcare systems to provide diabetes- and cardiovascular disease-related services: A comparison of indices using data from the 2014 and 2017 Bangladesh Health Facility Surveys." F1000Research 12 (July 28, 2023): 898. http://dx.doi.org/10.12688/f1000research.138772.1.
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Background: The increasing prevalence of non-communicable diseases (NCDs) in Bangladesh is a significant obstacle for the government's already under-resourced healthcare centers and healthcare management. This study aimed to determine whether healthcare services are prepared to handle cardiovascular disease (CVD) and diabetes in the future. Methods: This cross-sectional study used the Bangladesh Health Facilities Survey (BHFS) 2014 and 2017 data. The BHFS 2014 completed assessment of 317 facilities providing diabetes care and 407 facilities providing CVD care, while the 2017 BHFS included 305 and 368 facilities providing diabetes and CVD care, respectively. Results: A slight increase in facility readiness status was observed in 2017 compared with 2014, though it was not statistically significant. District hospitals (DHs) and Upazila health complexes (UHCs) showed improvement in staff and guidelines, basic equipment, diagnostic capabilities, and essential drugs, as their Readiness Index (RI) value increased in 2017 from 2014. The RI values of non-governmental organizations (NGOs) clinics were 48.65% in 2014, whereas the value was slightly increased to 55.28% in 2017. For private clinics, the RI value diminished in 2017 (56.11%), which was lower than the 2014 survey (60.62%). There was a slightly mixed trend for public and private facilities regarding managing CVDs. In DHs and UHCs, the RI value decreased to 58.5% and 53.06% in 2017 from 64.04% and 53.02% in 2014. NGO clinics were valued at 48.65% in 2014, which dropped to 44.53%. For private clinics, the value showed a decreasing trend as the value in 2017 was 61.58%, lower than the value of 2014 (64.15%). Conclusions: In Bangladesh, public and private healthcare facilities lack readiness for healthcare towards DM and CVD maintenance. It is noteworthy that this improvement has been insignificant over the years in this regard. Healthcare policy reform is urgently required to strengthen NCD healthcare, particularly in public healthcare facilities.
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Susilo, Joko, and Feny Tunjungsari. "Resiko Gangguan Pernapasan pada Industri Besi Baja." CoMPHI Journal: Community Medicine and Public Health of Indonesia Journal 3, no. 2 (October 14, 2022): 110–21. http://dx.doi.org/10.37148/comphijournal.v3i2.109.
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Work in steel mills is close to exposure to dust, fumes, and gases. Pollutants from activities in factory workers such as iron dust and other particles can increase the permeability of the respiratory tract mucosa. Iron dust can cause damage to lung surfactant and lung function and quartz can pose a risk of silicosis, lung cancer, cardiovascular disease, and mortality. This study uses several literature reviews through several international journals from 2015 to 2020. Search articles related to the risk of respiratory disorders in steel factories. Exposures to factory workers include metal fumes, dust, silica, acid gases. Respiratory disorders appear in the form of clinical symptoms which are divided into chronic and acute symptoms as well as changes in lungfunction as seen from changes in FVC and FEV1 from spirometry examination. The influencing factors are metallic agents that can be inhaled, the length of time workers are exposed to, working in confined spaces, lack of adequate ventilation, lack of occupational safety and health training, and worker compliance in the use of personal protective equipment. The risk of respiratory disorders in steel industry workers is a decrease in lung function accompanied by acute and chronic respiratory disorders. There are several factors that affect respiratory disorders in workers so that steel production companies are advised to take a comprehensive holistic approach in dealing with the risk of respiratory problems in steel factories.
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Ignjatovic, Svetlana, Nada Majkic-Singh, Dejan Radenkovic, Miomir Gvozdenovic, and Mihajlo Mitrovic. "Diagnosis, assessment of severity and management of acute pancreatitis." Jugoslovenska medicinska biohemija 23, no. 3 (2004): 229–33. http://dx.doi.org/10.2298/jmh0403229i.
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Severe pancreatitis occurs in 20%?30% of all patients with acute pancreatitis. Pancreatic enzymes, cytokines and other active peptides, liberated from the inflamed pancreas, convert inflammation of the pancreas as a single-organ disease of the retroperitoneum to a multisystem disease. Determinations of pancreatic serum enzymes are still ?the golden standard? for diagnosis of the acute pancreatitis. Out of clinically significant pancreatic enzymes, pancreatic-amylase and lipase are suggested for routine clinical determination due to available methods for their measurement. The methods are simple, and the results may be obtained rather quickly without any special equipment. Maximal diagnostic accuracy is achieved by ?cut-off? values of 182 U/L for pancreatic-amylase and 656 U/L for lipase. Treatment of patients with acute pancreatitis is based on the initial assessment of disease severity. Early staging is based on the presence and degree of systemic failure (cardiovascular, pulmonary, and renal) and on the presence and extent of pancreatic necrosis. Individual clinical parameters and laboratory biomarkers, although sometimes helpful, are not sufficiently accurate to reliable assess the severity of an acute attack. Numeric grading systems with sensitivities of about 70% are commonly used today as indicators of organ failure and disease severity. Contrast material-enhanced computed tomography is used in addition to help evaluate local pancreatic morphology and the presence and extent of pancreatic necrosis. Out of all recently studied biochemical parameters for prognostic evaluation of acute pancreatitis patients, the measurement of C-reactive protein concentration appeared to be the parameter with the highest clinical accuracy. The best differentiation of moderate from severe acute pancreatitis forms is achieved by ?cut-off? CRP values of 126 mg/L, 48 hours from the onset of symptoms. For this reason, CRP measurement may be used as the alternative to computerized tomography. In compliance with the postulations for evidence- based medicine, the procedures related to diagnosis, prognosis and management of acute pancreatitis are classified into four categories: certain, probable, possible and inappropriate.
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Cartaxo, Adriana Nascimento Santos, Francisco Iran Cartaxo Barbosa, Paulo Henrique de Souza Bermejo, Marina Figueiredo Moreira, and David Nadler Prata. "The exposure risk to COVID-19 in most affected countries: A vulnerability assessment model." PLOS ONE 16, no. 3 (March 4, 2021): e0248075. http://dx.doi.org/10.1371/journal.pone.0248075.
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The world is facing the coronavirus pandemic (COVID-19), which began in China. By August 18, 2020, the United States, Brazil, and India were the most affected countries. Health infrastructure and socioeconomic vulnerabilities may be affecting the response capacities of these countries. We compared official indicators to identify which vulnerabilities better determined the exposure risk to COVID-19 in both the most and least affected countries. To achieve this purpose, we collected indicators from the Infectious Disease Vulnerability Index (IDVI), the World Health Organization (WHO), the World Bank, and the Brazilian Geography and Statistics Institute (IBGE). All indicators were normalized to facilitate comparisons. Speed, incidence, and population were used to identify the groups of countries with the highest and lowest risks of infection. Countries’ response capacities were determined based on socioeconomic, political, and health infrastructure conditions. Vulnerabilities were identified based on the indicator sensitivity. The highest-risk group included the U.S., Brazil, and India, whereas the lowest-risk group (with the largest population by continent) consisted of China, New Zealand, and Germany. The high-sensitivity cluster had 18 indicators (50% extra IDVI), such as merchandise trade, immunization, public services, maternal mortality, life expectancy at birth, hospital beds, GINI index, adolescent fertility, governance, political stability, transparency/corruption, industry, and water supply. The greatest vulnerability of the highest-risk group was related first to economic factors (merchandise trade), followed by public health (immunization), highlighting global dependence on Chinese trade, such as protective materials, equipment, and diagnostic tests. However, domestic political factors had more indicators, beginning with high sensitivity and followed by healthcare and economic conditions, which signified a lesser capacity to guide, coordinate, and supply the population with protective measures, such as social distancing.
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Hirsch, Jamie S., Samuel Colby Danna, Nihar Desai, Ty J. Gluckman, Manisha Jhamb, Kim Newlin, Bob Pellechio, Ahlam Elbedewe, and Evan Norfolk. "Optimizing Care Delivery in Patients with Chronic Kidney Disease in the United States: Proceedings of a Multidisciplinary Roundtable Discussion and Literature Review." Journal of Clinical Medicine 13, no. 5 (February 20, 2024): 1206. http://dx.doi.org/10.3390/jcm13051206.
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Background: Approximately 37 million individuals in the United States (US) have chronic kidney disease (CKD). Patients with CKD have a substantial morbidity and mortality, which contributes to a huge economic burden to the healthcare system. A limited number of clinical pathways or defined workflows exist for CKD care delivery in the US, primarily due to a lower prioritization of CKD care within health systems compared with other areas (e.g., cardiovascular disease [CVD], cancer screening). CKD is a public health crisis and by the year 2040, CKD will become the fifth leading cause of years of life lost. It is therefore critical to address these challenges to improve outcomes in patients with CKD. Methods: The CKD Leaders Network conducted a virtual, 3 h, multidisciplinary roundtable discussion with eight subject-matter experts to better understand key factors impacting CKD care delivery and barriers across the US. A premeeting survey identified topics for discussion covering the screening, diagnosis, risk stratification, and management of CKD across the care continuum. Findings from this roundtable are summarized and presented herein. Results: Universal challenges exist across health systems, including a lack of awareness amongst providers and patients, constrained care team bandwidth, inadequate financial incentives for early CKD identification, non-standardized diagnostic classification and triage processes, and non-centralized patient information. Proposed solutions include highlighting immediate and long-term financial implications linked with failure to identify and address at-risk individuals, identifying and managing early-stage CKD, enhancing efforts to support guideline-based education for providers and patients, and capitalizing on next-generation solutions. Conclusions: Payers and other industry stakeholders have opportunities to contribute to optimal CKD care delivery. Beyond addressing the inadequacies that currently exist, actionable tactics can be implemented into clinical practice to improve clinical outcomes in patients at risk for or diagnosed with CKD in the US.
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Chou, Tai-Hua, Chia-Hsuan Cheng, Chi-Jen Lo, Guang-Huar Young, Szu-Heng Liu, and Robert Y.-L. Wang. "New Advances in Rapid Pretreatment for Small Dense LDL Cholesterol Measurement Using Shear Horizontal Surface Acoustic Wave (SH-SAW) Technology." International Journal of Molecular Sciences 25, no. 2 (January 15, 2024): 1044. http://dx.doi.org/10.3390/ijms25021044.
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Atherosclerosis is an inflammatory disease of the arteries associated with alterations in lipid and other metabolism and is a major cause of cardiovascular disease (CVD). LDL consists of several subclasses with different sizes, densities, and physicochemical compositions. Small dense LDL (sd-LDL) is a subclass of LDL. There is growing evidence that sd-LDL-C is associated with CVD risk, metabolic dysregulation, and several pathophysiological processes. In this study, we present a straightforward membrane device filtration method that can be performed with simple laboratory methods to directly determine sd-LDL in serum without the need for specialized equipment. The method consists of three steps: first, the precipitation of lipoproteins with magnesium harpin; second, the collection of effluent from a 100 nm filter; and third, the quantification of sd-LDL-ApoB in the effluent with an SH-SAW biosensor. There was a good correlation between ApoB values obtained using the centrifugation (y = 1.0411x + 12.96, r = 0.82, n = 20) and filtration (y = 1.0633x + 15.13, r = 0.88, n = 20) methods and commercially available sd-LDL-C assay values. In addition to the filtrate method, there was also a close correlation between sd-LDL-C and ELISA assay values (y = 1.0483x − 4489, r = 0.88, n = 20). The filtration treatment method also showed a high correlation with LDL subfractions and NMR spectra ApoB measurements (y = 2.4846x + 4.637, r = 0.89, n = 20). The presence of sd-LDL-ApoB in the effluent was also confirmed by ELISA assay. These results suggest that this filtration method is a simple and promising pretreatment for use with the SH-SAW biosensor as a rapid in vitro diagnostic (IVD) method for predicting sd-LDL concentrations. Overall, we propose a very sensitive and specific SH-SAW biosensor with the ApoB antibody in its sensitive region to monitor sd-LDL levels by employing a simple delay-time phase shifted SH-SAW device. In conclusion, based on the demonstration of our study, the SH-SAW biosensor could be a strong candidate for the future measurement of sd-LDL.
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Nechaeva, G. I., A. N. Dakuko, E. N. Loginova, and I. V. Bogatyrev. "Structural features of the heart in children with arrhythmic syndrome due to nonspecific connective tissue disorder." Meditsinskiy sovet = Medical Council, no. 17 (November 1, 2023): 204–13. http://dx.doi.org/10.21518/ms2023-359.
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Introduction. Connective tissue is highly organized system, its disorders are characterized by a pronounced polymorphism of morphological and clinical manifestations. The cardiovascular pathology in patients with nonspecific connective tissue disorder attracts attention due to the high risk of complications: rhythm and conduction disorders, infective endocarditis, vascular thromboembolism and sudden cardiac death. Therefore, it’s very important to use up-to-date equipment and methods of early diagnosis of a high risk of fatal events in young.Aim. To investigate the structural features of the heart and their relationship with the process of myocardial remodeling in children with arrhythmic syndrome and nonspecific connective tissue disorder.Materials and methods. Sixty-five children were examined, 40 of them had arrhythmic syndrome in combination with nonspecific connective tissue disorder, and 25 had only minimal manifestations of nonspecific connective tissue disorder without arrhythmic syndrome. Such up-to-date methods as assessment of myocardial remodeling and longitudinal strain, natriuretic peptide assessment were included in the diagnostic algorithm.Results and discussion. The study showed a variety of phenotypic and visceral markers of nonspecific connective tissue disorder in children with arrhythmic syndrome. Arrhythmic syndrome was manifested by monotopic and heterotopic heart rhythm disorders, and structural changes of the heart: mitral valve prolapse and myocardial wall thinning were correlated with a more frequent increase in natriuretic peptide. Speckle-tracking echocardiography showed a significant decrease in longitudinal myocardial strain with predominance of myocardial strain in the anterior basal segment in children with arrhythmic syndrome.Conclusion. Our study showed a variety of phenotypic and visceral markers of undifferentiated connective tissue dysplasia in children with arrhythmic syndrome. The data obtained require further mathematical analysis and the establishment of a possible relationship between the external manifestations of the disease and cardiac rhythm and conduction disturbances.
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Camm, N. John. "Revolutionizing Cardiac Diagnosis: An AI Algorithm for Heart Abnormality Detection in Medical Imaging- A Review of Current and Emerging Techniques." Clinical Cardiology and Cardiovascular Interventions 6, no. 2 (March 30, 2024): 01–08. http://dx.doi.org/10.31579/2641-0419/304.
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Artificial intelligence (AI) algorithms have been developed to analyze medical images and identify heart abnormalities. These algorithms can be trained to recognize patterns in medical images that are indicative of various heart conditions, such as coronary artery disease, heart valve abnormalities, and cardiomyopathies. One common approach to developing AI algorithms for medical image analysis is to use machine learning techniques. These algorithms are trained using large datasets of labeled medical images, along with corresponding diagnostic information. The algorithm is then able to use this training data to identify patterns that are indicative of different heart conditions. There are several potential benefits to using AI algorithms for medical image analysis. For example, these algorithms can help to reduce the workload of radiologists and other medical professionals, who may be overwhelmed by the large volume of images that they need to review on a daily basis. Additionally, AI algorithms may be able to identify patterns in medical images that are not immediately apparent to human reviewers, potentially leading to earlier diagnosis and treatment of heart conditions. We intend to review promise shown by these algorithms for improving diagnostic quality, patient outcomes and reducing the workload on medical professionals and address concerns about their accuracy and fairness. Artificial intelligence (AI) has the potential to revolutionize the diagnosis and management of cardiovascular disease (CVD). By analyzing large amounts of data from various sources, AI algorithms can identify patterns and make predictions that may not be apparent to the human eye.AI is increasingly being used in the healthcare industry to improve diagnostic accuracy and speed, especially in the field of medical imaging. One area where AI has shown promise is in the analysis of medical images to diagnose cardiac abnormalities. The goal of such algorithms is to provide accurate and fast diagnosis to support medical decision-making and improve patient outcomes. An AI algorithm for analyzing medical images to identify heart abnormalities typically uses techniques such as deep learning, computer vision, and image analysis. The algorithm is trained on large amounts of medical data, including imaging scans like MRI, CT, and X-ray images, to learn to recognize signs of heart diseases like cardiomegaly, ventricular hypertrophy, and valvular defects. The algorithm can then analyze new images and provide a diagnosis based on its training. The use of AI in medical imaging has several potential benefits, including improved accuracy, speed, and consistency compared to traditional methods. It can also help to reduce the workload on medical professionals and provide access to medical imaging services in remote and underserved areas. However, it is important to note that AI algorithms are only as accurate as the data they are trained on, and careful consideration must be given to the quality and diversity of the training data. In conclusion, AI algorithms analyzing medical images to identify heart abnormalities have the potential to revolutionize the way heart diseases are diagnosed and treated. While still in the early stages of development. This article reviews promise shown by these algorithms for improving diagnostic quality, patient outcomes and reducing the workload on medical professionals.
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Новикова, Е. И., И. В. Кочеткова, А. В. Арчегова, and М. К. Новиков. "DETAIL CODE – AS AN INTEGRAL INDICATOR OF HEALTH ASSESSMENT IN PERSONS WITHOUT PREDISIVE CARDIOVASCULAR RISK FACTORS." СИСТЕМНЫЙ АНАЛИЗ И УПРАВЛЕНИЕ В БИОМЕДИЦИНСКИХ СИСТЕМАХ 22, no. 2 (June 30, 2023): 114–18. http://dx.doi.org/10.36622/vstu.2023.22.2.016.
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Одним из главных направлений в современной медицине является профилактика заболеваний. Донозологическая диагностика необходима для выявления патологий на начальных стадиях: лучше предотвратить развитие заболевания, чем иметь дело с его последствиями в будущем. Особенно остро это касается сердечно-сосудистых заболеваний, смертность от которых занимает в стране лидирующие позиции. Для улучшения результатов профилактических мероприятий врачам необходимо иметь соответствующее техническое оборудование, которое будет выявлять самые начальные отклонения в состоянии здоровья пациентов, и при этом удовлетворять современным требованиям к техническому обеспечению. Одно из таких требований – быстрота получения итогового полного результата исследования. Для врачей, особенно государственных медицинских учреждений, важно большую часть времени приема пациента посвятить непосредственно анализу здоровья пациента и выдаче рекомендаций по нему. Аппаратно-программный комплекс «Экосан-2007» предназначен для выявления начальных отклонений здоровья на основе компьютеризированного анализа вариабельности сердечного ритма, однако полученный после исследования результат не является конечным – его еще необходимо расшифровать и только после этого дать оценку здоровья пациента и иметь возможность спрогнозировать риски. В статье рассматривается создание такого программного обеспечения, которое по введенным данным диагностического исследования пациента комплексом «Экосан-2007» будет выдавать оценку предрасположенности пациента к сердечно-сосудистым заболеваниям. Были проанализированы данные исследования на аппарате группы людей, по которым была построена нейронная сеть, также в статье приведена схема работы врача при использовании нашей программы и прототип интерфейса программы, созданный при помощи Delphi. Вместе с тем проанализирован целевой рынок и составлена таблица сравнения разрабатываемой программы с уже существующими предложениями. Целью работы является разработка моделей и алгоритма, обеспечивающих повышение эффективности процесса диагностики и прогнозирования сердечно-сосудистых заболеваний One of the main directions in modern medicine is disease prevention. Prenosological diagnostics is necessary to detect pathologies in the initial stages: it is better to prevent the development of the disease than to deal with its consequences in the future. This is especially acute for cardiovascular diseases, the mortality from which occupies a leading position in the country. To improve the results of preventive measures, doctors need to have appropriate technical equipment that will detect the most initial deviations in the health status of patients and at the same time meet modern requirements for technical support. One of these requirements is the speed of obtaining the final complete result of the study. It is important for physicians, especially public medical institutions, to devote most of the time of a patient's appointment directly to analyzing the patient's health and issuing recommendations on it. The hardware-software complex "Ecosan-2007" is designed to identify initial health deviations based on a computerized analysis of heart rate variability, however, the result obtained after the study is not final - it still needs to be deciphered and only after that an assessment of the patient's health and be able to predict - take risks. The article discusses the creation of such software, which, according to the data of the patient's diagnostic examination by the Ecosan-2007 complex, will provide an assessment of the patient's predisposition to cardiovascular diseases. The study data were analyzed on the apparatus of a group of people, according to which a neural network was built, and the article also provides a diagram of the work of a doctor using our program and a prototype of the program interface created using Delphi. At the same time, the target market was analyzed and a table was compiled for comparing the program being developed with existing proposals. The aim of the work is to develop models and algorithms that provide an increase in the efficiency of the process of diagnosing and predicting cardiovascular diseases
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Henry, Olivia, Alexandra Brito, Marguerite Cooper Lloyd, Robert Miller, Eleanor Weaver, and Raghu Upender. "A Model for Sleep Apnea Management in Underserved Patient Populations." Journal of Primary Care & Community Health 13 (January 2022): 215013192110689. http://dx.doi.org/10.1177/21501319211068969.
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Introduction: Obstructive sleep apnea (OSA) is a common condition in the United States that is strongly linked to metabolic disease, cardiovascular disease, and increased mortality. Uninsured populations experience sleep health disparities, including delayed recognition, diagnosis, and treatment of OSA due to barriers accessing and affording care. Partnerships between primary care clinics and sleep medicine specialists for sleep apnea management have the potential to increase screening, testing, and treatment among underserved populations. Here, we present an integrated and cost-effective model that is easier to navigate for patients while maintaining high quality care. Methods: We designed and implemented a specialty sleep clinic at Shade Tree Clinic, Vanderbilt’s student-run, free primary care clinic. Patients with signs and symptoms of OSA were identified at primary care appointments and screened using the STOP-BANG questionnaire. Clinic visits took place over telehealth with a medical student and sleep specialist. Patients were diagnosed using a home sleep test, and if indicated, were prescribed and given a CPAP device for treatment. CPAP adherence was monitored using a cloud-based remote monitoring system. Results: From December 2020 through August 2021, we hosted 6 telehealth Sleep Clinics, seeing a total of 28 patients across these visits. We have received a total of 37 referrals and have coordinated sleep evaluations and diagnostic testing for 18 of these patients so far. Prior to initiation of the sleep clinic, there were 17 patients on our primary care panel at Shade Tree with a diagnosis of OSA. These patients were using donated equipment and many had been lost to follow-up or had broken parts. We were able to replace 10 of these patient’s CPAP devices and plan to replace the remaining seven. Conclusions: We have created a model of integrated specialty care that is efficient and cost-effective. This paradigm can be replicated for the many specialties that are typically overlooked and undertreated when working with uninsured patients. As awareness of this sleep medicine program becomes more widespread at Shade Tree Clinic, we anticipate reaching more primary care patients with signs and symptoms of sleep apnea through student education, cost-effective diagnostics, and partnership with sleep specialists.
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Bamgboje, David, Iasonas Christoulakis, Ioannis Smanis, Gaurav Chavan, Rinkal Shah, Masoud Malekzadeh, Ioannis Violaris, et al. "Continuous Non-Invasive Glucose Monitoring via Contact Lenses: Current Approaches and Future Perspectives." Biosensors 11, no. 6 (June 9, 2021): 189. http://dx.doi.org/10.3390/bios11060189.
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Diabetes mellitus (DM) is a chronic disease that must be carefully managed to prevent serious complications such as cardiovascular disease, retinopathy, nephropathy and neuropathy. Self-monitoring of blood glucose is a crucial tool for managing diabetes and, at present, all relevant procedures are invasive while they only provide periodic measurements. The pain and measurement intermittency associated with invasive techniques resulted in the exploration of painless, continuous, and non-invasive techniques of glucose measurement that would facilitate intensive management. The focus of this review paper is the existing solutions for continuous non-invasive glucose monitoring via contact lenses (CLs) and to carry out a detailed, qualitative, and comparative analysis to inform prospective researchers on viable pathways. Direct glucose monitoring via CLs is contingent on the detection of biomarkers present in the lacrimal fluid. In this review, emphasis is given on two types of sensors: a graphene-AgNW hybrid sensor and an amperometric sensor. Both sensors can detect the presence of glucose in the lacrimal fluid by using the enzyme, glucose oxidase. Additionally, this review covers fabrication procedures for CL biosensors. Ever since Google published the first glucose monitoring embedded system on a CL, CL biosensors have been considered state-of-the-art in the medical device research and development industry. The CL not only has to have a sensory system, it must also have an embedded integrated circuit (IC) for readout and wireless communication. Moreover, to retain mobility and ease of use of the CLs used for continuous glucose monitoring, the power supply to the solid-state IC on such CLs must be wireless. Currently, there are four methods of powering CLs: utilizing solar energy, via a biofuel cell, or by inductive or radiofrequency (RF) power. Although, there are many limitations associated with each method, the limitations common to all, are safety restrictions and CL size limitations. Bearing this in mind, RF power has received most of the attention in reported literature, whereas solar power has received the least attention in the literature. CLs seem a very promising target for cutting edge biotechnological applications of diagnostic, prognostic and therapeutic relevance.
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Tewes, Federico R. "Artificial Intelligence in the American Healthcare Industry: Looking Forward to 2030." Journal of Medical Research and Surgery 3, no. 5 (October 6, 2022): 107–8. http://dx.doi.org/10.52916/jmrs224089.
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Artificial intelligence (AI) has the potential to speed up the exponential growth of cutting-edge technology, much way the Internet did. Due to intense competition from the private sector, governments, and businesspeople around the world, the Internet has already reached its peak as an exponential technology. In contrast, artificial intelligence is still in its infancy, and people all over the world are unsure of how it will impact their lives in the future. Artificial intelligence, is a field of technology that enables robots and computer programmes to mimic human intellect by teaching a predetermined set of software rules to learn by repetitive learning from experience and slowly moving toward maximum performance. Although this intelligence is still developing, it has already demonstrated five different levels of independence. Utilized initially to resolve issues. Next, think about solutions. Third, respond to inquiries. Fourth, use data analytics to generate forecasts. Fifth, make tactical recommendations. Massive data sets and "iterative algorithms," which use lookup tables and other data structures like stacks and queues to solve issues, make all of this possible. Iteration is a strategy where software rules are regularly adjusted to patterns in the data for a certain number of iterations. The artificial intelligence continuously makes small, incremental improvements that result in exponential growth, which enables the computer to become incredibly proficient at whatever it is trained to do. For each round of data processing, the artificial intelligence tests and measures its performance to develop new expertise. In order to address complicated problems, artificial intelligence aims to create computer systems that can mimic human behavior and exhibit human-like thought processes [1]. Artificial intelligence technology is being developed to give individualized medication in the field of healthcare. By 2030, six different artificial intelligence sectors will have considerably improved healthcare delivery through the utilization of larger, more accessible data sets. The first is machine learning. This area of artificial intelligence learns automatically and produces improved results based on identifying patterns in the data, gaining new insights, and enhancing the outcomes of whatever activity the system is intended to accomplish. It does this without being trained to learn a particular topic. Here are several instances of machine learning in the healthcare industry. The first is the IBM Watson Genomics, which aids in rapid disease diagnosis and identification by fusing cognitive computing with genome-based tumour sequencing. Second, a project called Nave Bayes allows for the prediction of diabetes years before an official diagnosis, before it results in harm to the kidneys, the heart, and the nerves. Third, employing two machine learning approaches termed classification and clustering to analyse the Indian Liver Patient Data (ILPD) set in order to predict liver illness before this organ that regulates metabolism becomes susceptible to chronic hepatitis, liver cancer, and cirrhosis [2]. Second, deep learning. Deep learning employs artificial intelligence to learn from data processing, much like machine learning does. Deep learning, on the other hand, makes use of synthetic neural networks that mimic human brain function to analyse data, identify relationships between the data, and provide outputs based on positive and negative reinforcement. For instance, in the fields of Magnetic Resonance Imaging (MRI) and Computed Tomography (CT), deep learning aids in the processes of picture recognition and object detection. Deep learning algorithms for the early identification of Alzheimer's, diabetic retinopathy, and breast nodule ultrasound detection are three applications of this cutting-edge technology in the real world. Future developments in deep learning will make considerable improvements in pathology and radiology pictures [3]. Third, neural networks. The artificial intelligence system can now accept massive data sets, find patterns within the data, and respond to queries regarding the information processed because the computer learning process resembles a network of neurons in the human brain. Let's examine a few application examples that are now applicable to the healthcare sector. According to studies from John Hopkins University, surgical errors are a major contributor to medical malpractice claims since they happen more than 4,000 times a year in just the United States due to the human error of surgeons. Neural networks can be used in robot-assisted surgery to model and plan procedures, evaluate the abilities of the surgeon, and streamline surgical activities. In one study of 379 orthopaedic patients, it was discovered that robotic surgery using neural networks results in five times fewer complications than surgery performed by a single surgeon. Another application of neural networks is in visualising diagnostics, which was proven to physicians by Harvard University researchers who inserted an image of a gorilla to x-rays. Of the radiologists who saw the images, 83% did not recognise the gorilla. The Houston Medical Research Institute has created a breast cancer early detection programme that can analyse mammograms with 99 percent accuracy and offer diagnostic information 30 times faster than a human [4]. Cognitive computing is the fourth. Aims to replicate the way people and machines interact, showing how a computer may operate like the human brain when handling challenging tasks like text, speech, or image analysis. Large volumes of patient data have been analysed, with the majority of the research to date focusing on cancer, diabetes, and cardiovascular disease. Companies like Google, IBM, Facebook, and Apple have shown interest in this work. Cognitive computing made up the greatest component of the artificial market in 2020, with 39% of the total [5]. Hospitals made up 42% of the market for cognitive computing end users because of the rising demand for individualised medical data. IBM invested more than $1 billion on the development of the WATSON analytics platform ecosystem and collaboration with startups committed to creating various cloud and application-based systems for the healthcare business in 2014 because it predicted the demand for cognitive computing in this sector. Natural Language Processing (NLP) is the fifth. This area of artificial intelligence enables computers to comprehend and analyse spoken language. The initial phase of this pre-processing is to divide the data up into more manageable semantic units, which merely makes the information simpler for the NLP system to understand. Clinical trial development is experiencing exponential expansion in the healthcare sector thanks to NLP. First, the NLP uses speech-to-text dictation and structured data entry to extract clinical data at the point of care, reducing the need for manual assessment of complex clinical paperwork. Second, using NLP technology, healthcare professionals can automatically examine enormous amounts of unstructured clinical and patient data to select the most suitable patients for clinical trials, perhaps leading to an improvement in the patients' health [6]. Computer vision comes in sixth. Computer vision, an essential part of artificial intelligence, uses visual data as input to process photos and videos continuously in order to get better results faster and with higher quality than would be possible if the same job were done manually. Simply put, doctors can now diagnose their patients with diseases like cancer, diabetes, and cardiovascular disorders more quickly and at an earlier stage. Here are a few examples of real-world applications where computer vision technology is making notable strides. Mammogram images are analysed by visual systems that are intended to spot breast cancer at an early stage. Automated cell counting is another example from the real world that dramatically decreases human error and raises concerns about the accuracy of the results because they might differ greatly depending on the examiner's experience and degree of focus. A third application of computer vision in the real world is the quick and painless early-stage tumour detection enabled by artificial intelligence. Without a doubt, computer vision has the unfathomable potential to significantly enhance how healthcare is delivered. Other than for visual data analysis, clinicians can use this technology to enhance their training and skill development. Currently, Gramener is the top company offering medical facilities and research organisations computer vision solutions [7]. The usage of imperative rather than functional programming languages is one of the key difficulties in creating artificial intelligence software. As artificial intelligence starts to increase exponentially, developers employing imperative programming languages must assume that the machine is stupid and supply detailed instructions that are subject to a high level of maintenance and human error. In software with hundreds of thousands of lines of code, human error detection is challenging. Therefore, the substantial amount of ensuing maintenance may become ridiculously expensive, maintaining the high expenditures of research and development. As a result, software developers have contributed to the unreasonably high cost of medical care. Functional programming languages, on the other hand, demand that the developer use their problem-solving abilities as though the computer were a mathematician. As a result, compared to the number of lines of code needed by the programme to perform the same operation, mathematical functions are orders of magnitude shorter. In software with hundreds of thousands of lines of code, human error detection is challenging. Therefore, the substantial amount of ensuing maintenance may become ridiculously expensive, maintaining the high expenditures of research and development. As a result, software developers have contributed to the unreasonably high cost of medical care. Functional programming languages, on the other hand, demand that the developer use their problem-solving abilities as though the computer were a mathematician. As a result, compared to the number of lines of code needed by the programme to perform the same operation, mathematical functions are orders of magnitude shorter. The bulk of software developers that use functional programming languages are well-trained in mathematical logic; thus, they reason differently than most American software developers, who are more accustomed to following step-by-step instructions. The market for artificial intelligence in healthcare is expected to increase from $3.4 billion in 2021 to at least $18.7 billion by 2027, or a 30 percent annual growth rate before 2030, according to market research firm IMARC Group. The only outstanding query is whether these operational reductions will ultimately result in less expensive therapies.
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"Individualized Therapeutic Design Against Lyme Disease." Microbial Bioactives 6, no. 1 (December 2, 2023). http://dx.doi.org/10.25163/microbbioacts.619391.
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The incidence of Lyme disease, which is caused by the bacteria Borrelia burgdorferi and is transmitted by ticks in 77% of cases, has significantly increased. Skin rashes, neurological, dermatological, cardiovascular, and musculoskeletal problems are all brought on by the illness. Ten to twenty percent of individuals with post-treatment Lyme disease syndrome (PTLDS) do not improve after receiving treatment. It is essential to comprehend the traits of Borrelia burgdorferi in order to create Lyme disease diagnostic equipment and treatments. Since North America has the highest prevalence of infected black-legged ticks, the disease is spread by their bite. Preventing health issues requires early detection and treatment. Lyme disease is diagnosed using diagnostic methods such as PCR, qPCR, RT-PCR, NAATs, NGS, and multiplex PCR panels. Lyme arthritis treatment, longer courses of oral antibiotics, intravenous antibiotics, and post-treatment Lyme disease syndrome are among the treatments available. Precision medicine, also known as customized medicine, tries to modify medical judgments and treatments for specific patients in light of their distinctive genetic makeup, way of life, and environment. The future treatment of Lyme disease will comprise better diagnostic equipment, sophisticated imaging methods, precision medicine, individualized vaccination plans, and patient-centered research.
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Nonaka, Carolina Kymie Vasques, Antônio Augusto Fonseca Junior, Estefânia Oliveira Guedes, Régia Maria D´Ambros, Graciela Kunrath Lima, Marcelo Fernandes Camargos, and Marcos Bryan Heinemann. "Different methods of real-time PCR for detection of pseudorabies virus." Ciência Rural 47, no. 3 (2017). http://dx.doi.org/10.1590/0103-8478cr20160342.
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ABSTRACT: Pseudorabies (PR) is a highly contagious viral disease of great animal health and economic importance in swine industry. The aim of this study was to evaluate different genomic regions, real-time PCR chemistries and equipment for the molecular diagnosis of PR. Eight primer pairs targeting four genes (gB, gC, gE, gD), three different qPCR chemistries (SybrGreen, hydrolysis probes and plexor) and two equipment (ABI7500, Rotorgene 3000) were evaluated. Oligonucleotides targeting gB using hydrolysis probes showed the best performance after evaluating efficiency (99%), the detection limit (10-1.5 TCID50 mL-1) and diagnostic sensitivity and; therefore, those primers were selected for performance verification factors such as repeatability, reproducibility and robustness (1.39% variance between days, 24% variance between analysts and 4.07% variance in analysis error). The qPCR standardized and validated in this research proved to be reliable for the diagnosis of PR and may be used in diagnostic laboratories that follow ISO 17025 and ISO 16140.
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Liu, Bohan, Hao Chang, Dong Yang, Feifei Yang, Qiushuang Wang, Yujiao Deng, Lijun Li, et al. "A deep learning framework assisted echocardiography with diagnosis, lesion localization, phenogrouping heterogeneous disease, and anomaly detection." Scientific Reports 13, no. 1 (January 2, 2023). http://dx.doi.org/10.1038/s41598-022-27211-w.
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AbstractEchocardiography is the first-line diagnostic technique for heart diseases. Although artificial intelligence techniques have made great improvements in the analysis of echocardiography, the major limitations remain to be the built neural networks are normally adapted to a few diseases and specific equipment. Here, we present an end-to-end deep learning framework named AIEchoDx that differentiates four common cardiovascular diseases (Atrial Septal Defect, Dilated Cardiomyopathy, Hypertrophic Cardiomyopathy, prior Myocardial Infarction) from normal subjects with performance comparable to that of consensus of three senior cardiologists in AUCs (99.50% vs 99.26%, 98.75% vs 92.75%, 99.57% vs 97.21%, 98.52% vs 84.20%, and 98.70% vs 89.41%), respectively. Meanwhile, AIEchoDx accurately recognizes critical lesion regions of interest along with each disease by visualizing the decision-making process. Furthermore, our analysis indicates that heterogeneous diseases, like dilated cardiomyopathy, could be classified into two phenogroups with distinct clinical characteristics. Finally, AIEchoDx performs efficiently as an anomaly detection tool when applying handheld device-produced videos. Together, AIEchoDx provides a potential diagnostic assistant tool in either cart-based echocardiography equipment or handheld echocardiography device for primary and point-of-care medical personnel with high diagnostic performance, and the application of lesion region identification and heterogeneous disease phenogrouping, which may broaden the application of artificial intelligence in echocardiography.
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Vudriko, Patrick, Abel B. Ekiri, Isabella Endacott, Sitira Williams, Nyangi Gityamwi, Joseph Byaruhanga, Ruth Alafiatayo, et al. "A Survey of Priority Livestock Diseases and Laboratory Diagnostic Needs of Animal Health Professionals and Farmers in Uganda." Frontiers in Veterinary Science 8 (September 23, 2021). http://dx.doi.org/10.3389/fvets.2021.721800.
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Background: Despite the investments made in veterinary diagnostic laboratory service delivery in Uganda, the scope and level of utilization remains low. This study aimed to determine the priority livestock diseases for which farmers and animal health professionals require veterinary diagnostic laboratory services, document the perceptions and opinions of key stakeholders on veterinary diagnostic laboratory services, and determine the factors that influence the delivery and utilization of animal disease diagnostic services in Uganda.Methods: A qualitative study approach involving a survey and key informant interviews was used to collect relevant data from four stakeholder groups: animal health workers, laboratory technologists and technicians, farmers, and key informants. The survey data were exported to excel, and descriptive statistics performed. The key informant interview recordings were transcribed, and thematic analysis performed.Results: The most reported diseases and conditions for which diagnostic services were needed were hemoparasites (including East Coast fever, anaplasmosis, babesiosis, and trypanosomosis), viral (including Foot and mouth disease, lumpy skin disease, rift valley fever, and papillomatosis), bacteria (including brucellosis, colibacillosis, anthrax, leptospirosis, and paratuberculosis) and protozoa diseases (coccidiosis), endoparasites (helminths), and mastitis. The most common diagnostic laboratory tests requested by clients, but laboratories were unable to provide included: rapid tests for contagious bovine pleuropneumonia, Foot and mouth disease, Newcastle disease, acaricide analysis, culture and antimicrobial sensitivity test, serology, and complete blood count. The most frequently reported challenges to providing diagnostic laboratory services were poor or lack of relevant equipment, insufficient or lack of supplies and reagents, high cost of reagents, inadequate or lack of laboratory staff to perform tests, and inadequate training of laboratory staff.Conclusions: This study highlighted the need to improve provision of laboratory diagnostic services to meet the prioritized diagnostic needs of farmers and animal health professionals. Increased intersectoral engagement and funding support from the private, industry, and government sectors is necessary to help address the observed challenges to provision of diagnostic laboratory services, including equipping of the laboratories, provision of supplies, and hiring and training of laboratory staff. Finally, the findings also suggest that the education of farmers and animal health workers on the value and benefits of laboratory diagnostic services may contribute to increase in sample submission and subsequent demand for diagnostic laboratory services.
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Okpara, Ihunanya Chinyere, and Efosa Kenneth Oghagbon. "Mitigating the Risk of COVID-19 Deaths in Cardiovascular Disease Patients in Africa Resource Poor Communities." Frontiers in Cardiovascular Medicine 8 (February 16, 2021). http://dx.doi.org/10.3389/fcvm.2021.626115.
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The novel coronavirus disease 2019 (Covid-19) pandemic has affected millions of patients in almost all countries with over one million cases recorded in Africa where it is a major health challenge. Covid-19 is known to have significant implications for those with pre-existing cardiovascular disease (CVD) and their cardiologists. Patients with pre-existing CVD are at increased risk of morbidity and mortality from Covid-19 due to associated direct and indirect life threatening cardiovascular (CV) complications. Mitigating the risk of such Covid-19 deaths in resource poor communities requires the institution of preventive measures at the primary, secondary and tertiary levels of preventive phenomenon with emphasis at the first two levels. General preventive measures, screening and monitoring of CVD patients for complications and modification of drug treatment and other treatment methods will need to be implemented. Health policy makers and manager should provide required training and retraining of CV health care workers managing Covid-19 patients with CVD, provision of health education, personal protective equipment (PPE), and diagnostic kits.
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Wang, Hao, Hongzhao Li, Bo Tang, Chen Ye, Meiqing Han, Lin Teng, Min Yue, and Yan Li. "Fast and sensitive differential diagnosis of pseudorabies virus-infected versus pseudorabies virus-vaccinated swine using CRISPR-Cas12a." Microbiology Spectrum, December 11, 2023. http://dx.doi.org/10.1128/spectrum.02617-23.
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ABSTRACT Pseudorabies virus (PRV) is the causative pathogen of Aujeszky’s disease. It causes high mortality and miscarriage rates in the infected swine, leading to tremendous economic losses in the global swine industry. PRV has also been demonstrated to trigger viral encephalitis in humans. The eradication policy and large-scale vaccination have been adopted globally as the most effective strategy against PRV. A simple, fast, and sensitive diagnostic method is highly demanded to differentiate between vaccinated and infected swine. Herein, we designed a detection system combining multienzyme isothermal rapid amplification (MIRA) and CRISPR-Cas12a (termed MIRA-Cas12a), characterized by high sensitivity and specificity, low cost, less equipment, and convenient visualization. By targeting the gB, gE, and TK genes of PRV, the MIRA-Cas12a assay is able to distinguish the infected, uninfected, and vaccinated swine by the naked eyes in 40 min (from DNA extraction to result readout) and with comparable sensitivity to conventional quantitative PCR. A 37°C heater and a source of blue light are all the equipment required to detect PRV. Thus, the MIRA-Cas12a detection will facilitate PRV surveillance and minimize the financial losses to the swine industry. IMPORTANCE Pseudorabies virus (PRV) causes high mortality and miscarriage rates in the infected swine, and the eradication policy coupled with large-scale vaccination of live attenuated vaccines has been adopted globally against PRV. Differential diagnosis of the vaccinated and infected swine is highly demanded. Our multienzyme isothermal rapid amplification (MIRA)-Cas12a detection method described in this study can diagnose PRV with a superior sensitivity comparable to the quantitative PCR (qPCR) and a competitive detection speed (only half the time as qPCR needs). The portable feature and the simple procedure of MIRA-Cas12a make it easier to deploy for clinical diagnosis, even in resource-limited settings. The MIRA-Cas12a method would provide immediate and accurate diagnostic information for policymakers to respond promptly.
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Cafezeiro, C., A. C. Alencar Neto, B. V. K. Bueno, J. H. Rissato, N. M. Pereira, F. L. Pereira, F. J. A. Ramires, et al. "Non-invasive assessment of myocardial stiffness by the two-dimensional shear wave elastography ultrasound technique in patients with amyloidosis and Fabry disease." European Heart Journal 44, Supplement_2 (November 2023). http://dx.doi.org/10.1093/eurheartj/ehad655.045.
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Abstract Background Cardiac amyloidosis and Fabry disease are cardiomyopathies that evolve with structural alteration of the ventricular walls, diastolic dysfunction and heart failure. Diastolic dysfunction encompass myocardial stiffness and impaired relaxation. Cardiac elastography has been proposed as a diagnostic modality for the non-invasive assessment of myocardial stiffness. Purpose The aim of this study was to investigate if myocardial shear wave elastography could assess myocardial stiffness in Healthy volunteers, Fabry disease and variant transthyretin amyloidosis (ATTRv) patients with cardiac involvement and correlate with other complementary imaging and laboratory tests (electrocardiogram, 2D echocardiogram, troponin and BNP) and with the 6-minute walk test. Methods We prospectively included 60 adults: 20 patients with Fabry disease, 20 patients with ATTRv and 20 patients as control group. Echocardiography, electrocardiogram and laboratory evaluations were performed. Elastography assessment of myocardial stiffness was performed using an ultrasound equipment with a multifrequency convex transducer, under specific adjustment of the equipment for performing myocardial elastography. Results Myocardial Stiffness was significantly higher in Cardiac Amyloidosis patients than in healthy volunteers in anteroseptal basal segment (ASB) (PLAX 6.95 ± 1.4 kPa vs. 5.45 ± 1.1 kPa, respectively, p=0.02; PSAX 6.85 ± 1.4 kPa vs. 5.4 ± 1.2 kPa, respectively, p=0.02) and right ventricle (RV) (5.9 ± 2.6 kPa vs. 4.0 ± 0.7 kPa, respectively, p=0.003) and no difference in anteroseptal mid and septal apical. Statistically difference between Fabry Disease patients and Cardiac Amyloidosis group was found in right ventricle (5.9 ± 2.6 kPa vs. 4.4 ± 1.0 kPa, respectively, p=0.01). Conclusion Myocardial Stiffness was significantly higher in patients with Cardiac Amyloidosis compared with healthy volunteers in anteroseptal basal and right ventricle, but with no difference in anteroseptal mid and septal apical. Cardiac Amyloidosis myocardial stiffness was statistically higher in right ventricle compared with Fabry Disease group.