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Cardiovascular Risk Stratification in Diabetic Retinopathy via Atherosclerotic Pathway in COVID-19/Non-COVID-19 Frameworks Using Artificial Intelligence Paradigm: A Narrative Review.
Munjral, S, Maindarkar, M, Ahluwalia, P, Puvvula, A, Jamthikar, A, Jujaray, T, Suri, N, Paul, S, Pathak, R, Saba, L, et al
Diagnostics (Basel, Switzerland). 2022;(5)
Abstract
Diabetes is one of the main causes of the rising cases of blindness in adults. This microvascular complication of diabetes is termed diabetic retinopathy (DR) and is associated with an expanding risk of cardiovascular events in diabetes patients. DR, in its various forms, is seen to be a powerful indicator of atherosclerosis. Further, the macrovascular complication of diabetes leads to coronary artery disease (CAD). Thus, the timely identification of cardiovascular disease (CVD) complications in DR patients is of utmost importance. Since CAD risk assessment is expensive for low-income countries, it is important to look for surrogate biomarkers for risk stratification of CVD in DR patients. Due to the common genetic makeup between the coronary and carotid arteries, low-cost, high-resolution imaging such as carotid B-mode ultrasound (US) can be used for arterial tissue characterization and risk stratification in DR patients. The advent of artificial intelligence (AI) techniques has facilitated the handling of large cohorts in a big data framework to identify atherosclerotic plaque features in arterial ultrasound. This enables timely CVD risk assessment and risk stratification of patients with DR. Thus, this review focuses on understanding the pathophysiology of DR, retinal and CAD imaging, the role of surrogate markers for CVD, and finally, the CVD risk stratification of DR patients. The review shows a step-by-step cyclic activity of how diabetes and atherosclerotic disease cause DR, leading to the worsening of CVD. We propose a solution to how AI can help in the identification of CVD risk. Lastly, we analyze the role of DR/CVD in the COVID-19 framework.
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Nutrition, atherosclerosis, arterial imaging, cardiovascular risk stratification, and manifestations in COVID-19 framework: a narrative review.
Munjral, S, Ahluwalia, P, Jamthikar, AD, Puvvula, A, Saba, L, Faa, G, Singh, IM, Chadha, PS, Turk, M, Johri, AM, et al
Frontiers in bioscience (Landmark edition). 2021;(11):1312-1339
Abstract
Background: Atherosclerosis is the primary cause of the cardiovascular disease (CVD). Several risk factors lead to atherosclerosis, and altered nutrition is one among those. Nutrition has been ignored quite often in the process of CVD risk assessment. Altered nutrition along with carotid ultrasound imaging-driven atherosclerotic plaque features can help in understanding and banishing the problems associated with the late diagnosis of CVD. Artificial intelligence (AI) is another promisingly adopted technology for CVD risk assessment and management. Therefore, we hypothesize that the risk of atherosclerotic CVD can be accurately monitored using carotid ultrasound imaging, predicted using AI-based algorithms, and reduced with the help of proper nutrition. Layout: The review presents a pathophysiological link between nutrition and atherosclerosis by gaining a deep insight into the processes involved at each stage of plaque development. After targeting the causes and finding out results by low-cost, user-friendly, ultrasound-based arterial imaging, it is important to (i) stratify the risks and (ii) monitor them by measuring plaque burden and computing risk score as part of the preventive framework. Artificial intelligence (AI)-based strategies are used to provide efficient CVD risk assessments. Finally, the review presents the role of AI for CVD risk assessment during COVID-19. Conclusions: By studying the mechanism of low-density lipoprotein formation, saturated and trans fat, and other dietary components that lead to plaque formation, we demonstrate the use of CVD risk assessment due to nutrition and atherosclerosis disease formation during normal and COVID times. Further, nutrition if included, as a part of the associated risk factors can benefit from atherosclerotic disease progression and its management using AI-based CVD risk assessment.
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Bidirectional link between diabetes mellitus and coronavirus disease 2019 leading to cardiovascular disease: A narrative review.
Viswanathan, V, Puvvula, A, Jamthikar, AD, Saba, L, Johri, AM, Kotsis, V, Khanna, NN, Dhanjil, SK, Majhail, M, Misra, DP, et al
World journal of diabetes. 2021;(3):215-237
Abstract
Coronavirus disease 2019 (COVID-19) is a global pandemic where several comorbidities have been shown to have a significant effect on mortality. Patients with diabetes mellitus (DM) have a higher mortality rate than non-DM patients if they get COVID-19. Recent studies have indicated that patients with a history of diabetes can increase the risk of severe acute respiratory syndrome coronavirus 2 infection. Additionally, patients without any history of diabetes can acquire new-onset DM when infected with COVID-19. Thus, there is a need to explore the bidirectional link between these two conditions, confirming the vicious loop between "DM/COVID-19". This narrative review presents (1) the bidirectional association between the DM and COVID-19, (2) the manifestations of the DM/COVID-19 loop leading to cardiovascular disease, (3) an understanding of primary and secondary factors that influence mortality due to the DM/COVID-19 loop, (4) the role of vitamin-D in DM patients during COVID-19, and finally, (5) the monitoring tools for tracking atherosclerosis burden in DM patients during COVID-19 and "COVID-triggered DM" patients. We conclude that the bidirectional nature of DM/COVID-19 causes acceleration towards cardiovascular events. Due to this alarming condition, early monitoring of atherosclerotic burden is required in "Diabetes patients during COVID-19" or "new-onset Diabetes triggered by COVID-19 in Non-Diabetes patients".
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Proposed low-density lipoprotein cholesterol goals for secondary prevention and familial hypercholesterolemia in India with focus on PCSK9 inhibitor monoclonal antibodies: Expert consensus statement from Lipid Association of India.
Puri, R, Mehta, V, Duell, PB, Nair, D, Mohan, JC, Yusuf, J, Dalal, JJ, Mishra, S, Kasliwal, RR, Agarwal, R, et al
Journal of clinical lipidology. 2020;(2):e1-e13
Abstract
BACKGROUND Rates of atherosclerotic cardiovascular disease (ASCVD) are strikingly high in India compared to Western countries and are increasing. Moreover, ASCVD events occur at a younger age with only modest hypercholesterolemia, most commonly with low levels of high-density lipoprotein cholesterol. The course of ASCVD also appears to be more fulminant with higher mortality. OBJECTIVE In light of these issues, the Lipid Association of India (LAI) endeavored to develop revised guidelines with more aggressive low-density lipoprotein cholesterol (LDL-C) goals in secondary prevention and for patients with familial hypercholesterolemia compared to guidelines in the United States and other countries. METHODS Owing to the paucity of clinical outcomes data in India, it was necessary to place major emphasis on expert opinion as a complement to randomized placebo-controlled data generated mostly in non-Indian cohorts. To facilitate this process, the LAI conducted a series of 19 meetings among 162 lipid specialists in 13 cities throughout India over a period of 11 months before formulating this expert consensus statement. RESULTS The LAI recommends an LDL-C goal <50 mg/dL in all patients in secondary prevention or very high-risk primary prevention but proposes an optional goal ≤30 mg/dL in category A extreme-risk patients (eg, coronary artery disease + familial hypercholesterolemia) and a recommended goal ≤30 mg/dL in category B extreme-risk patients [coronary artery disease + (1) diabetes and polyvascular disease/≥3 major ASCVD risk factors/end organ damage, or (2) recurrent acute coronary syndrome within 12 months despite LDL-C <50 mg/dL, or (3) homozygous familial hypercholesterolemia]. CONCLUSIONS More aggressive LDL-C goals are needed for prevention of ASCVD in India, as described in this expert consensus statement. Use of statins and ezetimibe needs to increase in India in combination with improved control of other ASCVD risk factors. Proprotein convertase subtilisin kexin type 9 inhibitors can improve LDL-C goal achievement in patients with refractory hypercholesterolemia.
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Wilson's disease: A new perspective review on its genetics, diagnosis and treatment.
Saba, L, Tiwari, A, Biswas, M, Gupta, SK, Godia-Cuadrado, E, Chaturvedi, A, Turk, M, Suri, HS, Orru, S, Sanches, JM, et al
Frontiers in bioscience (Elite edition). 2019;(1):166-185
Abstract
Wilson's disease (WD) is an autosomal recessive disorder which is caused by poor excretion of copper in mammalian cells. In this review, various issues such as effective characterization of ATP7B genes, scope of gene network topology in genetic analysis, pattern recognition using different computing approaches and fusion possibilities in imaging and genetic dataset are discussed vividly. We categorized this study into three major sections: (A) WD genetics, (B) diagnosis guidelines and (3) treatment possibilities. We addressed the scope of advanced mathematical modelling paradigms for understanding common genetic sequences and dominating WD imaging biomarkers. We have also discussed current state-of-the-art software models for genetic sequencing. Further, we hypothesized that involvement of machine and deep learning techniques in the context of WD genetics and image processing for precise classification of WD. These computing procedures signify changing roles of various data transformation techniques with respect to supervised and unsupervised learning models.
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Calcium detection, its quantification, and grayscale morphology-based risk stratification using machine learning in multimodality big data coronary and carotid scans: A review.
Banchhor, SK, Londhe, ND, Araki, T, Saba, L, Radeva, P, Khanna, NN, Suri, JS
Computers in biology and medicine. 2018;:184-198
Abstract
PURPOSE OF REVIEW Atherosclerosis is the leading cause of cardiovascular disease (CVD) and stroke. Typically, atherosclerotic calcium is found during the mature stage of the atherosclerosis disease. It is therefore often a challenge to identify and quantify the calcium. This is due to the presence of multiple components of plaque buildup in the arterial walls. The American College of Cardiology/American Heart Association guidelines point to the importance of calcium in the coronary and carotid arteries and further recommend its quantification for the prevention of heart disease. It is therefore essential to stratify the CVD risk of the patient into low- and high-risk bins. RECENT FINDING Calcium formation in the artery walls is multifocal in nature with sizes at the micrometer level. Thus, its detection requires high-resolution imaging. Clinical experience has shown that even though optical coherence tomography offers better resolution, intravascular ultrasound still remains an important imaging modality for coronary wall imaging. For a computer-based analysis system to be complete, it must be scientifically and clinically validated. This study presents a state-of-the-art review (condensation of 152 publications after examining 200 articles) covering the methods for calcium detection and its quantification for coronary and carotid arteries, the pros and cons of these methods, and the risk stratification strategies. The review also presents different kinds of statistical models and gold standard solutions for the evaluation of software systems useful for calcium detection and quantification. Finally, the review concludes with a possible vision for designing the next-generation system for better clinical outcomes.