1.
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.
2.
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.
3.
High-density lipoprotein as a therapeutic target: a systematic review.
Singh, IM, Shishehbor, MH, Ansell, BJ
JAMA. 2007;(7):786-98
Abstract
CONTEXT High-density lipoprotein cholesterol (HDL-C) is a cardiovascular risk factor that is gaining substantial interest as a therapeutic target. OBJECTIVES To review the current and emerging strategies that modify high-density lipoproteins (HDLs). DATA SOURCES Systematic search of English-language literature (1965-May 2007) in MEDLINE and the Cochrane database, using the key words HDL-C and apolipoprotein A-I and the subheadings reverse cholesterol transport, CVD [cardiovascular disease] prevention and control, drug therapy, and therapy; review of presentations made at major cardiovascular meetings from 2003-2007; and review of ongoing trials from ClinicalTrials.gov and current guidelines from major cardiovascular societies. STUDY SELECTION AND DATA EXTRACTION Study selection was prioritized to identify randomized controlled trials over meta-analyses over mechanistic studies; identified studies also included proof-of-concept studies and key phase 1 through 3 trials of novel agents. Study eligibility was assessed by 2 authors; disagreements were resolved by consensus with the third. DATA SYNTHESIS Of 754 studies identified, 31 randomized controlled trials met the inclusion criteria. Currently available therapeutic and lifestyle strategies, when optimized, increase HDL-C levels by 20% to 30%. While basic and small pilot studies have shown promise, proof that increasing HDL-C levels confers a reduction in major cardiovascular outcomes independent of changes in levels of low-density lipoprotein cholesterol or triglycerides has been more elusive. Some novel therapeutic agents in human studies appear to effectively increase HDL-C levels, whereas other novel strategies that target HDL metabolism or function may have minimal effect on HDL-C levels. CONCLUSIONS At present there is modest evidence to support aggressively increasing HDL-C levels in addition to what is achieved by lifestyle modification alone. Ongoing clinical trials that target specific pathways in HDL metabolism may help expand cardiovascular treatment options.