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Online Parenting Intervention for Children's Eating and Mealtime Behaviors: Protocol of a Randomized Controlled Trial.
Rathore, V, Mitchell, AE, Morawska, A, Tadakamadla, SK
Healthcare (Basel, Switzerland). 2022;(5)
Abstract
INTRODUCTION Obesity and overweight are significant health problems among Australian children. Parents play a vital role in establishing healthy eating behaviors in their children. However, parents often experience difficulties in implementing effective parenting practices and lack confidence in their ability to help children adopt these behaviors. This trial will evaluate the efficacy of an online program, Healthy Habits Triple P, in improving children's snacking and mealtime behaviors and related parenting practices. METHODS AND ANALYSIS This is a single-blinded, randomized controlled trial for parents of young Australian children aged 2-6 years. Participants will be recruited through childcare centers, social media, online parent forums and existing networks. The participants in the intervention arm will receive access to a web-based parenting intervention in addition to nutrition-related information for parents published by the National Health and Medical Research Council of Australia; those in the control arm will receive nutrition-related information only. After the completion of the study, the parenting intervention will be offered to the control arm. The primary outcome will be improvement in children's eating habits. The secondary outcomes include parents' self-efficacy, confidence, children's mealtime behaviors and mealtime parenting strategies. Both primary and secondary outcomes will be evaluated through online-administered, validated parent-reported questionnaires. We will also undertake a quantitative and qualitative evaluation of the practicality and acceptability of the intervention.
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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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In vitro studies evaluating the efficacy of mouth rinses on Sars-Cov-2: A systematic review.
Tadakamadla, J, Boccalari, E, Rathore, V, Dolci, C, Tartaglia, GM, Tadakamadla, SK
Journal of infection and public health. 2021;(9):1179-1185
Abstract
This systematic review aims to evaluate the evidence on the efficacy of mouth rinses on SARS-CoV-2 from in vitro studies. Five electronic databases were searched up to February 2021; no language or time restrictions were used. Two independent reviewers conducted both selection and data extraction processes. The toxicological data reliability assessment tool was used to evaluate the risk of bias. Starting from 239 articles, retrieved by the electronic search, only eight studies were included in our systematic review. Povidone Iodine (PVP-I) was effective in killing SARS-CoV-2, demonstrated higher virucidal activity than other commonly used active ingredients. Conflicting results were found about the effectiveness of Chlorhexidine (CHX) while hydrogen peroxide (H2O2) proved less effective than PVP-I. Other active ingredients, such as quaternary ammonium compounds and Ethanol (particularly when combined with essential oils), have also shown promising results in reducing viral load, with results comparable to PVP-I.
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Lipid profile as an indicator of COVID-19 severity: A systematic review and meta-analysis.
Mahat, RK, Rathore, V, Singh, N, Singh, N, Singh, SK, Shah, RK, Garg, C
Clinical nutrition ESPEN. 2021;:91-101
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Abstract
BACKGROUND Coronavirus disease-2019 (COVID-19) is a global pandemic. Studies reported dyslipidemia in patients with COVID-19. Herein, we conducted a systematic review and meta-analysis of published articles to evaluate the association of the lipid profile with the severity and mortality in COVID-19 patients. METHODS PubMed/Medline, Europe PMC, and Google Scholar were searched for studies published between January 1, 2020 and January 13, 2021. Random or Fixed effects models were used to calculate the mean difference (MD) and 95% confidence intervals (CIs). Statistical heterogeneity was assessed using Cochran's Q test and I2 statistics. RESULTS This meta-analysis included 19 studies. Of which, 12 studies were categorized by severity, 04 studies by mortality, and 03 studies by both severity and mortality. Our findings revealed significantly decreased levels of total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), and low-density lipoprotein cholesterol (LDL-C) in the severe group when compared with the non-severe group in a random effect model. Similarly, random effect model results demonstrated significantly lower levels of HDL-C and LDL-C in the non-survivor group when compared with the survivor group. The level of TC was also found to be decreased in the non-survivor group when compared to the survivor group in a fixed-effect model. CONCLUSION In conclusion, the lipid profile is associated with both the severity and mortality in COVID-19 patients. Hence, the lipid profile may be used for assessing the severity and prognosis of COVID-19. PROSPERO REGISTRATION NUMBER CRD42021216316.
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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.