0000000000746763

AUTHOR

E. Mirrakhimov

showing 2 related works from this author

The impact of type of dietary protein, animal versus vegetable, in modifying cardiometabolic risk factors: A position paper from the International Li…

2020

Proteins play a crucial role in metabolism, in maintaining fluid and acid-base balance and antibody synthesis. Dietary proteins are important nutrients and are classified into: 1) animal proteins (meat, fish, poultry, eggs and dairy), and, 2) plant proteins (legumes, nuts and soy). Dietary modification is one of the most important lifestyle changes that has been shown to significantly decrease the risk of cardiovascular (CV) disease (CVD) by attenuating related risk factors. The CVD burden is reduced by optimum diet through replacement of unprocessed meat with low saturated fat, animal proteins and plant proteins. In view of the available evidence, it has become acceptable to emphasize the …

AdultMaleDietary proteinWeight lossCardiometabolic Risk Factorsfood and beveragesMiddle AgedRecommended Dietary AllowancesCardiovascular diseasePlant Proteins DietaryCardiovascular disease Cholesterol Dietary protein Metabolic syndrome Weight loss Adult Aged Animal Proteins Dietary Cardiometabolic Risk Factors Cardiovascular Diseases Diet Healthy Expert Testimony Female Humans Male Middle Aged Plant Proteins Dietary Young Adult Recommended Dietary AllowancesMetabolic syndromeYoung AdultCholesterolCardiovascular DiseasesAnimal Proteins DietaryHumansFemaleDiet HealthyExpert TestimonyAged
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Impact of clinical phenotypes on management and outcomes in European atrial fibrillation patients: a report from the ESC-EHRA EURObservational Resear…

2021

Abstract Background Epidemiological studies in atrial fibrillation (AF) illustrate that clinical complexity increase the risk of major adverse outcomes. We aimed to describe European AF patients’ clinical phenotypes and analyse the differential clinical course. Methods We performed a hierarchical cluster analysis based on Ward’s Method and Squared Euclidean Distance using 22 clinical binary variables, identifying the optimal number of clusters. We investigated differences in clinical management, use of healthcare resources and outcomes in a cohort of European AF patients from a Europe-wide observational registry. Results A total of 9363 were available for this analysis. We identified three …

RegistrieResearch Reportmedicine.medical_specialtyMajor adverse outcomeCardiovascular risk factorsCluster analysisRisk FactorsInternal medicineClinical phenotypeAtrial FibrillationEpidemiologyHumansMedicineRegistriesCluster analysiAtrial fibrillation; Clinical management; Clinical phenotypes; Cluster analysis; Major adverse outcomes; Humans; Phenotype; Registries; Research Report; Risk Factors; Atrial FibrillationClinical managementbusiness.industryProportional hazards modelRisk FactorHazard ratioRAtrial fibrillationClinical phenotypesMajor adverse outcomesGeneral Medicinemedicine.diseaseAtrial fibrillationConfidence intervalPhenotypeCohortMedicineObservational studybusinessResearch ArticleHumanBMC Medicine
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