A5088937036- Diabetes, Cardiovascular Risks, and Lipoproteins
- Diabetes Treatment and Management
- Statistical Methods in Clinical Trials
- Blood Pressure and Hypertension Studies
- Global Cancer Incidence and Screening
- Lipoproteins and Cardiovascular Health
- COVID-19 Clinical Research Studies
- Chronic Kidney Disease and Diabetes
- Health Systems, Economic Evaluations, Quality of Life
- Cardiac Health and Mental Health
- Career Development and Diversity
- Sepsis Diagnosis and Treatment
- BRCA gene mutations in cancer
- Health Promotion and Cardiovascular Prevention
- Artificial Intelligence in Healthcare
- Socioeconomic Development in MENA
- Chronic Disease Management Strategies
- Genetic factors in colorectal cancer
- Heart Rate Variability and Autonomic Control
- Mental Health Treatment and Access
- Heart rate and cardiovascular health
- Cardiovascular Disease and Adiposity
- Hemoglobinopathies and Related Disorders
- Diversity and Career in Medicine
- Cardiovascular Function and Risk Factors
United Arab Emirates University
2020-2024
Emirates Foundation
2024
Institute of Public Health Bengaluru
2022
Objective: The United Arab Emirates (UAE), with its characteristic local population, geography, and history, presents several risk factors for cardiovascular diseases (CVDs) in obese individuals. Obesity associated complications, including diabetes, atherogenic dyslipidemia, CVDs leading to significant health risks. In the present study, "Youths" defined as young people between 18 22 years. We assessed inflammation, oxidative stress biomarker levels their association endothelial dysfunction...
ObjectiveTo examine the association between plasma levels of soluble urokinase plasminogen activator receptor (suPAR) and incidence severe complications COVID-19.Methods403 RT-PCR-confirmed COVID-19 patients were recruited prospectively followed-up at a major hospital in United Arab Emirates. The primary endpoint was time from admission until development composite outcome, including acute respiratory distress syndrome (ARDS), intensive care unit (ICU) admission, or death any cause. Patients...
Data on breast cancer survival and its prognostic factors are lacking in the United Arab Emirates (UAE). Sociodemographic pathologic have been studied widely western populations but very limited this region. This study is first to report investigate associated with UAE.This a retrospective cohort involving 988 patients who were diagnosed histologically confirmed between January 2008 December 2012 at Tawam hospital, Al Ain, UAE. Patient followed from date of initial diagnosis until death any...
ABSTRACT Background A plethora of studies on COVID-19 investigating mortality and recovery have used the Cox Proportional Hazards (Cox PH) model without taking into account presence competing risks. We investigate, through extensive simulations, bias in estimating hazard ratio (HR) absolute risk reduction (ARR) death when risks are ignored, suggest an alternative method. Methods simulated a fictive clinical trial mimicking interventions such as Hydroxychloroquine, Remdesivir, or convalescent...
Introduction Evidence regarding the performance of cardiovascular disease (CVD) risk assessment tools is limited in United Arab Emirates (UAE). Therefore, we assessed agreement between various externally validated CVD UAE. Methods A secondary analysis Abu Dhabi Screening Program for Cardiovascular Risk Markers (AD-SALAMA) data, a large population-based cross-sectional survey conducted Dhabi, UAE during period 2009 until 2015, was performed July 2019. The included 2,621 participants without...
Background Chronic diseases constitute a major public health problem in the United Arab Emirates (UAE) and are leading cause of mortality morbidity. have been found to be associated with an increased prevalence depression depressive symptoms. Depression can detrimental effect on prognosis disease quality life patients. Aims objectives This study aimed estimate correlates sample patients suffering from chronic Al-Ain city, UAE. Materials methods A cross-sectional survey based was conducted...
Abstract Aim To demonstrate the gain in predictive performance when cardiovascular disease (CVD) risk prediction tools (RPTs) incorporate repeated rather than only single measurements of factors. Materials and methods We used data from Exenatide Study Cardiovascular Event Lowering (EXSCEL) trial to compare quality predictions future major adverse events (MACE) with Cox proportional hazards model (using values factors) compared Bayesian joint measures factors). The MACE was calculated...
Thyroid cancer is the most common endocrine malignancy. It ranked second among females of Gulf Cooperation Council States and sixth United Arab Emirates population.We herein describe incidence distribution different types thyroid cancers demographic features patients diagnosed with in Emirate Abu Dhabi. Settings Design: The study design was Dhabi registry retrospective chart review.This a description between January 2012 December 2015 throughout period calculated. Gender, age, ethnicity,...
(1) Background: The present study aimed to assess the changes in blood pressure (BP) within first 6 months of treatment initiation a newly treated hypertensive cohort and identify factors that are associated with achieving target BP recommended by American (ACC/AHA, 2017), European (ESC/ESH, 2018), United Kingdom (NICE, 2019), International Society Hypertension (ISH, 2020) guidelines. (2) Methods: We analyzed 5308 incident outpatients across Abu Dhabi, Arab Emirates (UAE), 2017; each patient...
Introduction and Objective: Declining estimated glomerular filtration rate (eGFR) is a predictor for the development progression of chronic kidney disease incident cardiovascular (CVD). We used novel statistical approach to investigate role eGFR decline in predicting CVD events people with type 2 diabetes, both primary secondary prevention settings. Methods: Bayesian joint modelling repeated measures time event was applied Exenatide Study Cardiovascular Event Lowering (EXSCEL) examine...
Abstract Aim The decline in estimated glomerular filtration rate (eGFR), a significant predictor of cardiovascular disease (CVD), occurs heterogeneously people with diabetes because various risk factors. We investigated the role eGFR predicting CVD events type 2 both primary and secondary prevention settings. Materials Methods Bayesian joint modelling repeated measures time to event was applied Exenatide Study Cardiovascular Event Lowering (EXSCEL) trial examine association between slope...
<ns4:p>Background The representation of women in science, technology, engineering, and mathematics (STEM) is disproportionate to graduates from STEM fields. There limited research addressing challenges facing retention the UAE. Methods A cross-sectional study using a validated questionnaire was conducted. total 165 participants were enrolled; 62% males 35% females. Results More believed there gender inequality (47% versus 28%). 44% female experienced their career. Men significantly less...
Type 1 diabetes mellitus (T1DM) is an autoimmune disease characterized by the chronic inflammation and cause of endothelial dysfunction (ED). Heart rate variability (HRV) a marker sympathetic parasympathetic autonomic nervous system dysfunction. We investigated association lipid profile, inflammatory biomarkers, dysfunction, heart in adolescents with T1DM among UAE population.
Background Low hemoglobin (Hb) level is a leading cause of many adverse pregnancy outcomes. Patterns changes in Hb levels during are not well understood. Aim This study estimated levels, described its changing patterns across gestational trimesters, and identified factors associated with these among pregnant women. Materials methods Data from the ongoing maternal child health cohort study–The Mutaba’ah Study, was used (N = 1,120). KML machine learning algorithm applied to identify three...
In the field of cardiovascular disease diagnosis, electrocardiogram (ECG) signals are used to identify conditions like arrhythmia and myocardial infarction (MI). These reflect electrical activity heart help cardiologists diagnose cardiac disorders. However, due limited amplitude duration ECG signals, visual interpretation is challenging. Therefore, machine learning models have become valuable for automatically detecting MI using data. this paper, we aim develop an automatic technique...