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[This corrects the article DOI: 10.2196/46036.].
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BACKGROUND: A plethora of weight management apps are available, but many individuals, especially those living with overweight and obesity, still struggle to achieve adequate weight loss. An emerging area in weight management is the support for one's self-regulation over momentary eating impulses. OBJECTIVE: This study aims to examine the feasibility and effectiveness of a novel artificial intelligence-assisted weight management app in improving eating behaviors in a Southeast Asian cohort. METHODS: A single-group pretest-posttest study was conducted. Participants completed the 1-week run-in period of a 12-week app-based weight management program called the Eating Trigger-Response Inhibition Program (eTRIP). This self-monitoring system was built upon 3 main components, namely, (1) chatbot-based check-ins on eating lapse triggers, (2) food-based computer vision image recognition (system built based on local food items), and (3) automated time-based nudges and meal stopwatch. At every mealtime, participants were prompted to take a picture of their food items, which were identified by a computer vision image recognition technology, thereby triggering a set of chatbot-initiated questions on eating triggers such as who the users were eating with. Paired 2-sided t tests were used to compare the differences in the psychobehavioral constructs before and after the 7-day program, including overeating habits, snacking habits, consideration of future consequences, self-regulation of eating behaviors, anxiety, depression, and physical activity. Qualitative feedback were analyzed by content analysis according to 4 steps, namely, decontextualization, recontextualization, categorization, and compilation. RESULTS: The mean age, self-reported BMI, and waist circumference of the participants were 31.25 (SD 9.98) years, 28.86 (SD 7.02) kg/m2, and 92.60 (SD 18.24) cm, respectively. There were significant improvements in all the 7 psychobehavioral constructs, except for anxiety. After adjusting for multiple comparisons, statistically significant improvements were found for overeating habits (mean -0.32, SD 1.16; P<.001), snacking habits (mean -0.22, SD 1.12; P<.002), self-regulation of eating behavior (mean 0.08, SD 0.49; P=.007), depression (mean -0.12, SD 0.74; P=.007), and physical activity (mean 1288.60, SD 3055.20 metabolic equivalent task-min/day; P<.001). Forty-one participants reported skipping at least 1 meal (ie, breakfast, lunch, or dinner), summing to 578 (67.1%) of the 862 meals skipped. Of the 230 participants, 80 (34.8%) provided textual feedback that indicated satisfactory user experience with eTRIP. Four themes emerged, namely, (1) becoming more mindful of self-monitoring, (2) personalized reminders with prompts and chatbot, (3) food logging with image recognition, and (4) engaging with a simple, easy, and appealing user interface. The attrition rate was 8.4% (21/251). CONCLUSIONS: eTRIP is a feasible and effective weight management program to be tested in a larger population for its effectiveness and sustainability as a personalized weight management program for people with overweight and obesity. TRIAL REGISTRATION: ClinicalTrials.gov NCT04833803; https://classic.clinicaltrials.gov/ct2/show/NCT04833803.
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Inteligencia Artificial , Conducta Alimentaria , Aplicaciones Móviles , Humanos , Conducta Alimentaria/psicología , Adulto , Femenino , Masculino , Obesidad/psicología , Obesidad/terapia , Persona de Mediana EdadRESUMEN
Improved upstream primary prevention of cardiovascular disease (CVD) would enable more individuals to lead lives free of CVD. However, there remain limitations in the current provision of CVD primary prevention, where artificial intelligence (AI) may help to fill the gaps. Using the data informatics capabilities at the National University Health System (NUHS), Singapore, empowered by the Endeavour AI system, and combined large language model (LLM) tools, our team has created a real-time dashboard able to capture and showcase information on cardiovascular risk factors at both individual and geographical level- CardioSight. Further insights such as medication records and data on area-level socioeconomic determinants allow a whole-of-systems approach to promote healthcare delivery, while also allowing for outcomes to be tracked effectively. These are paired with interventions, such as the CHronic diseAse Management Program (CHAMP), to coordinate preventive cardiology care at a pilot stage within our university health system. AI tools in synergy allow the identification of at-risk patients and actionable steps to mitigate their health risks, thereby closing the gap between risk identification and effective patient care management in a novel CVD prevention workflow.
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Cardiac blood flow is a critical determinant of human health. However, the definition of its genetic architecture is limited by the technical challenge of capturing dynamic flow volumes from cardiac imaging at scale. We present DeepFlow, a deep-learning system to extract cardiac flow and volumes from phase-contrast cardiac magnetic resonance imaging. A mixed-linear model applied to 37,653 individuals from the UK Biobank reveals genome-wide significant associations across cardiac dynamic flow volumes spanning from aortic forward velocity to aortic regurgitation fraction. Mendelian randomization reveals a causal role for aortic root size in aortic valve regurgitation. Among the most significant contributing variants, localizing genes (near ELN, PRDM6 and ADAMTS7) are implicated in connective tissue and blood pressure pathways. Here we show that DeepFlow cardiac flow phenotyping at scale, combined with genotyping data, reinforces the contribution of connective tissue genes, blood pressure and root size to aortic valve function.
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Aorta , Insuficiencia de la Válvula Aórtica , Humanos , Velocidad del Flujo Sanguíneo/fisiología , Imagen por Resonancia Magnética/métodos , Válvula AórticaRESUMEN
Conrad Waddington's epigenetics landscape has provided a metaphorical framework for how cells progress from undifferentiated states to one of several discrete, distinct, differentiated cell fates. The understanding of epigenetics has evolved over time, with DNA methylation being the most studied epigenetic modification, followed by histone modifications and non-coding RNA. Cardiovascular diseases (CVD) are leading contributors to death worldwide, with the prevalence of CVDs increasing across the last couple of decades. Significant amount of resources being poured into researching key mechanisms and underpinnings of the various CVDs. These molecular studies looked at the genetics, epigenetics as well as the transcriptomics of various cardiovascular conditions, aiming to provide mechanistic insights. It has paved the way for therapeutics to be developed and in recent years, epi-drugs for the treatment of CVDs. This chapter aims to cover the various roles of epigenetics in the context of cardiovascular health and disease. The following will be examined in detail: the developments in basic experimental techniques used to study epigenetics, the role of epigenetics in various CVDs (hypertension, atrial fibrillation, atherosclerosis, and heart failure), and current advances in epi-therapeutics, providing a holistic view of the current concerted efforts in advancing the field of epigenetics in CVDs.
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Enfermedades Cardiovasculares , Sistema Cardiovascular , Humanos , Epigénesis Genética , Sistema Cardiovascular/metabolismo , Metilación de ADN , Enfermedades Cardiovasculares/tratamiento farmacológico , Procesamiento Proteico-PostraduccionalRESUMEN
Ischemic stroke is a heterogeneous condition influenced by a combination of genetic and environmental factors. Recent advancements have explored genetics in relation to various aspects of ischemic stroke, including the alteration of individual stroke occurrence risk, modulation of treatment response, and effectiveness of post-stroke functional recovery. This article aims to review the recent findings from genetic studies related to various clinical and molecular aspects of ischemic stroke. The potential clinical applications of these genetic insights in stratifying stroke risk, guiding personalized therapy, and identifying new therapeutic targets are discussed herein.
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While various influencing factors of overweight and obesity have been identified, the underlying mechanism remains unclear. We examined the relationships among sociodemographic, behavioral, and psychological factors on anthropometry in a multi-ethnic population with overweight and obesity. Participants (N = 251) were recruited from January to October 2022. Mean age and self-reported BMI were 31.7 ± 10.1 years and 29.2 ± 7.2 kg/m2. Participants were mostly female (52.4%) and overweight (58.2%). Multivariate multiple regression was performed using maximum likelihood estimation. Body mass index was associated with waist circumference, age, sex, race, marital status, education level, residential region, overeating habit, immediate thinking, self-regulation, and physical activity, but not anxiety, depression, or the intention to change eating habits. Final model indicated good fit: χ2 (30, N = 250) = 33.5, p = 0.32, CFI = 0.993, TLI = 0.988, RMSEA = 0.022, and SRMR = 0.041. Direct effects were found between BMI and overeating (ß = 0.10, p = 0.004), race (ß = -0.82, p < 0.001), marital status (ß = -0.42, p = 0.001), and education level (ß = -0.28, p = 0.019). Crisps (68.8%), cake (66.8%) and chocolate (65.6%) were identified as the most tempting foods. Immediate thinking indirectly increased overeating habits through poor self-regulation, although sociodemographic characteristics better predicted anthropometry than psycho-behavioral constructs.
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Sobrepeso , Pueblos del Sudeste Asiático , Adulto , Humanos , Femenino , Masculino , Índice de Masa Corporal , Sobrepeso/epidemiología , Obesidad/epidemiología , Etnicidad , HiperfagiaRESUMEN
We conducted an umbrella review to consolidate the evidence of adopting plant-based diets on anthropometric and cardiometabolic outcomes. Six electronic databases (CINAHL, EMBASE, PubMed, Scopus, the Cochrane Library, and Web of Science) were searched for systematic reviews with meta-analysis (SRMAs) published from each journal's inception until 1 October 2022. Effect sizes from SRMAs and primary studies were pooled separately using random effects models. Overlapping primary studies were removed for primary studies' analyses. Seven SRMAs representing 51 primary studies were included, suggesting significant benefits of plant-based diets on weight (-2.09 kg, 95% CI: -3.56, -0.62 kg, p = 0.01, I2 = 95.6%), body mass index (-0.95 kg/m2, 95% CI: -1.26, -0.63 kg/m2, p = 0.002; I2 = 45.1%), waist circumference (-2.20 cm, 95% CI: -0.08, 0.00 cm, p = 0.04; I2 = 88.4%), fasting blood glucose (-0.11 mmol/L, 95% CI: -0.13, -0.09 mmol/L, p < 0.001, I2 = 18.2%), and low-density lipoprotein cholesterol (-0.31 mmol/L, 95% CI: -0.41, -0.20 mmol/L, p < 0.001, I2 = 65.6%). Changes in high-density lipoprotein cholesterol, triglycerides, and blood pressure were not statistically significant. Generally, plant-based diets were recommended to improve anthropometry, lipid profile, and glucose metabolism. However, findings should be interpreted with caution, because most of the reviews were rated to be of low credibility of evidence and were largely based on Western eating habits and traditions, which may limit the generalizability of findings.
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Enfermedades Cardiovasculares , Dieta Vegetariana , Adulto , Humanos , Índice de Masa Corporal , Enfermedades Cardiovasculares/prevención & control , LDL-Colesterol , Revisiones Sistemáticas como AsuntoRESUMEN
OBJECTIVE: With rising prevalence of hypertension and obesity, the effect of hypertension in obesity remains an important global issue. The prognosis of the US general population with obesity based on hypertension control was examined. METHODS: This study examined participants from the National Health and Nutrition Examination Survey between 1999 and 2018. Individuals with obesity were stratified into no hypertension, controlled hypertension, and uncontrolled hypertension. The study outcome was all-cause mortality. Cox regression of all-cause mortality was adjusted for age, sex, ethnicity, diabetes, and previous myocardial infarction. RESULTS: Of 16,386 individuals with obesity, 53.1% had no hypertension, 24.7% had controlled hypertension, and 22.2% had uncontrolled hypertension. All-cause mortality was significantly higher in uncontrolled hypertension (17.1%), followed by controlled hypertension (14.8%) and no hypertension (4.0%). Uncontrolled hypertension had the highest mortality risk (hazard ratio [HR] 1.34, 95% CI: 1.13-1.59, p = 0.001), followed by controlled hypertension (HR 1.21, 95% CI: 1.10-1.34, p < 0.001), compared with no hypertension after adjustment. The excess mortality trend was more pronounced in females, those with diabetes, and those older than age 65 years. CONCLUSIONS: The incremental mortality risk in controlled and uncontrolled hypertension, compared with the normotensive counterparts, irrespective of sex, age, and diabetes status, urges health care providers to optimize hypertension control and advocate weight loss to achieve better outcomes in obesity.
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Diabetes Mellitus , Hipertensión , Femenino , Humanos , Estados Unidos , Anciano , Encuestas Nutricionales , Hipertensión/epidemiología , Obesidad/epidemiología , Presión Sanguínea , Factores de RiesgoRESUMEN
BACKGROUND: Epicardial adipose tissue (EAT) has garnered attention as a prognostic and risk stratification factor for cardiovascular disease. This study, via meta-analyses, evaluates the associations between EAT and cardiovascular outcomes stratified across imaging modalities, ethnic groups, and study protocols. METHODS: Medline and Embase databases were searched without date restriction on May 2022 for articles that examined EAT and cardiovascular outcomes. The inclusion criteria were (1) studies measuring EAT of adult patients at baseline and (2) reporting follow-up data on study outcomes of interest. The primary study outcome was major adverse cardiovascular events. Secondary study outcomes included cardiac death, myocardial infarction, coronary revascularization, and atrial fibrillation. RESULTS: Twenty-nine articles published between 2012 and 2022, comprising 19 709 patients, were included in our analysis. Increased EAT thickness and volume were associated with higher risks of cardiac death (odds ratio, 2.53 [95% CI, 1.17-5.44]; P=0.020; n=4), myocardial infarction (odds ratio, 2.63 [95% CI, 1.39-4.96]; P=0.003; n=5), coronary revascularization (odds ratio, 2.99 [95% CI, 1.64-5.44]; P<0.001; n=5), and atrial fibrillation (adjusted odds ratio, 4.04 [95% CI, 3.06-5.32]; P<0.001; n=3). For 1 unit increment in the continuous measure of EAT, computed tomography volumetric quantification (adjusted hazard ratio, 1.74 [95% CI, 1.42-2.13]; P<0.001) and echocardiographic thickness quantification (adjusted hazard ratio, 1.20 [95% CI, 1.09-1.32]; P<0.001) conferred an increased risk of major adverse cardiovascular events. CONCLUSIONS: The utility of EAT as an imaging biomarker for predicting and prognosticating cardiovascular disease is promising, with increased EAT thickness and volume being identified as independent predictors of major adverse cardiovascular events. REGISTRATION: URL: https://www.crd.york.ac.uk/prospero; Unique identifier: CRD42022338075.
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Fibrilación Atrial , Infarto del Miocardio , Adulto , Humanos , Pericardio/diagnóstico por imagen , Tomografía Computarizada por Rayos X/métodos , Ecocardiografía , Tejido Adiposo/diagnóstico por imagenRESUMEN
Background: Malnutrition and obesity are interdependent pathologies along the same spectrum. We examined global trends and projections of disability-adjusted life years (DALYs) and deaths from malnutrition and obesity until 2030. Methods: Using data from the 2019 Global Burden of Disease study involving 204 countries and territories, trends in DALYs and deaths were described for obesity and malnutrition from 2000 to 2019, stratified by geographical regions (as defined by WHO) and Socio-Demographic Index (SDI). Malnutrition was defined according to the 10th revision of International Classification of Diseases codes for nutritional deficiencies, stratified by malnutrition type. Obesity was measured via body mass index (BMI) using metrics related to national and subnational estimates, defined as BMI ≥25 kg/m2. Countries were stratified into low, low-middle, middle, high-middle, and high SDI bands. Regression models were constructed to predict DALYs and mortality up to 2030. Association between age-standardised prevalence of the diseases and mortality was also assessed. Findings: In 2019, age-standardised malnutrition-related DALYs was 680 (95% UI: 507-895) per 100,000 population. DALY rates decreased from 2000 to 2019 (-2.86% annually), projected to fall 8.4% from 2020 to 2030. Africa and low SDI countries observed highest malnutrition-related DALYs. Age-standardised obesity-related DALY estimates were 1933 (95% UI: 1277-2640). Obesity-related DALYs rose 0.48% annually from 2000 to 2019, predicted to increase by 39.8% from 2020 to 2030. Highest obesity-related DALYs were in Eastern Mediterranean and middle SDI countries. Interpretation: The ever-increasing obesity burden, on the backdrop of curbing the malnutrition burden, is predicted to rise further. Funding: None.
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Through extensive multisystem phenotyping, the central aim of Project PICMAN is to correlate metabolic flexibility to measures of cardiometabolic health, including myocardial diastolic dysfunction, coronary and cerebral atherosclerosis, body fat distribution and severity of non-alcoholic fatty liver disease. This cohort will form the basis of larger interventional trials targeting metabolic inflexibility in the prevention of cardiovascular disease. Participants aged 21-72 years with no prior manifest atherosclerotic cardiovascular disease (ASCVD) are being recruited from a preventive cardiology clinic and an existing cohort of non-alcoholic fatty liver disease (NAFLD) in an academic medical centre. A total of 120 patients will be recruited in the pilot phase of this study and followed up for 5 years. Those with 10-year ASCVD risk ≥ 5% as per the QRISK3 calculator are eligible. Those with established diabetes mellitus are excluded. Participants recruited undergo a detailed assessment of health behaviours and physical measurements. Participants also undergo a series of multimodality clinical phenotyping comprising cardiac tests, vascular assessments, metabolic tests, liver and neurovascular testing. Blood samples are also being collected and banked for plasma biomarkers, 'multi-omics analyses' and for generation of induced pluripotent stem cells (iPSC). Extensive evidence points to metabolic dysregulation as an early precursor of cardiovascular disease, particularly in Asia. We hypothesise that quantifiable metabolic inflexibility may be representative of an individual in his/her silent, but high-risk progression towards insulin resistance, diabetes and cardiovascular disease. The platform for interdisciplinary cardiovascular-metabolic-neurovascular diseases (PICMAN) is a pilot, prospective, multi-ethnic cohort study.