Integrated Machine Learning and Deep Learning Models for Cardiovascular Disease Risk Prediction: A Comprehensive Comparative Study

Cardiovascular Diseases (CVDs) pose a significant global health challenge, necessitating accurate risk prediction for effective preventive measures. This comprehensive comparative study explores the performance of traditional Machine Learning (ML) and Deep Learning (DL) models in predicting CVD risk, utilizing a meticulously curated dataset derived from health records. Rigorous preprocessing, including normalization and outlier removal, enhances model robustness. Diverse ML models (Logistic Regression, Random Forest, Support Vector Machine, K-Nearest Neighbor, Decision Tree, and Gradient Boosting) are compared with a Long Short-Term Memory (LSTM) neural network for DL. Evaluation metrics include accuracy, ROC AUC, computation time, and memory usage. Results identify the Gradient Boosting Classifier and LSTM as top performers, demonstrating high accuracy and ROC AUC scores. Comparative analyses highlight model strengths and limitations, contributing valuable insights for optimizing predictive strategies. This study advances predictive analytics for cardiovascular health, with implications for personalized medicine. The findings underscore the versatility of intelligent systems in addressing health challenges, emphasizing the broader applications of ML and DL in disease identification beyond cardiovascular health.

Improving Prediction Efficiency of Machine Learning Models for Cardiovascular Disease in IoST-Based Systems through Hyperparameter Optimization

This study explores the impact of hyperparameter optimization on machine learning models for predicting cardiovascular disease using data from an IoST(Internet of Sensing Things)device.Ten distinct machine learning approaches were implemented and systematically evaluated before and after hyperparameter tuning.Significant improvements were observed across various models,with SVM and Neural Networks consistently showing enhanced performance metrics such as F1-Score,recall,and precision.The study underscores the critical role of tailored hyperparameter tuning in optimizing these models,revealing diverse outcomes among algorithms.Decision Trees and Random Forests exhibited stable performance throughout the evaluation.While enhancing accuracy,hyperparameter optimization also led to increased execution time.Visual representations and comprehensive results support the findings,confirming the hypothesis that optimizing parameters can effectively enhance predictive capabilities in cardiovascular disease.This research contributes to advancing the understanding and application of machine learning in healthcare,particularly in improving predictive accuracy for cardiovascular disease management and intervention strategies.

Dynamics of Advantageous Mutant Spread in Spatial Death-Birth and Birth-Death Moran Models

The spread of an advantageous mutation through a population is of fundamental interest in population genetics. While the classical Moran model is formulated for a well-mixed population, it has long been recognized that in real-world applications, the population usually has an explicit spatial structure which can significantly influence the dynamics. In the context of cancer initiation in epithelial tissue, several recent works have analyzed the dynamics of advantageous mutant spread on integer lattices, using the biased voter model from particle systems theory. In this spatial version of the Moran model, individuals first reproduce according to their fitness and then replace a neighboring individual. From a biological standpoint, the opposite dynamics, where individuals first die and are then replaced by a neighboring individual according to its fitness, are equally relevant. Here, we investigate this death-birth analogue of the biased voter model. We construct the process mathematically, derive the associated dual process, establish bounds on the survival probability of a single mutant, and prove that the process has an asymptotic shape. We also briefly discuss alternative birth-death and death-birth dynamics, depending on how the mutant fitness advantage affects the dynamics. We show that birth-death and death-birth formulations of the biased voter model are equivalent when fitness affects the former event of each update of the model, whereas the birth-death model is fundamentally different from the death-birth model when fitness affects the latter event.

Fatty liver is associated with an increased risk of diabetes and cardiovascular disease- Evidence from three different disease models: NAFLD, HCV and HIV

Fatty liver, which frequently coexists with necroinflammatory and fibrotic changes, may occur in the setting of nonalcoholic fatty liver disease(NAFLD) and chronic infections due to either hepatitis C virus(HCV) or human immunodeficiency virus(HIV). These three pathologic conditions are associated with an increased prevalence and incidence of cardiovascular disease(CVD) and type 2 diabetes(T2D). In this multidisciplinary clinical review, we aim to discuss the ever-expanding wealth of clinical and epidemiological evidence supporting a key role of fatty liver in the development of T2 D and CVD in patients with NAFLD and in those with HCV or HIV infections. For each of these three common diseases, the epidemiological features, pathophysiologic mechanisms and clinical implications of the presence of fatty liver in predicting the risk of incident T2 D and CVD are examined in depth. Collectively, the data discussed in this updated review, which follows an innovative comparative approach, further reinforce the conclusion that the presence of fatty/inflamed/fibrotic liver might be a shared important determinant for the development of T2 D and CVD in patients with NAFLD, HCV or HIV. This review may also open new avenues in the clinical and research arenas and paves the way for the planning of future, well-designed prospective and intervention studies.

Morphological Features of Complex Congenital Cardiovascular Anomalies in Fetuses:as Evaluated by Cast Models

Accurate prenatal diagnosis of complex congenital cardiovascular anomalies, vascular ones in particular, is still challenging. A fetal cardiovascular cast model can provide a copy of the cardiac chambers and great vessels with normal or pathological structures. This study was aimed to demonstrate three-dimensional anatomy of complex congenital cardiovascular anomalies in fetuses by means of corrosion casting. Twenty fetuses with prenatal-ultrasound-diagnosed complex cardiovascular anomalies were enrolled in this study（19 to 35 gestational weeks）. Fetal cardiovascular cast models were made by a corrosion casting technique. The specimens were injected with casting material via the umbilical vein, and then immersed in strong acid after casting fluid was solidified, to disclose the geometries of cardiovascular cavities. Nineteen cast models were successfully made from 20 specimens. The casts distinctly showed the morphological malformations and spatial relationship between cardiac chambers and great vessels. One hundred and eleven abnormalities were revealed by casting in the 19 specimens, including 34 abnormalities located in the cardiac chambers（3, 4 and 27 anomalies in the atria, atrioventricular valves and ventricles, respectively）, and 77 in the great vessels（28, 20, 24 and 5 anomalies in the aorta and its branches, the pulmonary artery, the ductus arteriosus and the major veins, respectively）. Corrosion casting can display three-dimensional anatomy of fetal complex cardiovascular anomalies. This improves our understanding of related pathomorphology and prenatal diagnosis.

Evolution and Prospects of Foundation Models: From Large Language Models to Large Multimodal Models

Since the 1950s,when the Turing Test was introduced,there has been notable progress in machine language intelligence.Language modeling,crucial for AI development,has evolved from statistical to neural models over the last two decades.Recently,transformer-based Pre-trained Language Models(PLM)have excelled in Natural Language Processing(NLP)tasks by leveraging large-scale training corpora.Increasing the scale of these models enhances performance significantly,introducing abilities like context learning that smaller models lack.The advancement in Large Language Models,exemplified by the development of ChatGPT,has made significant impacts both academically and industrially,capturing widespread societal interest.This survey provides an overview of the development and prospects from Large Language Models(LLM)to Large Multimodal Models(LMM).It first discusses the contributions and technological advancements of LLMs in the field of natural language processing,especially in text generation and language understanding.Then,it turns to the discussion of LMMs,which integrates various data modalities such as text,images,and sound,demonstrating advanced capabilities in understanding and generating cross-modal content,paving new pathways for the adaptability and flexibility of AI systems.Finally,the survey highlights the prospects of LMMs in terms of technological development and application potential,while also pointing out challenges in data integration,cross-modal understanding accuracy,providing a comprehensive perspective on the latest developments in this field.

Discrimination and stratification tests of cardiovascular disease risk assessment models against ultrasound detection of carotid plaques in type 2 diabetics

Atherosclerosis is the early stage of arterial disease, and underlies development of cardiovascular disease (CVD) and stroke. Although sophisticated models for assessing CVD and stroke risk have been derived based on large-scale prospective studies, their abilities in detecting the presence or absence of atherosclerotic plaque have not been investigated. This study aimed to evaluate and compare discriminatory and risk stratifying abilities of 13 CVD risk assessment models against the ultrasound detection of carotid plaques in type 2 diabetes mellitus (T2DM) patients. Forty-nine T2DM subjects were recruited with informed consent, and major anthropomorphic and biomarker data for these models were collected. The model risk scores were evaluated against the carotid plaques detected by Doppler ultrasound. Only the FHS-Lpts-CHD-10Y model, which is a variant of the Framingham model, revealed an area under the receiver operating curve (AUROC) that was significantly different from a random scoring approach (AUROC: 0.681, p was able to stratify the risk levels of carotid plaque presence (Chi-Square statistic: 5.99,

The Importance of Setting Treatment Goals for Cardiovascular Diseases

Background: Guidelines are issued by most major organizations that focus on a specific disease entity. Guidelines should be a significant help to the practicing physician who may not be up-to-date with the recent medical literature. Unfortunately, when conflicting guidelines for a specific disease are published, confusion results. Purpose: This article provides a suggested guideline outcome measure that would benefit the physician and patient. Methods: A review of 19 different guidelines for cardiovascular disease treatment is one example of the lack of specific outcomes that currently exist. The basic problem with most guidelines is that they do not state the expected end result (i.e., the benefit to the patient) if that guideline is followed. When guidelines use cardiovascular disease risk factors to dictate therapy, the end benefit is never stated so that the patient can make an appropriate choice of which (if any) guideline to follow. Results: A good example is guidelines published by the American Heart Association for reducing cardiovascular disease. These guidelines are risk factor based and only indicate that cardiovascular disease would be reduced if followed. No specific percentage in the reduction of the incidence of disease is given. In contrast, when elimination of the disease is the stated goal of the guideline, the end result is clear. To date, this goal has been stated by only one organization devoted to eliminating cardiovascular disease. Conclusion: Guidelines need to be written to provide the physician and the patient with a specific end point that is expected when the guideline is followed. Patient acceptance and compliance will be much improved if the patient knows the risk/benefit of following the guideline’s recommendations.

The relationship between compartment models and their stochastic counterparts:A comparative study with examples of the COVID-19 epidemic modeling

Deterministic compartment models(CMs)and stochastic models,including stochastic CMs and agent-based models,are widely utilized in epidemic modeling.However,the relationship between CMs and their corresponding stochastic models is not well understood.The present study aimed to address this gap by conducting a comparative study using the susceptible,exposed,infectious,and recovered(SEIR)model and its extended CMs from the coronavirus disease 2019 modeling literature.We demonstrated the equivalence of the numerical solution of CMs using the Euler scheme and their stochastic counterparts through theoretical analysis and simulations.Based on this equivalence,we proposed an efficient model calibration method that could replicate the exact solution of CMs in the corresponding stochastic models through parameter adjustment.The advancement in calibration techniques enhanced the accuracy of stochastic modeling in capturing the dynamics of epidemics.However,it should be noted that discrete-time stochastic models cannot perfectly reproduce the exact solution of continuous-time CMs.Additionally,we proposed a new stochastic compartment and agent mixed model as an alternative to agent-based models for large-scale population simulations with a limited number of agents.This model offered a balance between computational efficiency and accuracy.The results of this research contributed to the comparison and unification of deterministic CMs and stochastic models in epidemic modeling.Furthermore,the results had implications for the development of hybrid models that integrated the strengths of both frameworks.Overall,the present study has provided valuable epidemic modeling techniques and their practical applications for understanding and controlling the spread of infectious diseases.

Sex and racial disparities in non-alcoholic fatty liver disease-related cardiovascular events: National inpatient sample analysis (2019)

BACKGROUND Non-alcoholic fatty liver disease(NAFLD)increases cardiovascular disease(CVD)risk irrespective of other risk factors.However,large-scale cardiovascular sex and race differences are poorly understood.AIM To investigate the relationship between NAFLD and major cardiovascular and cerebrovascular events(MACCE)in subgroups using a nationally representative United States inpatient sample.METHODS We examined National Inpatient Sample(2019)to identify adult hospitalizations with NAFLD by age,sex,and race using ICD-10-CM codes.Clinical and demographic characteristics,comorbidities,and MACCE-related mortality,acute myocardial infarction(AMI),cardiac arrest,and stroke were compared in NAFLD cohorts by sex and race.Multivariable regression analyses were adjusted for sociodemographic characteristics,hospitalization features,and comorbidities.RESULTS We examined 409130 hospitalizations[median 55(IQR 43-66)years]with NFALD.NAFLD was more common in females(1.2%),Hispanics(2%),and Native Americans(1.9%)than whites.Females often reported non-elective admissions,Medicare enrolment,the median age of 55(IQR 42-67),and poor income.Females had higher obesity and uncomplicated diabetes but lower hypertension,hyperlipidemia,and complicated diabetes than males.Hispanics had a median age of 48(IQR 37-60),were Medicaid enrollees,and had non-elective admissions.Hispanics had greater diabetes and obesity rates than whites but lower hypertension and hyperlipidemia.MACCE,all-cause mortality,AMI,cardiac arrest,and stroke were all greater in elderly individuals(P<0.001).MACCE,AMI,and cardiac arrest were more common in men(P<0.001).Native Americans(aOR 1.64)and Asian Pacific Islanders(aOR 1.18)had higher all-cause death risks than whites.CONCLUSION Increasing age and male sex link NAFLD with adverse MACCE outcomes;Native Americans and Asian Pacific Islanders face higher mortality,highlighting a need for tailored interventions and care.

Excess cardiovascular mortality in men with non-alcoholic fatty liver disease:A cause for concern!

Non-alcoholic fatty liver disease(NAFLD)has emerged as the commonest cause of chronic liver disease worldwide in recent years.With time,our understanding of NAFLD has evolved from an isolated liver condition to a systemic disease with significant manifestations beyond the liver.Amongst them,cardiovascular diseases(CVDs)are the most important and clinically relevant.Recent research supports a strong independent link between NALFD and CVD beyond the shared risk factors and pathophysiology.Female sex hormones are well known to not only protect against CVD in pre-menopausal females,but also contribute to improved adipose tissue function and preventing its systemic deposition.Recent research highlights the increased risk of major adverse cardiovascular-cerebral events(MACCE)amongst male with NAFLD compared to females.Further,racial variation was observed in MACCE outcomes in NAFLD,with excess mortality in the Native Americans and Asian Pacific Islanders compared to the other races.

Prevalence of Cardiovascular Risk Factors and Heart Diseases within the Urban and Rural Communities of the Town of Bougouni and Its Surroundings (Southern Mali): A Comparative Study

In Mali, few studies have been conducted on the prevalence of cardiovascular risk factors and diseases according to place of residence. The aim of this study was to assess the prevalence of risk factors and cardiovascular diseases according to residents in town of Bougouni and its rural area (southern Mali). Methods: This was a retrospective descriptive study from February 2019 to March 2024. All patients who visited the “CENTRE MEDICAL DE BOUGOUNI” clinic with known or suspected heart disease during the study period were included. Data were collected from medical records. Incomplete or unusable records were excluded. Data were processed using SPS version 22 software. Results: we included 452 patients with an average age of 50 ± 19 years. High blood pression has been found in 42.70% of cases, with higher prevalence in urban areas (47.01%) than in rural areas (41.50%). Diabetes and smoking were found respectively 5.31% and 8.19% in our population. The prevalence of diabetes was higher in urban areas (5.97%) than rural area (5.35%). smoking prevalence was higher in rural areas (8.49%) than urban areas (6.72%). Alcoholism was found in 2.21% of cases with a little difference between rural area (2.24%) and urban area (2.20%). 31.63% of our patients had no cardiovascular factor. Dyspnea was the reason of consultation in 5.75% of cases and atypical precordialgia in 13.72%. Headaches and dizziness in 8.63% of cases and 21.90% of patients presented other non-specific symptoms. Diagnosis of idiopathic dilated cardiomyopathy was found in 23.45% of cases with higher prevalence in rural areas (28.30%) than urban areas (13.43%). Ischaemic heart disease accounted for 9.29% of cases with a higher prevalence in rural areas (10.38%) than in urban areas (6.71%). PPCMs accounted for 5.98% of cases, with a slight increase in urban areas (6.66%) compared with rural areas (5.68%). Rheumatic valvulopathy accounted for 2.21% of cases;2.84% in rural areas and 0.74% in urban areas. Other valvular diseases accounted for 3.76% of cases;4.73% in rural areas and 1.48% in urban areas. Right heart diseases accounted for 3.98% of cases and stroke for 1.77%. Conclusion: The prevalence of cardiovascular risk factors and heart diseases is high in the rural and urban population of the town of Bougouni and its surroundings (Mali). Excepted smoking, the prevalence of other CV risk factors is higher in urban areas, whereas the prevalence of idiopathic dilated cardiomyopathy and ischemic heart disease is higher in rural areas. These data could serve as a basis for developing tailored preventive strategies, depending on the place of residence.

Cardiovascular diseases in European ethnic minorities: Beyond the traditional cardiovascular risk factors

This editorial is intended to be a reflection on cardiovascular disease(CVD)burden in European ethnic minorities.In some European countries,ethnic minority realities,due to their recent appearance,are still to be studied in depth.The experience of several European countries,where the migration processes started earlier,even more than a century ago,can help by being an example.Many studies have shown that major differences in CVD burden exist not only between countries,but also within the same country when considering different social strata and ethnic groups.The CV risk factors underlying heart disease have been well established.Important epidemiological studies have helped us understand that the underlying causes of heart disease as well as the behaviors that can help prevent them are the same.We are now well aware that CVD should be treated by considering a holistic approach.This is why the social determinants(SDs)of health that may worsen the disease burden or that,vice versa,may improve the treatment,and even more significantly,the prognosis of a patient’s illness should be taken into consideration.For ethnic minority patients,this holistic,hermeneutic approach is of importance.Several SDs of health that influence CVDs have been identified but their relevance for the health of ethnic minorities has not yet been clearly defined.In some European countries,most ethnic minorities are largely also religious minorities.Only a few studies have evaluated the role of religion,which is an important SD that affects the probability of having CV risk factors and diseases.Adolescents,particularly those belonging to the second generation,seem to be the weak link.If we believe that these young people are really citizens of their country of birth,then a way of recognizing their belonging to the community starts from a will to better understand their condition,in order to assist them while they grow physically and mentally.Thinking about safeguarding the health of this population should be more than a health task,rather a goal of social justice.

Elevated cardiovascular risk and acute events in hospitalized colon cancer survivors:A decade-apart study of two nationwide cohorts

BACKGROUND Over the years,strides in colon cancer detection and treatment have boosted survival rates;yet,post-colon cancer survival entails cardiovascular disease(CVD)risks.Research on CVD risks and acute cardiovascular events in colorectal cancer survivors has been limited.AIM To compare the CVD risk and adverse cardiovascular outcomes in current colon cancer survivors compared to a decade ago.METHODS We analyzed 2007 and 2017 hospitalization data from the National Inpatient Sample,studying two colon cancer survivor groups for CVD risk factors,mortality rates,and major adverse events like pulmonary embolism,arrhythmia,cardiac arrest,and stroke,adjusting for confounders via multivariable regression analysis.RESULTS Of total colon cancer survivors hospitalized in 2007(n=177542)and 2017(n=178325),the 2017 cohort often consisted of younger(76 vs 77 years),male,African-American,and Hispanic patients admitted non-electively vs the 2007 cohort.Furthermore,the 2017 cohort had higher rates of smoking,alcohol abuse,drug abuse,coagulopathy,liver disease,weight loss,and renal failure.Patients in the 2017 cohort also had higher rates of cardiovascular comorbidities,including hypertension,hyperlipidemia,diabetes,obesity,peripheral vascular disease,congestive heart failure,and at least one traditional CVD(P<0.001)vs the 2007 cohort.On adjusted multivariable analysis,the 2017 cohort had a significantly higher risk of pulmonary embolism(PE)(OR:1.47,95%CI:1.37-1.48),arrhythmia(OR:1.41,95%CI:1.38-1.43),atrial fibrillation/flutter(OR:1.61,95%CI:1.58-1.64),cardiac arrest including ventricular tachyarrhythmia(OR:1.63,95%CI:1.46-1.82),and stroke(OR:1.28,95%CI:1.22-1.34)with comparable all-cause mortality and fewer routine discharges(48.4%vs 55.0%)(P<0.001)vs the 2007 cohort.CONCLUSION Colon cancer survivors hospitalized 10 years apart in the United States showed an increased CVD risk with an increased risk of acute cardiovascular events(stroke 28%,PE 47%,arrhythmia 41%,and cardiac arrest 63%).It is vital to regularly screen colon cancer survivors with concomitant CVD risk factors to curtail long-term cardiovascular complications.

Analysis of the inflection points of height-diameter models

The inflection point is an important feature of sigmoidal height-diameter(H-D)models.It is often cited as one of the properties favoring sigmoidal model forms.However,there are very few studies analyzing the inflection points of H-D models.The goals of this study were to theoretically and empirically examine the behaviors of inflection points of six common H-D models with a regional dataset.The six models were the Wykoff(WYK),Schumacher(SCH),Curtis(CUR),HossfeldⅣ(HOS),von Bertalanffy-Richards(VBR),and Gompertz(GPZ)models.The models were first fitted in their base forms with tree species as random effects and were then expanded to include functional traits and spatial distribution.The distributions of the estimated inflection points were similar between the two-parameter models WYK,SCH,and CUR,but were different between the threeparameter models HOS,VBR,and GPZ.GPZ produced some of the largest inflection points.HOS and VBR produced concave H-D curves without inflection points for 12.7%and 39.7%of the tree species.Evergreen species or decreasing shade tolerance resulted in larger inflection points.The trends in the estimated inflection points of HOS and VBR were entirely opposite across the landscape.Furthermore,HOS could produce concave H-D curves for portions of the landscape.Based on the studied behaviors,the choice between two-parameter models may not matter.We recommend comparing seve ral three-parameter model forms for consistency in estimated inflection points before deciding on one.Believing sigmoidal models to have inflection points does not necessarily mean that they will produce fitted curves with one.Our study highlights the need to integrate analysis of inflection points into modeling H-D relationships.

Progress in experimental models to investigate the in vivo and in vitro antidiabetic activity of drugs

Diabetes mellitus is one of the world's most prevalent and complex metabolic disorders,and it is a rapidly growing global public health issue.It is characterized by hyperglycemia,a condition involving a high blood glucose level brought on by deficiencies in insulin secretion,decreased activity of insulin,or both.Prolonged effects of diabetes include cardiovascular problems,retinopathy,neuropathy,nephropathy,and vascular alterations in both macro-and micro-blood vessels.In vivo and in vitro models have always been important for investigating and characterizing disease pathogenesis,identifying targets,and reviewing novel treatment options and medications.Fully understanding these models is crucial for the researchers so this review summarizes the different experimental in vivo and in vitro model options used to study diabetes and its consequences.The most popular in vivo studies involves the small animal models,such as rodent models,chemically induced diabetogens like streptozotocin and alloxan,and the possibility of deleting or overexpressing a specific gene by knockout and transgenic technologies on these animals.Other models include virally induced models,diet/nutrition induced diabetic animals,surgically induced models or pancreatectomy models,and non-obese models.Large animals or non-rodent models like porcine(pig),canine(dog),nonhuman primate,and Zebrafish models are also outlined.The in vitro models discussed are murine and human beta-cell lines and pancreatic islets,human stem cells,and organoid cultures.The other enzymatic in vitro tests to assess diabetes include assay of amylase inhibition and inhibition ofα-glucosidase activity.

Smaller & Smarter: Score-Driven Network Chaining of Smaller Language Models

With the continuous evolution and expanding applications of Large Language Models (LLMs), there has been a noticeable surge in the size of the emerging models. It is not solely the growth in model size, primarily measured by the number of parameters, but also the subsequent escalation in computational demands, hardware and software prerequisites for training, all culminating in a substantial financial investment as well. In this paper, we present novel techniques like supervision, parallelization, and scoring functions to get better results out of chains of smaller language models, rather than relying solely on scaling up model size. Firstly, we propose an approach to quantify the performance of a Smaller Language Models (SLM) by introducing a corresponding supervisor model that incrementally corrects the encountered errors. Secondly, we propose an approach to utilize two smaller language models (in a network) performing the same task and retrieving the best relevant output from the two, ensuring peak performance for a specific task. Experimental evaluations establish the quantitative accuracy improvements on financial reasoning and arithmetic calculation tasks from utilizing techniques like supervisor models (in a network of model scenario), threshold scoring and parallel processing over a baseline study.

The association of diet quality and physical activity with cardiovascular disease and mortality in 85,545 older Australians:A longitudinal study

Background:A quality diet and an active lifestyle are both important cornerstones of cardiovascular disease(CVD)prevention.However,despite their interlinked effects on metabolic health,the 2 behaviors are rarely considered jointly,particularly within the context of CVD prevention.We examined the independent,interactive,and joint associations of diet and physical activity with CVD hospitalization,CVD mortality,and all-cause mortality.Methods:CVD-free Australian participants aged 4574 years(n=85,545)reported physical activity,diet,sociodemographic,and lifestyle characteristics at baseline(20062009)and follow-up(20122015),and data were linked to hospitalization and death registries(03/31/2019 for CVD hospitalization and all-cause mortality and 12/08/2017 for CVD mortality).Diet quality was categorized as low,medium,and high based on meeting dietary recommendations.Physical activity was operationalized as(a)total moderate-to-vigorous physical activity(MVPA)as per guidelines,and(b)the composition of MVPA as the ratio of vigorous-intensity physical activity(VPA)to total MVPA.We used a left-truncated cause-specific Cox proportional hazards model using time-varying covariates.Results:During a median of 10.7 years of follow-up,6576 participants were admitted to the hospital for CVD and 6581 died from all causes(876 from CVD during 9.3 years).A high-quality diet was associated with a 17%lower risk of all-cause mortality than a low-quality diet,and the highest MVPA category(compared with the lowest)was associated with a 44%and 48%lower risk of CVD and all-cause mortality,respectively.Multiplicative interactions between diet and physical activity were non-significant.For all outcomes,the lowest risk combinations involved a high-quality diet and the highest MVPA categories.Accounting for total MVPA,some VPA was associated with further risk reduction of CVD hospitalization and all-cause mortality.Conclusion:For CVD prevention and longevity,one should adhere to both a healthy diet and an active lifestyle and incorporate some VPA when possible.

Age-specific differences in the association between prediabetes and cardiovascular diseases in China:A national cross-sectional study

BACKGROUND Cardiovascular disease(CVD)is a leading cause of morbidity and mortality worldwide,the global burden of which is rising.It is still unclear the extent to which prediabetes contributes to the risk of CVD in various age brackets among adults.To develop a focused screening plan and treatment for Chinese adults with prediabetes,it is crucial to identify variations in the connection between prediabetes and the risk of CVD based on age.AIM To examine the clinical features of prediabetes and identify risk factors for CVD in different age groups in China.METHODS The cross-sectional study involved a total of 46239 participants from June 2007 through May 2008.A thorough evaluation was conducted.Individuals with prediabetes were categorized into two groups based on age.Chinese atherosclerotic CVD risk prediction model was employed to evaluate the risk of developing CVD over 10 years.Random forest was established in both age groups.SHapley Additive exPlanation method prioritized the importance of features from the perspective of assessment contribution.RESULTS In total,6948 people were diagnosed with prediabetes in this study.In prediabetes,prevalences of CVD were 5(0.29%)in the younger group and 148(2.85%)in the older group.Overall,11.11%of the younger group and 29.59% of the older group were intermediate/high-risk of CVD for prediabetes without CVD based on the Prediction for ASCVD Risk in China equation in ten years.In the younger age group,the 10-year risk of CVD was found to be more closely linked to family history of CVD rather than lifestyle,whereas in the older age group,resident status was more closely linked.CONCLUSION The susceptibility to CVD is age-specific in newly diagnosed prediabetes.It is necessary to develop targeted approaches for the prevention and management of CVD in adults across various age brackets.

Report on Cardiovascular Health and Diseases in China 2023:An Updated Summary

Since 1990,China has made considerable progress in resolving the problem of“treatment difficulty”of cardiovascular diseases(CVD).The prevalent unhealthy lifestyle among Chinese residents has exposed a massive proportion of the population to CVD risk factors,and this situation is further worsened due to the accelerated aging population in China.CVD remains one of the greatest threats to the health of Chinese residents.In terms of the proportions of disease mortality among urban and rural residents in China,CVD has persistently ranked first.In 2021,CVD accounted for 48.98%and 47.35%of deaths in rural and urban areas,respectively.Two out of every five deaths can be attributed to CVD.To implement a national policy“focusing on the primary health institute and emphasizing prevention”and truly achieve a shift of CVD prevention and treatment from hospitals to communities,the National Center for Cardiovascular Diseases has organized experts from relevant fields across China to compile the“Report on Cardiovascular Health and Diseases in China”annually since 2005.The 2024 report is established based on representative,published,and high-quality big-data research results from cross-sectional and cohort population epidemiological surveys,randomized controlled clinical trials,large sample registry studies,and typical community prevention and treatment cases,along with data from some projects undertaken by the National Center for Cardiovascular Diseases.These firsthand data not only enrich the content of the current report but also provide a more timely and comprehensive reflection of the status of CVD prevention and treatment in China.