Hasil untuk "Diseases of the circulatory (Cardiovascular) system"

L. Liberale, Simon Tual-Chalot, S. Sedej et al.

Saiqing Chen, Chunxia Zhang, Yueting Yu

BackgroundHeart failure (HF) represents the terminal phase of multiple cardiovascular conditions and is associated with significant morbidity and mortality rates. Arachidonic acid (AA), an essential fatty acid, plays a crucial role in modulating cardiovascular function under both normal and disease states. The purpose of this research was to examine how AA is related to HF, providing new perspective for individualized treatment.MethodsTranscriptomic datasets were retrieved from the Gene Expression Omnibus (GEO) database. The raw data were consolidated to identify differentially expressed genes (DEGs) and subsequently subjected to bioinformatics analysis. Gene ontology (GO) annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed. Signature genes were identified through Least Absolute Shrinkage and Selection Operator (LASSO) regression, Support Vector Machine-Recursive Feature Elimination (SVM-RFE), and Random Forest (RF) algorithms. Receiver Operating Characteristic (ROC) curves were generated for gene evaluation, and a nomogram was developed. An analysis of immune cell infiltration was conducted using Single Sample Gene Set Enrichment Analysis (ssGSEA), and Gene Set Enrichment Analysis (GSEA) was conducted to determine important pathways. Subsequently, we also performed drug sensitivity evaluation. Finally, the expression levels of the identified signature genes in HF samples were confirmed using qRT-PCR analysis.ResultsFour characteristic genes demonstrating favorable performance in the ROC analysis. The comprehensive nomogram developed in this study exhibited enhanced clinical utility. In addition, notable variations in immune cell infiltration levels were detected, and GSEA highlighted key biological pathways.ConclusionThis investigation demonstrated a strong association between arachidonic acid-associated gene expression and heightened risk of HF, offering novel perspectives on the disease's underlying pathological processes and providing potential insights for personalized management of HF.

Linlin Wang, Shuang Xie, Aoxue Mei et al.

Abstract Purpose Acute coronary syndromes (ACS) is a leading cause of death worldwide. Albumin and globulin are the main components of serum proteins. The albumin-to-globulin ratio (AGR) is often used to assess nutritional status. However, the clinical significance of the AGR in predicting the prognosis of patients with ACS remains unclear. Patients and methods A total of 1408 patients with ACS who underwent percutaneous coronary intervention (PCI) were consecutively enrolled between January 2016 and December 2018 at The Affiliated Hospital of Chengde Medical University. The follow-up endpoints were defined as cardiac death or recurrent acute myocardial infarction. Results A total of 1363 patients responded in the follow-up period, of whom 49 had MACEs. AGR was significantly different between the MACEs and non-MACE groups. The area under the curve for the AGR was 0.619 (P = 0.004, 95% confidence interval [CI]: 0.542–0.697). The optimal cut-off value for the AGR was determined to be 1.350 using Youden’s index. The cumulative survival rate of the low AGR group was significantly lower than that of the high AGR group, according to the Kaplan–Meier curve (log-rank P = 0.008). Multivariate Cox proportional hazards model showed age ≥ 60 years, HR:2.689 (95%CI:1.288–5.615, P = 0.008), left ventricular ejection fraction (LVEF) < 40%, HR: 3.527, (95%CI: 1.357–9.164, P = 0.010), and AGR < 1.350, HR: 2.180, (95%CI: 1.078–4.407, P = 0.030) were all independent risk factors. A restricted cubic spline showed that a decreasing AGR was correlated with increasing risk of MACEs. Conclusion AGR < 1.350 is an independent prognostic risk factor for patients with ACS undergoing PCI and may be a valuable clinical marker for identifying high-risk patients.

Pranav Kumar Sasikumar

Zero-dimensional cardiovascular models provide a computationally efficient framework for studying global hemodynamic behavior, yet the influence of model complexity on parameter sensitivity remains insufficiently understood. This work investigates two lumped-parameter cardiovascular models, a simplified single-ventricle configuration and a detailed four-chamber representation, to examine how physiological parameter sensitivities vary with model structure. Time-varying elastance functions are used to represent cardiac dynamics, and global sensitivity analysis is performed using Sobol and Morris methods to quantify the impact of key physiological parameters, including venous return, myocardial contractility, total peripheral resistance, and arterial compliance. The results demonstrate that sensitivity rankings differ substantially between the two models, highlighting the role of model granularity and parameter interactions in shaping cardiovascular responses. These findings support sensitivity-driven model reduction and provide a foundation for scalable, non-invasive cardiovascular simulation frameworks.

K. A. Muthukumar, Dhruva Nandi, Priya Ranjan et al.

Cardiovascular diseases (CVD) are a predominant health concern globally, emphasizing the need for advanced diagnostic techniques. In our research, we present an avant-garde methodology that synergistically integrates ECG readings and retinal fundus images to facilitate the early disease tagging as well as triaging of the CVDs in the order of disease priority. Recognizing the intricate vascular network of the retina as a reflection of the cardiovascular system, alongwith the dynamic cardiac insights from ECG, we sought to provide a holistic diagnostic perspective. Initially, a Fast Fourier Transform (FFT) was applied to both the ECG and fundus images, transforming the data into the frequency domain. Subsequently, the Earth Mover's Distance (EMD) was computed for the frequency-domain features of both modalities. These EMD values were then concatenated, forming a comprehensive feature set that was fed into a Neural Network classifier. This approach, leveraging the FFT's spectral insights and EMD's capability to capture nuanced data differences, offers a robust representation for CVD classification. Preliminary tests yielded a commendable accuracy of 84 percent, underscoring the potential of this combined diagnostic strategy. As we continue our research, we anticipate refining and validating the model further to enhance its clinical applicability in resource limited healthcare ecosystems prevalent across the Indian sub-continent and also the world at large.

Yuri G. Vykhovanets, S. M. Tetyura, Tatiana A. Vykhovanets et al.

Introduction. In the context of global climate changes occurring on the planet, an important task is to develop modern methods for modelling and forecasting the complex influence of meteorological and environmental components of the environment on physical health, for the rapid development of measures to prevent diseases of the cardiovascular system in human. The purpose. Development of an effective method for hygienic assessment of the risk of cardiovascular pathology, which is formed under the influence of the complex effects of meteorological and chemical environmental factors. Materials and methods. The average annual and seasonal fluctuations of meteorological factors were studied. Bioclimatic indices, the index of pathogenicity of the meteorological situation, and severity of the weather were calculated. Concentrations of chemicals in atmospheric air were assessed, and the influence of meteorological environmental factors on the incidence of cardiovascular pathology in the population living in an industrial region was analyzed. Results. Based on the conducted studies, an unfavourable combined effect of meteorological components of the environment on thermoregulation processes in residents of an industrial region has been established. The relationship between the average daily wind speed and the seasonal excess of the maximum permissible concentrations of certain substances in the atmospheric air over a number of years has been revealed. The combination of seasonal fluctuations in meteorological factors with increased levels of pollution of the city’s atmospheric air with heavy metals are factors that increase the incidence of cardiovascular pathology in the population. Research limitations. The studies had no methodological or administrative restrictions. Conclusions: There has been developed the method for calculating and assessing the risk of cardiovascular pathology, formed under the influence of the complex effects of meteorological and chemical environmental factors.

S. A. Bogachevskaya, S. Kiselev, V. Stupak

The objective of this study was to examine interregional medical and organizational problems of providing specialized medical care to patients with circulatory system diseases living in the Far East, using the example of the diagnostic service of the subjects of the Far Eastern Federal District. Material and methods. The analysis of the availability of ultrasound and functional diagnostic methods for patients with circulatory system diseases in the constituent entities of the Far Eastern Federal District was carried out in accordance with the procedures for providing medical care and clinical protocols in the profiles of "cardiovascular surgery" and "cardiology", the dynamics of their growth and decline were studied for 37 232 cases of referrals for planned hospitalization for the periods of 2012–2014, as well as 2021–2023, based on the developed expert assessment map. Economic losses from duplicating patient studies at different levels of medical care for diseases of the circulatory system were calculated. Results. The defects in the diagnostic examination of patients by medical organizations of the region's constituent entities when referring them for planned surgical treatment to the Federal Center for Cardiovascular Surgery in Khabarovsk were identified, as well as significant heterogeneity in the capabilities of diagnostic services in medical organizations of the Far East, a high need for an expert assessment of the condition of patients with circulatory system diseases before surgical interventions. The estimated economic damage from repeated examination of patients admitted to the Federal Center for Cardiovascular Surgery amounted to 56 million 242 thousand rubles per year, taking into account the turnover of an average of 8,450 patients per year. Conclusion. The results of the study indicate the need to take additional medical and organizational measures to eliminate duplication of functional and ultrasound studies.

G. Artamonova, E. Bazdyrev, S. Makarov

HighlightsWe have identified regional peculiarities of traditional and non-traditional cardiovascular risk factors.We have defined and characterized clinical and organizational characteristics of the specialized care, prevention, and treatment of diseases of the circulatory system in the Kemerovo region - Kuzbass.Moreover, we have described the principles of innovative organizational models for improving care for patients with diseases of the circulatory system, focused on the needs of outpatient organizations. AbstractThe review presents the main research findings obtained at the Department of Optimization of Medical Care for Cardiovascular Diseases of the Research Institute for Complex Issues of Cardiovascular Diseases over the past 13 years of work. The uniqueness of the obtained data lies in the fact that we have identified regional peculiarities of cardiovascular risk factors in residents of an industrial region (using the Kemerovo region data). Data on monitoring of health and risk factors served as the basis for the development of innovative organizational models for improving care for patients with diseases of the circulatory system from the stage of primary care to tertiary care using a systematic and integrated approach, and situational analysis. Management decisions within models are based on international quality standards that reaffirm that risk-based management, the role of personnel and the work environment are the integral to the improvement of performance and the achievement of the main goals of medical organization. Using the project approach, we have implemented management tools for internal quality control and safety of patients and personnel.

E. Enina, D. Vaisman, T. Bogdanova

Significance. Diseases of the circulatory system are among the leading ones in the structure of morbidity and top the structure of adult mortality in Russia. Analyzing dynamics in morbidity and coverage with regular health examination is necessary to develop comprehensive programs to control cardiovascular diseases. In order to preserve and prolong the life of the patients suffering from diseases of the circulatory system, the federal project “Fighting Cardiovascular Diseases” has been implemented in the Russian Federation since 2019. Due to high significance of diseases of the circulatory system in the structure of morbidity and mortality, it is of great scientific and practical interest to study trends in incidence and prevalence, as well as coverage with regular health examination of the Russian adult population. The purpose of the study is to analyze dynamics in incidence and prevalence of diseases of the circulatory system as well as coverage with regular health examination of the adult population of the Russian Federation in 2019-2023. Material and methods. The study used statistical reference books of the Ministry of Health of the Russian Federation “Disease prevalence among the Russian adult population” for 2019-2023. The following methods were used: statistical, analytical, and descriptive statistics. The coverage of patients with diseases of the circulatory system with regular health examination was calculated as a share of those taken under regular examination out of the total number of the registered patients with diseases of the circulatory system diseases, expressed in percent. Results. The prevalence of diseases of the circulatory system among the Russian adult population increased from 31975.4 in 2019 to 34757.5 in 2023 per 100000 adult population, with the growth rate adding up to 8.7%. In the period from 2019 to 2023, there was an increase in prevalence of diseases of the circulatory system across all federal districts, with the growth rate ranging from 2.8 to 20.0%, with an average of 9.8%. The highest growth rate was registered in the North Caucasian Federal District (20.0%), the lowest one- in the Southern Federal District (2.8%). There were registered both growth and fall in prevalence of diseases of the circulatory system among adults in the constituent entities of all federal districts of the Russian Federation. Incidence of diseases of the circulatory system in the Russian adult population increased from 4208.5 in 2019 to 4296.7 in 2023 per 100000 adult population, with the growth rate adding up to 2.1%. In the period from 2019 to 2023, there was an increase in incidence in four federal districts (Central, North Caucasian, Ural and Siberian Federal Districts), with the growth ranging from 1.9% to 19.5%, with an average of 9.95%. In other federal districts (Northwestern, Southern, Volga and Far Eastern Federal Districts) there was a decrease in incidence of diseases of the circulatory system by 0.7-7.4%, 3.7% on average. In the constituent entities of all federal districts of the Russian Federation there were registered both growth and fall in incidence of diseases of the circulatory system among adult population. The coverage of adult patients suffering from cardiovascular diseases with regular medical examination in the Russian Federation increased from 67.1% in 2019 to 79.6% in 2023 (by 12.5%). In all federal districts, the coverage differed and averaged to 67.6% in 2019 and 79.6% in 2023. Conclusion. In 2020, in the first year of the COVID-19 pandemic, there was a decrease in both incidence and prevalence of diseases of the circulatory system among the Russian adults. In 2021, there was an increase in both incidence and prevalence. In 2023, compared to 2022, the growth rate of incidence and prevalence of diseases of the circulatory system amounted to 7.6% and 5.7%, respectively. The overall growth rate in 2019-2023 added up to 8.7% for prevalence and 2.1% for incidence. In the regions of the Russian Federation, there were registered both growth and fall in prevalence and incidence. When comparing prevalence of diseases of the circulatory system and coverage with regular health examination with all registered cases of diseases of the circulatory system among adult population, no correlation has been identified. Scope of application. The study results can be used to develop activities of preventive programs. Keywords: prevalence; incidence; dynamics in morbidity indicators; adult population; regular health examination; diseases of the circulatory system; COVID-19

Rasit Dinc, Evren Ekingen

Arterial aneurysms remain a significant public health problem because they often result in death when ruptured; therefore, they require immediate medical treatment. Endovascular aneurysm repair (EVAR) has recently become the primary treatment option, owing to the fewer side effects compared to those with open surgery. However, stents used for conventional EVAR often cause side-branch occlusion, which alters the perfusion of vital organs. Recently, multilayer flow modulator (MFM) stents have been used as a new treatment for arterial aneurysms. These stents appear to be feasible owing to their unique design consisting of an uncoated three-dimensionally braided multilayered structure. MFM stents generally remodulate laminar flow and reduce the flow velocity in the aneurysmal sac, leading to thrombosis, which causes the aneurysm to shrink over time. Thus, they reduce the risk of mortality. Moreover, they reduce morbidity by preserving the side-branch blood flow. They can be easily applied to complex aneurysms and are ready to use without customization, which shortens the waiting time for interventions. This study aimed to evaluate the role of MFM stents in the treatment of arterial aneurysms based on available data.

Gabriella Iannuzzo, Geetank Kamboj, Parinita Barman et al.

Background and aims: Cardiovascular diseases (CVD) pose a significant global health burden. Lowering low-density lipoprotein-cholesterol is the primary therapeutic aim for preventing primary and secondary CVD events. While statins are the standard treatments, their limitations, such as side effects and intolerance in certain patient groups, necessitate exploration of alternative lipid-lowering therapies (LLTs). We systematically reviewed randomised controlled trials (RCTs) evaluating cardiovascular outcomes associated with non-statin LLTs (bempedoic acid, alirocumab, evolocumab, ezetimibe, and inclisiran) in adults with CVD or high cardiovascular risk. Methods: EMBASE, Medline, Cochrane Library, and clinical trial registries were systematically searched for eligible studies, from inception until February 08, 2023. Two reviewers independently screened the studies, with discrepancies resolved by a third reviewer. Data extraction and validation were conducted, and the risk of bias was assessed using the Cochrane Risk-of-Bias tool-2 for RCTs. Results: The search strategy yielded 2104 citations. Post screening for eligibility, nine unique trials/studies (84 publications) were identified. Among these, one trial each was identified for bempedoic acid and alirocumab, three for evolocumab, and four for ezetimibe. No published literature documenting the cardiovascular outcomes of inclisiran was identified. Only one trial (CLEAR Outcomes) included statin-intolerant patients at baseline. Most studies evaluated a 3-component, 4-component, or 5-component major adverse cardiovascular events composite as an outcome along with individual components. The quality of the included trials was found to be fair-to-good. Conclusions: The systematic review findings emphasise the significance of considering non-statin LLTs as viable treatment options for individuals with CVD or high cardiovascular risk who cannot tolerate or achieve optimal lipid control with statin therapy alone.

Moez Dawood, Ben Heavner, Marsha M. Wheeler et al.

Rare diseases are collectively common, affecting approximately one in twenty individuals worldwide. In recent years, rapid progress has been made in rare disease diagnostics due to advances in DNA sequencing, development of new computational and experimental approaches to prioritize genes and genetic variants, and increased global exchange of clinical and genetic data. However, more than half of individuals suspected to have a rare disease lack a genetic diagnosis. The Genomics Research to Elucidate the Genetics of Rare Diseases (GREGoR) Consortium was initiated to study thousands of challenging rare disease cases and families and apply, standardize, and evaluate emerging genomics technologies and analytics to accelerate their adoption in clinical practice. Further, all data generated, currently representing ~7500 individuals from ~3000 families, is rapidly made available to researchers worldwide via the Genomic Data Science Analysis, Visualization, and Informatics Lab-space (AnVIL) to catalyze global efforts to develop approaches for genetic diagnoses in rare diseases (https://gregorconsortium.org/data). The majority of these families have undergone prior clinical genetic testing but remained unsolved, with most being exome-negative. Here, we describe the collaborative research framework, datasets, and discoveries comprising GREGoR that will provide foundational resources and substrates for the future of rare disease genomics.

Morteza Maleki, Foad Haeri

Cardiovascular diseases are the leading cause of mortality globally, necessitating advancements in diagnostic techniques. This study explores the application of wavelet transformation for classifying electrocardiogram (ECG) signals to identify various cardiovascular conditions. Utilizing the MIT-BIH Arrhythmia Database, we employed both continuous and discrete wavelet transforms to decompose ECG signals into frequency sub-bands, from which we extracted eight statistical features per band. These features were then used to train and test various classifiers, including K-Nearest Neighbors and Support Vector Machines, among others. The classifiers demonstrated high efficacy, with some achieving an accuracy of up to 96% on test data, suggesting that wavelet-based feature extraction significantly enhances the prediction of cardiovascular abnormalities in ECG data. The findings advocate for further exploration of wavelet transforms in medical diagnostics to improve automation and accuracy in disease detection. Future work will focus on optimizing feature selection and classifier parameters to refine predictive performance further.

Snehasis Banerjee, Sayan Paul, Ruddradev Roychoudhury et al.

This article presents Teledrive, a telepresence robotic system with embodied AI features that empowers an operator to navigate the telerobot in any unknown remote place with minimal human intervention. We conceive Teledrive in the context of democratizing remote care-giving for elderly citizens as well as for isolated patients, affected by contagious diseases. In particular, this paper focuses on the problem of navigating to a rough target area (like bedroom or kitchen) rather than pre-specified point destinations. This ushers in a unique AreaGoal based navigation feature, which has not been explored in depth in the contemporary solutions. Further, we describe an edge computing-based software system built on a WebRTC-based communication framework to realize the aforementioned scheme through an easy-to-use speech-based human-robot interaction. Moreover, to enhance the ease of operation for the remote caregiver, we incorporate a person following feature, whereby a robot follows a person on the move in its premises as directed by the operator. Moreover, the system presented is loosely coupled with specific robot hardware, unlike the existing solutions. We have evaluated the efficacy of the proposed system through baseline experiments, user study, and real-life deployment.

Hakim El Massari, Noreddine Gherabi, Sajida Mhammedi et al.

Cardiovascular disease is one of the chronic diseases that is on the rise. The complications occur when cardiovascular disease is not discovered early and correctly diagnosed at the right time. Various machine learning approaches, including ontology-based Machine Learning techniques, have lately played an essential role in medical science by building an automated system that can identify heart illness. This paper compares and reviews the most prominent machine learning algorithms, as well as ontology-based Machine Learning classification. Random Forest, Logistic regression, Decision Tree, Naive Bayes, k-Nearest Neighbours, Artificial Neural Network, and Support Vector Machine were among the classification methods explored. The dataset used consists of 70000 instances and can be downloaded from the Kaggle website. The findings are assessed using performance measures generated from the confusion matrix, such as F-Measure, Accuracy, Recall, and Precision. The results showed that the ontology outperformed all the machine learning algorithms.

Jin Hyun Joh, Sun Hyung Joo

Cyanoacrylate glue is a non-thermal, non-tumescent agent used to treat saphenous reflux. It was introduced to overcome heat-related discomfort and complications. Multiple randomized controlled trials using this therapy have demonstrated excellent clinical outcomes at long-term follow-up. However, diffuse injection-site inflammation and systemic urticaria are worrisome complications. In preclinical studies, serial histopathological findings demonstrated acute inflammatory reaction, subacute vasculitis, chronic granulomatous foreign body reaction, fibrotic changes with partial vascular recanalization, and chronic foreign body-type inflammatory response. While the exact nature of this unique complication remains undefined, complex hypersensitivity and irritation reaction phenomena have been suggested based on reported clinical presentations. The incidence of this complication has been reported as ranging from 0.3%-25.4%. Typically, erythematous reactions can occur near treatment sites, with symptoms ranging from mild pruritus and/or erythema that resolves without treatment to recurrent severe inflammation and pruritus requiring nonsteroidal anti-inflammatory drugs, antihistamines, and/or corticosteroids. Surgical excision has been rarely reported in patients with severe intractable inflammation or treatment-site infections. Although several anecdotal studies reported on using antihistaminics or corticosteroids, no effective strategies have been established to prevent this complication.

Alkhateeb A, Mahmoud HEM, AK M et al.

Areej Alkhateeb,1 Hossam Eldin M Mahmoud,1 Mohammed AK,1 Mohammed H Hassan,2 Abdel Rahim Mahmoud Muddathir,3 Ahmed G Bakry1 1Cardiology Division of Internal Medicine Department, South Valley University Hospital, Faculty of Medicine, South Valley University, Qena, 83523, Egypt; 2Department of Medical Biochemistry, Faculty of Medicine, South Valley University, Qena, 83523, Egypt; 3Department of Hematology and Blood Transfusion, Faculty of Medical Laboratory Science, Alzaeim Alazhari University, Khartoum, SudanCorrespondence: Abdel Rahim Mahmoud Muddathir, Department of Hematology and Blood Transfusion, Faculty of Medical Laboratory Science, Alzaeim Alazhari University, Khartoum, Sudan, Email abdelrahimm@gmail.comBackground: The prognostic role of the soluble circulating suppression of tumorigenicity 2 marker (sST2) in different cardiovascular diseases (CVD) is still under investigation. This research aimed to assess the serum levels of sST2 in the blood of individuals with ischemic heart disease and its relation to disease severity, also to examine any changes in sST2 levels following a successful percutaneous coronary intervention (PCI) in those patients.Methods: A total of 33 ischemic patients and 30 non-ischemic controls were included. The plasma level of sST2 was measured using commercially available ELISA assay kit, at baseline and 24– 48 h after the intervention in the ischemic group.Results: On admission, there was a significant difference between the group of acute/chronic coronary syndrome cases and controls regarding the sST2 plasma level (p < 0.001). There was an insignificant difference between the three ischemic subgroups at the baseline sST2 level (p = 0.38). The plasma sST2 level decreased significantly after PCI (from 20.70 ± 1.71 to 16.51 ± 2.43, p = 0.006). There was a modestly just significant positive correlation between the acute change in post-PCI sST2 level and the severity of ischemia as measured by the Modified Gensini Score (MGS) (r = 0.45, p = 0.05). In spite of the highly significant improvement in the coronary TIMI flow of ischemic group after PCI, there was insignificant negative correlation between the post- PCI delta change in the sST2 level and the post-PCI TIMI coronary flow grade.Conclusion: A significantly high plasma level of sST2 in patients with myocardial ischemia and controlled cardiovascular risk factors showed an immediate reduction after successful revascularization. The high baseline level of the sST2 marker and the acute post-PCI reduction was mainly related to the severity of ischemia rather than left ventricular function.Keywords: soluble circulating suppression of tumorigenicity 2 marker, percutaneous coronary intervention, acute/chronic coronary syndrome, severity of ischemia, modified gensini score, revascularization

Eun Kyoung Kim, Hong-Mi Choi, Jong-Hwan Lee et al.

BackgroundDue to increased needs to reduce non-fatal as well as fatal cardiac events, preoperative echocardiography remains part of routine clinical practice in many hospitals. Data on the role of preoperative echocardiography in low-risk non-cardiac surgery (NCS) other than ambulatory surgeries do not exist. We aimed to investigate the role of preoperative echocardiography in predicting postoperative adverse cardiovascular events (CVEs) in asymptomatic patients undergoing low-risk NCS.MethodsThe study population was derived from a retrospective cohort of 1,264 patients who underwent elective low-risk surgery at three tertiary hospitals from June 1, 2021, to June 30, 2021. Breast, distal bone, thyroid, and transurethral surgeries were included. Preoperative examination data including electrocardiography, chest radiography, and echocardiography were collected. The primary outcome was a composite of postoperative adverse CVEs including all-cause death, myocardial infarction, cerebrovascular events, newly diagnosed or acutely decompensated heart failure (HF), lethal arrhythmia such as sustained ventricular tachycardia/fibrillation, and new-onset atrial fibrillation within 30 days after the index surgery.ResultsPreoperative echocardiography was performed in 503 patients (39.8%), most frequently in patients with breast surgery (73.5%), followed by transurethral (37.7%), distal bone (21.6%), and thyroid surgeries (11.9%). Abnormal findings were observed in 5.0% of patients with preoperative echocardiography. Postoperative adverse CVEs occurred in 10 (0.79%) patients. Although a history of previous HF was an independent predictor of postoperative CVE occurrence (adjusted odds ratio, aOR: 17.98; 95% confidence interval, CI: 1.21–266.71, P = 0.036), preoperative echocardiography did not significantly predict CVE in multivariate analysis (P = 0.097). However, in patients who underwent preoperative echocardiography, the presence of abnormal echocardiographic findings was independently associated with development of CVE after NCS (aOR: 23.93; 95% CI: 1.2.28–250.76, P = 0.008). In particular, the presence of wall motion abnormality was a strong predictor of postoperative adverse CVE.ConclusionIn real-world clinical practice, preoperative echocardiography was performed in substantial number of patients with potential cardiac risk even in low-risk NCS, and abnormal findings were independently associated with postoperative CVE. Future studies should identify patients undergoing low-risk NCS for whom preoperative echocardiography would be helpful to predict adverse CVE.

T. V. Afanasieva, A. P. Kuzlyakin, A. V. Komolov

Cardiovascular diseases are widespread among patients with chronic noncommunicable diseases and are one of the leading causes of death, including in the working age. The article presents the relevance of the development and application of patient-oriented systems, in which machine learning (ML) is a promising technology that allows predicting cardiovascular diseases. Automated machine learning (AutoML) makes it possible to simplify and speed up the process of developing AI/ML applications, which is key in the development of patient-oriented systems by application users, in particular medical specialists. The authors propose a framework for the application of automatic machine learning and three scenarios that allowed for data combining five data sets of cardiovascular disease indicators from the UCI Machine Learning Repository to investigate the effectiveness in detecting this class of diseases. The study investigated one AutoML model that used and optimized the hyperparameters of thirteen basic ML models (KNeighborsUnif, KNeighborsDist, LightGBMXT, LightGBM, RandomForestGini, RandomForestEntr, CatBoost, ExtraTreesGini, ExtraTreesEntr, NeuralNetFastA, XGBoost, NeuralNetTorch, LightGBMLarge) and included the most accurate models in the weighted ensemble. The results of the study showed that the structure of the AutoML model for detecting cardiovascular diseases depends not only on the efficiency and accuracy of the basic models used, but also on the scenarios for preprocessing the initial data, in particular, on the technique of data normalization. The comparative analysis showed that the accuracy of the AutoML model in detecting cardiovascular disease varied in the range from 87.41% to 92.3%, and the maximum accuracy was obtained when normalizing the source data into binary values, and the minimum was obtained when using the built-in AutoML technique.

Achyut Tiwari, Aryan Chugh, Aman Sharma

Heart disease is the major cause of non-communicable and silent death worldwide. Heart diseases or cardiovascular diseases are classified into four types: coronary heart disease, heart failure, congenital heart disease, and cardiomyopathy. It is vital to diagnose heart disease early and accurately in order to avoid further injury and save patients' lives. As a result, we need a system that can predict cardiovascular disease before it becomes a critical situation. Machine learning has piqued the interest of researchers in the field of medical sciences. For heart disease prediction, researchers implement a variety of machine learning methods and approaches. In this work, to the best of our knowledge, we have used the dataset from IEEE Data Port which is one of the online available largest datasets for cardiovascular diseases individuals. The dataset isa combination of Hungarian, Cleveland, Long Beach VA, Switzerland & Statlog datasets with important features such as Maximum Heart Rate Achieved, Serum Cholesterol, Chest Pain Type, Fasting blood sugar, and so on. To assess the efficacy and strength of the developed model, several performance measures are used, such as ROC, AUC curve, specificity, F1-score, sensitivity, MCC, and accuracy. In this study, we have proposed a framework with a stacked ensemble classifier using several machine learning algorithms including ExtraTrees Classifier, Random Forest, XGBoost, and so on. Our proposed framework attained an accuracy of 92.34% which is higher than the existing literature.