Diagnosis Of Coronary Heart Disease Research Articles

Segmentation and Automatic Identification of Vasculature in Coronary Angiograms

Coronary angiography is the “gold standard” for the diagnosis of coronary heart disease, of which vessel segmentation and identification technologies are paid much attention to. However, because of the characteristics of coronary angiograms, such as the complex and variable morphology of coronary artery structure and the noise caused by various factors, there are many difficulties in these studies. To conquer these problems, we design a preprocessing scheme including block-matching and 3D filtering, unsharp masking, contrast-limited adaptive histogram equalization, and multiscale image enhancement to improve the quality of the image and enhance the vascular structure. To achieve vessel segmentation, we use the C-V model to extract the vascular contour. Finally, we propose an improved adaptive tracking algorithm to realize automatic identification of the vascular skeleton. According to our experiments, the vascular structures can be successfully highlighted and the background is restrained by the preprocessing scheme, the continuous contour of the vessel is extracted accurately by the C-V model, and it is verified that the proposed tracking method has higher accuracy and stronger robustness compared with the existing adaptive tracking method.

Diagnosis of Arrhythmia for Patients with Occult Coronary Heart Disease Guided by Intracavitary Electrocardiogram under Data Mining Algorithm.

The objective of this study was to explore the application value of intracavitary electrocardiogram- (IEGM-) guided diagnosis of occult heart disease and conventional electrocardiogram (EGM) in the diagnosis of occult coronary heart disease (CHD) based on the classification and regression tree (CART) mining algorithm, hoping to provide a more effective basis for clinical diagnosis of the occult CHD. In this study, 100 patients with occult CHD admitted to our hospital from February 2016 to December 2020 were selected as the research objects. Based on the random number table method, 100 patients were randomly rolled into two groups, each with 50 cases. The patients diagnosed with conventional ECG were set as the control group, and patients in the experimental group were diagnosed with IEGM under the data mining algorithms. The diagnostic effects of the two groups were compared. The results showed that the processing effect of the CART algorithm (94%) was much better than that of the multiple linear regression algorithm (78%) and the random forest algorithm (69%) (P < 0.05), the agreement between the results of the experimental group and the results of coronary angiography (80%) and Kappa (0.7) was higher than those of the control group (55%, 0.45), and the difference was statistically significant (P < 0.05). In addition, the sensitivity (93%) and accuracy (80%) of the experimental group were obviously higher than those of the control group (62% and 55%), and the differences were remarkably significant (P < 0.05). In conclusion, the consistency ratio of the IEGM examination was higher, showing high accuracy; the intracavitary examination was invasive, so IEGM was not recommended when the diagnosis result of the examination may cause more harm than good.

Comparative Analysis of Classification Algorithms in the Analysis of Medical Images From Speckle Tracking Echocardiography Video Data

Background. Machine learning allows applying various intelligent algorithms to produce diagnostic and/or prognostic models. Such models can be used to determine the functional state of the heart, which is diagnosed by speckle-tracking echocardiography. To determine the patient's heart condition in detail, a classification approach is used in machine learning. Each of the classification algorithms has a different performance when applied to certain situations. Therefore, the actual task is to determine the most efficient algorithm for solving a specific task of classifying the patient's heart condition when applying the same speckle-tracking echocardiography data set. Objective. We are aimed to evaluate the effectiveness of the application of prognostic models of logistic regression, the group method of data handling (GMDH), random forest, and adaptive boosting (AdaBoost) in the construction of algorithms to support medical decision-making on the diagnosis of coronary heart disease. Methods. Video data from speckle-tracking echocardiography of 40 patients with coronary heart disease and 16 patients without cardiac pathology were used for the study. Echocardiography was recorded in B-mode in three positions: long axis, 4-chamber, and 2-chamber. Echocardiography frames that reflect the systole and diastole of the heart (308 samples in total) were taken as objects for classification. To obtain informative features of the selected objects, the genetic GMDH approach was applied to identify the best structure of harmonic textural features. We compared the efficiency of the following classification algorithms: logistic regression method, GMDH classifier, random forest method, and AdaBoost method. Results. Four classification models were constructed for each of the three B-mode echocardiography positions. For this purpose, the data samples were divided into 3: training sample (60%), validation sample (20%), and test sample (20%). Objective evaluation of the models on the test sample showed that the best classification method was random forest (90.3% accuracy on the 4-chamber echocardiography position, 74.2% on the 2-chamber, and 77.4% on the long axis). This was also confirmed by ROC analysis, wherein in all cases, the random forest was the most effective in classifying cardiac conditions. Conclusions. The best classification algorithm for cardiac diagnostics by speckle-tracking echocardiography was determined. It turned out to be a random forest, which can be explained by the ensemble approach of begging, which is inherent in this classification method. It will be the mainstay of further research, which is planned to be performed to develop a full-fledged decision support system for cardiac diagnostics.

Determinants of Coronary Heart Disease Incidence among Indonesian Hajj Pilgrims Hospitalized in Saudi Arabia in 2019

BACKGROUND: Cardiovascular diseases (CVDs) are the main causes of death worldwide, including in the hajj pilgrims. Coronary heart disease (CHD) is the most common CVDs in Indonesian hajj pilgrims hospitalized in Saudi Arabia. AIM: This study aimed to determine the determinants of the CHD incidence among Indonesian hajj pilgrims hospitalized in Saudi Arabia in 2019. METHODS: This study was an observational analytic study with a case–control design. The study was conducted in Makassar using data from the integrated Hajj computerized system in the health sector (siskohatkes) Hajj Health Center (Puskeshaji) in January–June 2021. Cases were pilgrims hospitalized in Saudi Arabia with a diagnosis of CHD, about 186 people, and controls were pilgrims hospitalized with diagnoses other than CVDs. Selection of controls by matching age and sex with a ratio of 1:1. The determinants analyzed included education, high blood pressure, high blood sugar levels, high low-density lipoprotein (LDL) cholesterol levels, excess body mass index (BMI), and smoking. Data analysis was using the STATA program with an odds ratio (OR) test and multiple logistic regression. RESULTS: The most respondents were 65 years (48.39%), female respondents, about 61.83%. Most respondents’ education was in elementary school, about 31.99%. Multivariate analysis showed that high blood pressure (OR = 2.32, 95% confidence index [CI] = 1.50–3.57), high blood sugar levels (RO = 1.90, 95% CI = 1.06–3.40), high LDL cholesterol levels (RO = 1.82, 95% CI = 1.15–2.88), and excess BMI (RO = 1.73, 95% CI = 1.07–2.68) were risk factors for the CHD incidence. However, education and smoking were not risk factors for CHD. CONCLUSION: By multiple logistic regression analyzes, the study revealed that the probability of CHD when having those four risk factors was 85.69%.

Algorithmic Study of the Characteristics of Electrocardiograph Signals in Patients with Coronary Heart Disease

This work aimed to analyze the electrocardiogram (ECG) characteristics and signal classification of patients with coronary heart disease (CHD) diagnosed by coronary angiography, so as to provide a theoretical basis for the clinical adoption of ECG images. 106 patients with CHD who were admitted to the XXX hospital from January 15, 2019, to May 30, 2020, underwent coronary intervention therapy, and their ECG indicators were recorded during the operation. Then, the LetNet-SoM algorithm designed in this work, as well as the traditional algorithms GoogLeNet and SqueezeNet, was applied to the patient’s ECG classification. It was found that part of ECG wave (QRS) and corrected Q-T interval (QTC) of patients after treatment were higher than those before treatment ( P &lt; 0.05 ), but PR interval, RR interval, Tpeak-Tend (TpTe) interval, and QT interval were not substantially different from those before treatment ( P &gt; 0.05 ). The diagnostic accuracy, sensitivity, and specificity of LetNet-SoM algorithm for patients with CHD were better than those of traditional algorithms, with evident difference ( P &lt; 0.05 ). The classification time of LetNet-SoM algorithm was lower in contrast to that of traditional algorithms, and the difference was also notable ( P &lt; 0.05 ). The R wave and T wave indicators of patients after treatment were higher than before treatment, with notable difference ( P &lt; 0.05 ). The difference between the patient’s S wave indicator before and after treatment was not statistically significant ( P &gt; 0.05 ). The positive rate of S wave amplitude, QRS, and QTC was 68.15%, 60.52%, and 51.36%, respectively. In short, the LetNet-SoM algorithm designed based on lightweight neural network had excellent performance in classification and diagnosis of ECG, and it had the value of further popularization and application. The ECG signals were important indicators in the diagnosis of CHD, among which the S wave amplitude, QRS, and QTC were the most sensitive ones.

Value of acoustic cardiography in the clinical diagnosis of coronary heart disease.

BackgroundTo investigate the clinical value of acoustic cardiography in the diagnosis of coronary artery disease (CAD) and post‐percutaneous coronary intervention (PCI) early asymptomatic left ventricular systolic dysfunction.MethodsInpatients in the department of cardiology were included in the research (n = 315); including 180 patients with angina pectoris and 135 patients with acute anterior wall myocardial infarction after emergency PCI did not present with signs and symptoms of heart failure. Color Doppler echocardiography, brain natriuretic peptide, acoustic cardiography examination were performed. The patients were divided into four groups: non‐CAD group (n = 60), CAD group (n = 120), MIREF group (EF% < 50%, n = 75), and MINEF group (EF% ≥ 50%, n = 60).ResultsAcoustic cardiography parameters EMATc, systolic dysfunction index, S3 strength and S4 strength in the MIREF group were higher than those in MINEF group (p < .05), and the MINEF group was higher than CAD group (p < .05). S3 strength (area under the curve [AUC] 0.67, 95% CI 0.585–0.755, p < .001) and S4 strength (AUC 0.617, 95% CI 0.536–0.698, p = .011) are useful in the diagnosis of CAD. S3 strength (AUC 0.942, 95% CI 0.807–0.978, p < .001) was superior to other indicators in the diagnosis of early left ventricular systolic dysfunction after myocardial infarction.ConclusionS4 combined with STT standard change can improve the diagnosis of CAD. Acoustic cardiography can be used as a non‐invasive, rapid, effective, and simple method for the diagnosis of asymptomatic left ventricular systolic dysfunction in the early stage after myocardial infarction.

Prognostic signs of an unfavorable course of coronary heart disease in patients with type 2 diabetes mellitus

Background. Despite the successful development of medical technologies in the diagnosis of coronary heart disease, mortality due to cardiovascular diseases in the population of patients with diabetes mellitus (DM) is not reduced. The development of an algorithm for the early diagnosis of coronary heart di­sease and ways to correct it is a topical problem of cardiology and endocrinology. The purpose is to determine prognostic signs for an unfavorable course of coronary heart disease and develop a table of test probabilities in order to enhance the effectiveness of risk stratification in patients with type 2 DM. Materials and methods. During 2017–2019, there were observed 40 patients (16 men and 24 women) with type 2 DM in combination with coronary heart disease. We took into account the presence of acute myocardial infarction, acute cerebrovascular accidents (stroke), repeated surgical interventions (percutaneous coronary intervention, coronary artery bypass grafting) for the last 3 years. The average age of patients was 65.5 years. Results. In total, 119 signs recorded in the first three days from the moment of patient’s admission were analyzed as possible predictors of an unfavorable prognosis. As markers of coronary heart disease, parameters were adopted that showed the highest occurrence in the group of patients with adverse course of DM and coronary heart disease. The most patho­gnomonic predictors of coronary heart disease progression in patients with type 2 DM were left ventricular systolic dysfunction (ejection fraction &lt; 40 %), systolic blood pressure &gt; 160 mmHg or diastolic blood pressure above 100 mmHg, electrocardiographic signs of myocardial ischemia, persisting upon discharge from the hospital. Conclusions. Criteria that negatively affect the long-term outcome of coronary heart disease in patients with type 2 diabetes are decompensation of DM, in particular, a high level of fasting glycemia (&gt; 13 mmol/l), as well as an increase in total cholesterol and low-density lipoprotein cholesterol.

Study on syndrome differentiation strategy of phlegm and blood stasis syndromes of coronary heart disease based on expert consultation on medical cases.

It is becoming more and more important to judge whether patients with coronary heart disease (CHD) have phlegm and blood stasis syndromes in the process of traditional Chinese medicine (TCM) diagnosis and treatment of CHD. The syndrome differentiation strategy of phlegm and blood stasis syndromes of CHD is still not standardized, and it is particularly necessary to make syndrome differentiation simpler and more accurate. Twenty-eight medical cases that met the criteria, comprising 10 ancient medical cases and 18 modern ones, were selected from the TCM literature, which were then analyzed by 57 experts via questionnaire. Statistical analysis of the data was mainly based on frequency analysis. (I) The average age of the 57 experts from 20 provinces was 48.9±8.5 years; 89.5% were associate professor or above, and 75.4% of them worked at a tertiary hospital. (II) Consistency of expert consultation over medical cases: for the ancient medical cases, the diagnostic consistency rate of phlegm syndrome was 27/34 (79.4%) and additional diagnosis rate of the blood stasis syndrome was 27/57 (47.4%); for the modern medical cases, the consistency rate compared with the original diagnosis of phlegm syndrome was 54/80 (67.5%) and that of blood stasis syndrome was 73/90 (81.1%). (III) The top five experts' diagnostic basics of phlegm syndrome were oppression in the chest, slippery pulse, greasy fur, coughing of phlegm, and chest pain; the top five diagnostic basics of blood stasis syndrome were chest pain, dark tongue, oppression in chest, red tongue, and ecchymosis on tongue. (IV) In the questionnaire consultation on CHD phlegm-blood stasis syndrome cases, the diagnostic basis of "symptom or (and) tongue manifestation" accounted for 12/27 (44.4%) of the diagnostic basics of phlegm syndrome and 28/38 (73.7%) of that of blood stasis syndrome basis. Modern Chinese medicine experts pay much attention to the diagnosis and treatment of CHD based on TCM pathology theories of phlegm and blood stasis. To collect and detect the patients' symptoms and tongue manifestation is an important strategy of the experts for CHD phlegm and blood stasis syndrome differentiation.

Correlation between coronary CTA-SYNTAX score and invasive coronary angiography-SYNTAX score.

It is important to evaluate the complex coronary artery disease in the diagnosis and treatment of coronary heart disease.The SYNTAX score based on invasive coronary angiography (ICA) (also referred to as ICA-SYNTAX score) plays a positive role in the selection of revascularization of complex coronary artery disease and the prediction of adverse events.The development of coronary computed tomography angiography (CCTA) technology promotes the clinical application of SYNTAX score (CCTA-SYNTAX score) based on coronary CTA, and also enriches the examination methods of patients with coronary heart disease. The CCTA-SYNTAX score has the advantages of non-invasiveness, simple operation, good reproducibility, and relatively low cost, which can make it play an increasingly important role in the diagnosis of coronary heart disease. A number of foreign studies have confirmed that CCTA-SYNTAX score is highly correlated with ICA-SYNTAX score, which further promotes the study of CCTA-SYNTAX score in revascularization of percutaneous coronary intervention (PCI) or coronary artery bypass grafting (CABG) and adverse event prediction.Therefore, the CCTA-SYNTAX score can be an auxiliary method for the ICA-SYNTAX score, as the first choice for preoperative evaluation and postoperative review of patients with coronary heart disease.

Application of CT coronary flow reserve fraction based on deep learning in coronary artery diagnosis of coronary heart disease complicated with diabetes mellitus

Application of CT coronary flow reserve fraction based on deep learning in coronary artery diagnosis of coronary heart disease complicated with diabetes mellitus

Scope and Social Determinants of Food Insecurity Among Adults With Atherosclerotic Cardiovascular Disease in the United States

BackgroundAtherosclerotic cardiovascular disease (ASCVD) results in high out‐of‐pocket healthcare expenditures predisposing to food insecurity. However, the burden and determinants of food insecurity in this population are unknown.Methods and ResultsUsing 2013 to 2018 National Health Interview Survey data, we evaluated the prevalence and sociodemographic determinants of food insecurity among adults with ASCVD in the United States. ASCVD was defined as self‐reported diagnosis of coronary heart disease or stroke. Food security was measured using the 10‐item US Adult Food Security Survey Module. Of the 190 113 study participants aged 18 years or older, 18 442 (adjusted prevalence 8.2%) had ASCVD, representing ≈20 million US adults annually. Among adults with ASCVD, 2968 or 14.6% (weighted ≈2.9 million US adults annually) reported food insecurity compared with 9.1% among those without ASCVD (P<0.001). Individuals with ASCVD who were younger (odds ratio [OR], 4.0 [95% CI, 2.8–5.8]), women (OR, 1.2 [1.0–1.3]), non‐Hispanic Black (OR, 2.3 [1.9–2.8]), or Hispanic (OR, 1.6 [1.2–2.0]), had private (OR, 1.8 [1.4–2.3]) or no insurance (OR, 2.3 [1.7–3.1]), were divorced/widowed/separated (OR, 1.2 [1.0–1.4]), and had low family income (OR, 4.7 [4.0–5.6]) were more likely to be food insecure. Among those with ASCVD and 6 of these high‐risk characteristics, 53.7% reported food insecurity and they had 36‐times (OR, 36.2 [22.6–57.9]) higher odds of being food insecure compared with those with ≤1 high‐risk characteristic.ConclusionAbout 1 in 7 US adults with ASCVD experience food insecurity, with more than 1 in 2 adults reporting food insecurity among the most vulnerable sociodemographic subgroups. There is an urgent need to address the barriers related to food security in this population.

RETRACTED ARTICLE: A novel intelligent machine learning system for coronary heart disease diagnosis

RETRACTED ARTICLE: A novel intelligent machine learning system for coronary heart disease diagnosis

Ultra-Fast Label-Free Serum Metabolic Diagnosis of Coronary Heart Disease via a Deep Stabilizer.

Although mass spectrometry (MS) of metabolites has the potential to provide real‐time monitoring of patient status for diagnostic purposes, the diagnostic application of MS is limited due to sample treatment and data quality/reproducibility. Here, the generation of a deep stabilizer for ultra‐fast, label‐free MS detection and the application of this method for serum metabolic diagnosis of coronary heart disease (CHD) are reported. Nanoparticle‐assisted laser desorption/ionization‐MS is used to achieve direct metabolic analysis of trace unprocessed serum in seconds. Furthermore, a deep stabilizer is constructed to map native MS results to high‐quality results obtained by established methods. Finally, using the newly developed protocol and diagnosis variation characteristic surface to characterize sensitivity/specificity and variation, CHD is diagnosed with advanced accuracy in a high‐throughput/speed manner. This work advances design of metabolic analysis tools for disease detection as it provides a direct label‐free, ultra‐fast, and stabilized platform for future protocol development in clinics.

Оцінка повздовжньої деформації лівого шлуночка і її зміни при інфаркті міокарда та ішемічній хворобі серця з обструктивним ураженням коронарних артерій

The review provides data on a new method of ultrasound diagnostics – speckle tracking echocardiography in the diagnosis of myocardial infarction and coronary heart disease with obstructive coronary artery lesions, the advantages of the global longitudinal strain (GLS) compared to the existing echocardiographic indicators of global systolic and segmental systolic function. The value of measuring GLS in coronary heart disease is the quantitative detection of wall motion abnormalities, when left ventricular ejection fraction is within normal values and visual assessment does not detect violations of regional contractility. In patients with myocardial infarction without ST-segment elevation, GLS measurement may assist in the selection of patients who need urgent reperfusion therapy. In coronary heart disease, GLS can complement the conventional assessment of wall movement; replace the need for additional non-invasive testing for some patients with suboptimal stress tests. The normal limits of the GLS for various manufacturers of ultrasound scanners and technical characteristics for the correct studying of the GLS are described. The value of the GLS gradually decreases in mild, moderate and severe forms of coronary heart disease, and is the lowest in patients with myocardial infarction with ST segment elevation. The possibilities of detecting infarct-related coronary artery using the amplitude of the segmental strain and the «bull’s eye» diagram in isolated lesions of one of the coronary arteries are described. The analysis of the strain curves is carried out, the characteristics of the strain curve in normal conditions and in ischemia are presented. The probable signs of ischemia are the phenomena of early systolic lengthening and postsystolic shortening on the curves of longitudinal deformation. The conditions when the postsystolic contraction on the strain curve is pathological are described. Key words: global longitudinal strain, myocardial infarction, ischemic heart disease, «bull’s eye», early systolic lengthening, postsystolic shortening.

Resilience and associated psychological, social/cultural, behavioural, and biological factors in patients with cardiovascular disease: a systematic review.

The aim of this systematic review of the literature is to synthesize the evidence regarding the associations between individual-level psychological, social/cultural, behavioral, and biological variables with resilience in patients with CVD. A systematic search of PubMed, PsycINFO and CINAHL was conducted from database inception through March 2020. Studies with a quantitative research design were eligible for inclusion if published in English and focused on resilience among adults with CVD. Of the 788 articles retrieved, 34 studies (35 articles) were included in the review. Twenty-three studies focused on psychological factors, with findings of inverse relationships between resilience and depression, anxiety, and stress. Evidence regarding associations between resilience and social/cultural or behavioral variables was scarce. Four of the 6 studies regarding biological factors found low stress resilience in young adulthood was associated with early diagnoses of stroke, heart failure, and coronary heart disease. Enhancing resilience may improve quality of life for CVD patients, but research is needed to further explore the complex relationships between resilience and associated variables. This research should prioritize under-represented groups (i.e. women and minority racial/ethnic groups), with the eventual goal of developing interventions to support resilience in CVD patients.

Comparative analysis of ischemic changes in electrocardiogram and coronary angiography results: A retrospective study.

To improve the correct diagnosis rate of coronary heart disease and to explore the guiding value of electrocardiogram (ECG) ST-T ischemic changes in the clinical diagnosis of coronary heart disease.A retrospective analysis was conducted on a total of 310 cases who underwent a conventional 12-lead ECG, 12-lead dynamic ECG (DECG, Holter) with ST-T ischemic changes, and then coronary angiography (CA) within 1 week in Qingdao Sttarr Heart Hospital from June 2015 to April 2020 in the study. Ischemic ST-T changes were evaluated using conventional diagnostic criteria, and Judkins diagnostic criteria were used in CA. The sensitivity and specificity of ECG were analyzed.The specificity of ST-T changes in conventional ECG for the diagnosis of coronary heart disease is 33.7% and the sensitivity is 66.0%. The specificity of ST-T changes in Holter in the diagnosis of coronary heart disease is 55.6% and the sensitivity is 32.2%. The sensitivity of conventional ECG for the diagnosis of coronary heart disease is better than Holter, but its specificity is inferior to Holter. The negative likelihood ratios of the 2 ECGs for the diagnosis of coronary heart disease were 1.0 and 1.22, both >0.1, and the positive likelihood ratios were 0.99 and 0.73, both <10. The positive results of ST-T in conventional ECG were 128 males (65.7%), 77 females (66.9%), (P < .05), 148 cases (74.7%) in the group ≥60 years old, and 75 cases in the group less than 60 years (67%), (P > .05). The positive results of ST-T change of DECG were 135 males (69.2%), 69 females (60.0%), (P < .05), 152 cases (78.7%) in the group ≥60 years, and 83 cases (70.9%) in the group less than 60 years, (P > .05). Coronary heart disease-related factors: symptoms, hypertension, diabetes, cancer, family history, smoking history as independent variables, and a binary multivariate logistic regression analysis was performed.The sensitivity of DECG in the diagnosis of myocardial ischemia in women and the elderly was slightly higher than that in men and young cases. ST-T ischemic changes in ECG are more significant for the diagnosis of coronary heart disease in male patients. Smoking, hypertension, diabetes, and family history are all high-risk factors for coronary heart disease.

Treatment of Complicated Coronary Heart Disease after Successful Prehospital Resuscitation in a Public Place

The current problem of modern medicine is the lack of public awareness about personal health, late diagnosis of diseases, untimely prehospital care and treatment of existing complications. This applies to all branches of medicine, especially cardiology and cardiac surgery. Coronary heart disease occupies one of the leading places in the structure of mortality due to cardiovascular diseases. This is mainly due to the fact that patients seek medical care with complicated forms of coronary heart disease like sudden cardiac death, cardiac arrhythmia (ventricular fibrillation, AV blockade, sinus bradycardia and tachycardia), formation of left ventricular (LV) aneurysm, LV free wall rupture and LV false aneurysm, mitral regurgitation. In such cases, all actions must be early, staged, well established, and concordant with clear algorithm.&#x0D; The aim. To demonstrate our clinical case as an example of proper logistics, rapid response and timely surgical treatment of complicated forms of coronary heart disease.&#x0D; Clinical case. Patient F., born in 1964, was admitted to the clinic on March 24, 2021 with a diagnosis of coronary heart disease: acute non-Q-wave myocardial infarction of the posterolateral LV since March 22, 2021. Clinical death with successful resuscitation at the prehospital stage (03/22/2021). Ventricular fibrillation (03/22/2021). Multivessel coronary artery disease. Mitral valve regurgitation grade II-III. Tricuspid valve regurgitation grade I-II. Pulmonary hypertension grade I. Hypertensive disease grade III, degree 3, risk 4 (very high). Heart failure II A with a moderately reduced LV ejection fraction (47%). NYHA3. Closed chest injury (03/22/2021): fracture of the ribs without displacement: ribs 4-8 on the left, ribs 4-8 on the right. He considers himself ill since March 22, 2021, when he suddenly felt severe pain in his chest and fell unconscious. According to witnesses, the man got out of the subway and fell unconscious, without breathing and pulse. Due to the presence of defibrillators at the subway station, successful resuscitation was conducted by police officers before the ambulance crew arrival. Clinical and instrumental studies were performed after hospitalization. The patient was taken to the operating room on 03/24/2021 at 5:30 PM, 50 minutes after admission to the National Amosov Institute, Kyiv. Urgent off-pump coronary artery bypass grafting of 3 coronary arteries was performed. A cardioverter-defibrillator was implanted due to the history of clinical death and the conclusion of daily ECG monitoring. The intra- and postoperative period was uneventful, the patient was discharged in satisfactory condition for rehabilitation.&#x0D; Conclusions. Our clinical experience shows that timely prehospital care, proper logistics and surgical correction of coronary heart disease not only saves but also significantly improves the quality of life of the patient in the future.

Analysis of quantitative and qualitative indicators of myocardial function for planning and evaluation of the surgical treatment results in patients with coronary heart disease

Coronary heart disease (CHD) is the main cause of the occurrence and progression of heart failure, as well as mortality among the adult population, both in Russia and around the world. Determining the functional state of the myocardium before surgery allows one to choose the right treatment strategy, methods of surgical correction of coronary disorders, and predict outcomes.Aim. The research aims at the improvement of methods for predicting revascularization outcomes by creating a mathematical model depending on the number of viable myocardium.Material and methods. We examined 118 patients with a diagnosis of CHD who underwent surgical correction of coronary blood fl ow disorders with the use of direct and indirect revascularization methods at the Pirogov National Medical Center. We analyzed correlation between gated-SPECT, Echocardiography and operation results.Results. An inverse strong correlation has been found between LV contractility after surgery and the preoperative amount of scar myocardium and the end diastolic volume (EDV) LV (p &lt; 0.05, Spearman criterion). A direct correlation has been determined between the improvement of EF and the volume of the hibernated myocardium (p &lt; 0.05, Spearman criterion). There is a model for predicting EF after revascularization: Ejection fraction (after revascularization)(%) = 70.99126 − 0.10490 × EDV (ml) + 0.38827 × hibernated myocardium(%) − – 0,50137 × scar myocardium (%).Conclusion. Statistical modeling based on quantitative and qualitative assessment of the functional state of the myocardium in patients with CHD with the use of gated-SPECT and Echocardiography is an actual and necessary way to fi nd optimal solutions in the treatment and rehabilitation of patients with CHD.

An accurate diagnosis of coronary heart disease by Catboost, with easily accessible data

Coronary heart diseases (CHD) have become the leading cause of death worldwide. Coronary angiography is the “gold standard” for diagnosing this disease. However, the invasive risk and expensive price make it difficult to promote on a large scale. This study was using Catboost to diagnose CHD through simple indicators. 2642 samples, including 717 patients, were collected from 2018 to 2019. 33 features were collected, including demography, anthropometry, questionnaire and laboratory examination indicators. The diagnosis model of CHD was established by using Catboost, random forest and logistic regression. Accuracy and area under ROC (AUROC) were used to evaluate the classification performance of the diagnosis models. In order to facilitate the application, we also set up a simplified model merely based on non-laboratory dataset. Catboost showed the best performance in identifying patients with CHD. The accuracy of Catboost, random forest and logistic regression was 82.5%, 75.1%, 75.8%, respectively, and the AUROC of them was 0.881, 0.837, 0.832, respectively. Age, total cholesterol and family history of coronary heart disease were the three most important risk factors for diagnosing CHD. Catboost also worked best in simplified models with 77.9% accuracy and 0.857 AUROC. The models can contribute to early screening and diagnosis for CHD, which would facilitate the prevention and timely treatment of the diseases.

Fuzzy-based Decision for Coronary Heart Disease Diagnosis: Systematic Literature Review

Coronary heart disease is usually caused by a buildup of fatty material and plaque inside the coronary arteries. The death rate caused by coronary heart diseases is threatening around the world. For the past two decades, most of the people from developing countries are suffering from heart disease. Diagnosing these diseases at earlier stages helps patients reduce the risk of death and also in reducing the cost of treatment. Decisions in medical diagnosis are mostly taken by expert’s experiences. In many cases, not all the expert’s experiences contribute towards effective diagnosis of a disease. Many alternative methods have been suggested for medical diagnosis in the healthcare domain. However, evaluating the functionality of coronary heart diseases diagnosis systems remains challenging. The purpose of this paper is to perform a study on literature related to fuzzy-based decision for diagnosis of coronary heart disease. Accordingly, the research gathered studies related to fuzzy-based decision for diagnosis of coronary heart disease between the periode 2016-2021.