scholarly journals KNOWLEDGE AND AWARENESS ABOUT ANGINA PECTORIS AMONG PHARMACY STUDENTS

2014 ◽  
Vol 4 ◽  
pp. 81
Author(s):  
Humera Khatoon ◽  
Keyword(s):  
Myocardial Infarction ◽  
Angina Pectoris ◽  
Blood Supply ◽  
Heart Muscle ◽  
Heart Attack ◽  
Pharmacy Students ◽  
Warning Sign ◽  
Chest Discomfort ◽  
Adequate Blood Supply ◽  
Disease Sign

Objective of this study is to determine the awareness among student of Pharm D with Angina Pectoris (AP) regarding the disease, sign & symptoms and treatment.The term Angina Pectoris is applied to varying forms of transient chest discomfort that are attributable to insufficient myocardial oxygen. The classic description of angina is a crushing pain that radiates through the chest and sometimes down the arm, neck, teeth /jaw or into the back, which is usually aggravated by exertion or stress. Angina is a warning sign that the heart muscle is not getting adequate blood supply and specially oxygen and it may lead to myocardial infarction or a heart attack

Myocardial infarction (clinic, diagnostic features, complications, treatment)

1997 ◽  
Vol 78 (2) ◽  
pp. 120-128
Author(s):  
I. A. Latfullin
Keyword(s):  
Myocardial Infarction ◽  
Blood Supply ◽  
Coronary Arteries ◽  
Heart Muscle ◽  
Oxygen Demand ◽  
Myocardial Oxygen Demand ◽  
Ischemic Necrosis ◽  
Diagnostic Features

Myocardial infarction (MI) occurs due to an acute mismatch between myocardial oxygen demand and its blood supply through the coronary arteries of the heart, which results in the development of ischemic necrosis of the heart muscle with subsequent topical changes on ECG.

scholarly journals An Effective Deep Learning Model for Automated Detection of Myocardial Infarction Based on Ultrashort-Term Heart Rate Variability Analysis

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Muhammad Bilal Shahnawaz ◽  
Hassan Dawood
Keyword(s):  
Myocardial Infarction ◽  
Heart Rate ◽  
Heart Rate Variability ◽  
Deep Learning ◽  
Blood Supply ◽  
Heart Attack ◽  
Learning Model ◽  
Fluctuation Analysis ◽  
Hrv Analysis ◽  
Deep Learning Model

Myocardial infarction (MI), usually termed as heart attack, is one of the main cardiovascular diseases that occur due to the blockage of coronary arteries. This blockage reduces the blood supply to heart muscles, and a prolonged deficiency of blood supply causes the death of heart muscles leading to a heart attack that may cause death. An electrocardiogram (ECG) is used to diagnose MI as it causes variations like ST-T changes in the recorded ECG. Manual inspection of these variations is a tedious task and also requires expertise as the variations produced by MI are often very short in duration with a low amplitude. Hence, these changes may be misinterpreted, leading to delayed diagnosis and appropriate treatment. Therefore, computer-aided analysis of ECG may help to detect MI automatically. In this study, a robust deep learning model is proposed to detect MI based on heart rate variability (HRV) analysis of ECG signals from a single lead. Ultrashort-term HRV analysis is performed to compute HRV analysis features from time-domain and frequency-domain parameters through power spectral density estimations. Nonlinear HRV parameters are also computed using Poincare Plot, Recurrence Analysis, and Detrended Fluctuation Analysis. A finely tuned customized artificial neural network (ANN) algorithm is applied on 23 HRV features for MI detection and classification. The K-fold validation method is used to avoid any biases in results and reported 99.1% accuracy, 100% sensitivity, 98.1% specificity, and 99.0% F1 for MI detection, whereas 98.85% accuracy, 97.40% sensitivity, 99.05% specificity, and 97.70% F1 score is achieved for classification. Furthermore, the ANN algorithm completed its execution in just 59 seconds that indicates the efficiency of the proposed ANN model. The overall performance in terms of computed evaluation matrices and execution time indicates the robustness and cost-effectiveness of the proposed methodology. Thus, the proposed model can be used for high-performance MI detection, even in wearable devices.

scholarly journals Myocardial Infarction

2022 ◽  
pp. 16-32
Author(s):  
Abhishek Kumar Singh ◽  
Rakesh Kumar Jat
Keyword(s):  
Myocardial Infarction ◽  
Heart Muscle ◽  
Muscle Function ◽  
Heart Attack ◽  
Sleep Disturbances ◽  
Common Symptom ◽  
Channel Blockers ◽  
Shortness Of Breath ◽  
Acute Mi ◽  
Zero Flow

Myocardial infarction (MI), commonly known as a heart attack is the disease of the blood vessels supplying the heart muscle (Myocardium) i.e. coronary heart disease. The area of heart muscle that has either zero flow or so little flow that it cannot sustain cardiac muscle function is said to be infracted and the overall process is called a myocardial infarction. MI are of two types; transmural and subendocardial. Mainly it is caused due to oxidative stress and atherosclerosis.Chest pain is the most common symptom of acute MI and is often described as a sensation of tightness, pressure, or squeezing. Other symptoms include diaphoresis (an excessive form of sweating), Shortness of breath (dyspnea), weakness, light-headedness, nausea, vomiting, and palpitations. The most common symptoms of MI in women include dyspnea, weakness, and fatigue, sleep disturbances. It can be treated by using  blockers, diuretics, ACE inhibitors, calcium channel blockers and nitrates.

Computer Simulations of the Blood Flows and the Growth of Stenosis in Arteries With Bends and Bifurcations

2009 ◽  
Author(s):  
Biyue Liu ◽  
Dalin Tang
Keyword(s):  
Shear Stress ◽  
Blood Supply ◽  
Heart Muscle ◽  
Heart Attack ◽  
Computational Models ◽  
Fluid Shear Stress ◽  
The United States ◽  
Human Aorta ◽  
Atherosclerotic Plaques ◽  
Artery Wall

Heart attack and stroke are the chief and the 3rd largest causes of death in the United States, respectively. A heart attack occurs when the blood supply to an area of heart muscle is blocked, usually by a clot in a coronary artery; a stroke occurs when the blood supply to a region of the brain is lost. The most frequent cause of loss of blood supply to brain tissue or to heart muscle is atherosclerosis, which involves complex interactions between the artery wall and the blood flow. Caro et al first suggested that the distribution of fatty streaking in human aorta may be coincident with regions in which the shear rate at the arterial wall is locally reduced [1]. After that, intensive research has been conducted to statistically study the role of shear stress in atherosclerosis and to quantitatively determine the correlation between the low shear stress and the development of atherosclerotic plaques [2–8]. It is widely believed that fluid shear stress acting on the artery wall plays an important role in the pathogenesis of atherosclerosis. The objectives of this project are to investigate how the geometrical adaptation of atherosclerotic plaques is related to the wall shear stress (WSS) and to study the influences of the flow parameters on the growth of the atherosclerotic plaque using computational models.

scholarly journals GAMBARAN KADAR HEMATOKRIT DAN HEMOGLOBIN PADA KEJADIAN INFARK MIOKARD AKUT (IMA) DI RSUP PROF. DR. R. D. KANDOU MANADO PERIODE JANUARI - AGUSTUS 2014

e-CliniC ◽  
2015 ◽  
Vol 3 (1) ◽  
Author(s):  
Fitri Jumalang ◽  
Linda W. A. Rotty ◽  
Agnes L. Panda
Keyword(s):  
Myocardial Infarction ◽  
Acute Myocardial Infarction ◽  
Cell Death ◽  
Heart Muscle ◽  
Heart Attack ◽  
Descriptive Study ◽  
Developed Countries ◽  
Heart Muscle Cell ◽  
Common Diagnosis ◽  
Age And Sex

Abstract: Acute myocardial infarction (AMI) or better known as a heart attack is a condition where the blood supply to a part of the heart stops so that the heart muscle cell death. Acute myocardial infarction is one of the most common diagnosis in developed countries. The rate of initial mortality (30 days) at the IMA is 30% with more than half of the deaths occur before the patient reaches the hospital. Methods - This research is a retrospective descriptive study. Samples were adult patients suffering from acute myocardial infarction who were treated in RSUP Prof. Dr R. D. Kandou. Results - Overview hematocrit and hemoglobin levels in the incidence of acute myocardial infarction in the department of Prof. Dr. RD Kandou Manado period January - August 2014 hemodilution patients get as many as 19 people (61.3%) and patients with normal hematocrit many as 12 people (38.7% ). In addition, for an overview of hemoglobin by age and sex obtained anemia patients by 5 people (16.1%) and patients with normal hemoglobin many as 26 people (83.9%). Conclusions - AMI patients in RSUP Prof. Dr RD Kandou Manado period January-August 2014 are subjected to low hematocrit (hemodilution) and normal hemoglobin.Keywords: acute myocardial infarction, hematocrit, hemoglobinAbstrak: Infark miokard akut (IMA) atau yang lebih dikenal dengan serangan jantung adalah suatu keadaan dimana suplai darah pada suatu bagian jantung terhenti sehingga sel otot jantung mengalami kematian. Infark miokard akut merupakan salah satu diagnosis rawat inap tersering di negara maju. Laju mortalitas awal (30 hari) pada IMA adalah 30% dengan lebih dari separuh kematian terjadi sebelum pasien mencapai Rumah Sakit. Metode - Penelitian ini merupakan penelitian deskriptif retrospektif. Sampel penelitian ini adalah penderita dewasa yang menderita infark miokard akut yang dirawat di RSUP Prof. Dr. R. D. Kandou. Hasil - Gambaran kadar hematokrit dan hemoglobin pada kejadian infark miokard akut di RSUP Prof DR RD Kandou Manado periode januari – agustus 2014 didapatkan pasien hemodilusi sebanyak 19 orang (61,3%) dan pasien hematokrit normal sebanyak 12 orang (38,7%). Selain itu, untuk gambaran hemoglobin berdasarkan umur dan jenis kelamin didapatkan pasien yang anemia sebanyak 5 orang (16,1%) dan pasien hemoglobin normal sebanyak 26 orang (83,9%). Simpulan - Pasien IMA di RSUP Prof. Dr. R. D. Kandou Manado periode januari-agustus 2014 sebagian besar mengalami hematokrit rendah (hemodilusi) dan hemoglobin normal.Kata kunci: infark miokard akut, hematokrit, hemoglobin

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