The objectives of this study were to evaluate the time delays between the onset of symptoms and admission to hospital and provision of thrombolytic therapy in patients with suspected acute myocardial infarction; and to examine the accuracy of the clinical diagnosis and the therapeutic decision on thrombolysis in these patients. An observational study of 96 patients with suspected myocardial infarction was undertaken over a period of 15 months in the Coronary Care Unit of Hospital Kuala Terengganu. Seventy per cent of the patients arrived in the hospital within 6 hours of the onset of symptoms. After arrival in the emergency room, it took a median time of 85 minutes before the administration of thrombolytic therapy. Of the 67 patients who were given thrombolysis, 46 were treated within 6 hours of the onset of symptoms. About a quarter of patients said that they had delayed seeking treatment at the hospital. Treatment delays occurring in the hospital were mainly due to admission procedures as well as late diagnosis. Eighty-one patients had confirmed myocardial infarction of whom 59 received thrombolytic therapy. Eight patients receiving thrombolytic therapy had no confirmation of myocardial infarctions. Improvements in diagnostic accuracy and reduction of delays in the provision of thrombolytic therapy could be achieved by better training of health care staff as well as by further streamlining of admission procedures.
The aim of the study was to use data from an electronic medical record system (EMR) to look for factors that would help us diagnose acute myocardial infarction (AMI) with the ultimate aim of using these factors in a decision support system for chest pain. We extracted 887 records from the electronic medical record system (EMR) in Selayang Hospital, Malaysia. We cleaned the data, extracted 69 possible variables and performed univariate and multivariate analysis. From the univariate analysis we find that 22 variables are significantly associated with a diagnosis of AMI. However, multiple logistic regression reveals that only 9 of these 22 variables are significantly related to a diagnosis of AMI. Race (Indian), male sex, sudden onset of persistent crushing pain, associated sweating and a history of diabetes mellitus are significant predictors of AMI. Pain that is relieved by other means and history of heart disease on treatment are important predictors of a diagnosis other than AMI. The degree of accuracy is high at 80.5%. There are 13 factors that are significant in the univariate analysis but are not among the nine significant factors in the multivariate analysis. These are location of pain, associated palpitations, nausea and vomiting; pain relieved by rest, pain aggravated by posture, cough, inspiration and exertion; age more than 40, being a smoker and abnormal chest wall and face examination. We believe that these findings can have important applications in the design of an intelligent decision support system for use in medical care as the predictive capability can be further refined with the use of intelligent computational techniques.
The study investigated the effect of different input selections on the performance of artificial neural networks in screening for acute myocardial infarction (AMI) in Malaysian patients complaining of chest pain. We used hospital data to create neural networks with four input selections and used these to diagnose AMI. A 10-fold cross-validation and committee approach was used. All the neural networks using various input selections outperformed a multiple logistic regression model, although the difference was not statistically significant. The neural networks achieved an area under the ROC curve of 0.792 using nine inputs, whereas multiple logistic regression achieved 0.739 using 64 inputs. Sensitivity levels of over 90 per cent were achieved using low output threshold levels. Specificity levels of over 90 per cent were achieved using threshold levels of 0.4-0.5. Thus neural networks can perform as well as multiple logistic regression models even when using far fewer inputs.
Coronary artery disease is one of the most rampant non-communicable diseases in the world. It begins indolently as a fatty streak in the lining of the artery that soon progresses to narrow the coronary arteries and impair myocardial perfusion. Often the atherosclerotic plaque ruptures and causes sudden thrombotic occlusion and acute ST-elevation myocardial infarction (STEMI), non-ST-elevation MI (NSTEMI) or unstable angina (UA). This phenomenon is called acute coronary syndrome (ACS) and is the leading cause of death not only in Malaysia but also globally. In order for us to tackle this threat to the health of our nation we must arm ourselves with reliable and accurate information to assess current burden of disease resources available and success of current strategies. The acute coronary syndrome (ACS) registry is the flagship of the National Cardiovascular Disease Database (NCVD) and is the result of the dedicated and untiring efforts of doctors and nurses in both public and private medical institutions and hospitals around the country, ably guided and supported by the National Heart Association, the National Heart Foundation, the Clinical Research Centre and the Ministry of Health of Malaysia. Analyses of data collected throughout 2006 from 3422 patients with ACS admitted to the 12 tertiary cardiac centres and general hospitals spanning nine states in Malaysia in this first report has already revealed surprising results. Mean age of patients was 59 years while the most consistent risk factor for STEMI was active smoking. Utilization of medications was high generally. Thirty-day mortality for STEMI was 11%, for NSTEMI 8% and UA 4%. Thrombolysis (for STEMI only) reduced in-hospital and 30-day mortality by nearly 50%. Percutaneous coronary intervention or PCI also reduced 30-day mortality for patients with non-ST elevation MI and unstable angina. The strongest determinants of mortality appears to be Killip Class and age of the patient. Fewer women received thrombolysis or underwent PCI on same admission although women make up 25% of the cohort.
Congenital coronary artery anomalies are rare, with an incidence of about 0.06-1.3 percent of all patients undergoing cardiac catheterisation. They are commonly asymptomatic, but potentially serious lesions may lead to myocardial ischaemia, infarction and/or sudden cardiac death. The occurrence of a concomitant stenotic lesion is exceedingly rare. We report an 80-year-old man who presented with acute anterior myocardial infarction. Coronary angiography revealed severe proximal left anterior descending (LAD) and arteriovenous malformation (AVM) from the first septal branch of the LAD. The LAD stenosis and the AVM were successfully treated with two Jomed covered stents.
Coronary arteries vasospasm (CAS) is commonly seen in invasive cardiology laboratory during diagnostic catheterization or coronary intervention. Though the incidence of Printzmetal angina is uncommon, coronary vasospasm resulting in acute myocardial infarct is rare, especially if there is no significant atherosclerotic plaque within the coronary vasculature.
Cardiovascular disease (CVD) is the major cause of death globally. More people die of CVDs each year than from any other disease. Over 80% of CVD deaths occur in low and middle income countries and occur almost equally in male and female. In this paper, different computational models based on Bayesian Networks, Multilayer Perceptron,Radial Basis Function and Logistic Regression methods are presented to predict early risk detection of the cardiovascular event. A total of 929 (626 male and 303 female) heart attack data are used to construct the models.The models are tested using combined as well as separate male and female data. Among the models used, it is found that the Multilayer Perceptron model yields the best accuracy result.
This paper aims at identifying the factors that would help to diagnose acute myocardial infarction (AMI) using data from an electronic medical record system (EMR) and then generating structure decisions in the form of linguistic fuzzy rules to help predict and understand the outcome of the diagnosis. Since there is a tradeoff in the fuzzy system between the accuracy which measures the capability of the system to predict the diagnosis of AMI and transparency which reflects its ability to describe the symptoms-diagnosis relation in an understandable way, the proposed fuzzy rules are designed in a such a way to find an appropriate balance between these two conflicting modeling objectives using multi-objective genetic algorithms. The main advantage of the generated linguistic fuzzy rules is their ability to describe the relation between the symptoms and the outcome of the diagnosis in an understandable way, close to human thinking and this feature may help doctors to understand the decision process of the fuzzy rules.
Risk stratification in ST-elevation myocardial infarction (STEMI) is important, such that the most resource intensive strategy is used to achieve the greatest clinical benefit. This is essential in developing countries with wide variation in health care facilities, scarce resources and increasing burden of cardiovascular diseases. This study sought to validate the Thrombolysis In Myocardial Infarction (TIMI) risk score for STEMI in a multi-ethnic developing country.
Left atrial volume index (LAVI) is well proven to be a reliable method of determining left atrial size, which has prognostic implications in cardiovascular diseases. Studies demonstrate that increased LAVI is a predictor of mortality in myocardial infarction, but its association with other major adverse cardiovascular events (MACEs) among patients post acute coronary syndrome (ACS) has not been adequately evaluated.
We report a 13-year-old girl diagnosed with systemic lupus erythematosus (SLE) who presented with left-sided chest pain, with ECG changes and elevation troponins that were suggestive of an acute inferior wall myocardial infarction (MI). Her multi-slice computed tomography coronary angiogram and standard angiogram were normal. The cardiac magnetic resonance imaging revealed an area of infarcted myocardium that was in the right coronary artery territory. We believe her MI was most likely secondary to coronary vasospasm. MI is rare and coronary vasospasm is an uncommon cause of MI in children and adolescents with SLE.
The objectives of this study were to determine the incidence of a myocardial infarction "false alarm" and evaluate the efficacy of the initial electrocardiogram and cardiac enzymes in diagnosing myocardial infarction in Malaysia.
This case report describes a case of presumed acute myocardial infarction in a returned traveler who was later diagnosed to have severe malaria. Emergency coronary angiography was normal and subsequent peripheral blood film was positive for Plasmodium falciparum.
A segmental two-parameter empirical deformable model is proposed for evaluating regional motion abnormality of the left ventricle. Short-axis tagged MRI scans were acquired from 10 healthy subjects and 10 postinfarct patients. Two motion parameters, contraction and rotation, were quantified for each cardiac segment by fitting the proposed model using a non-rigid registration algorithm. The accuracy in motion estimation was compared to a global model approach. Motion parameters extracted from patients were correlated to infarct transmurality assessed with delayed-contrast-enhanced MRI. The proposed segmental model allows markedly improved accuracy in regional motion analysis as compared to the global model for both subject groups (1.22-1.40 mm versus 2.31-2.55 mm error). By end-systole, all healthy segments experienced radial displacement by ~25-35% of the epicardial radius, whereas the 3 short-axis planes rotated differently (basal: 3.3°; mid: -1° and apical: -4.6°) to create a twisting motion. While systolic contraction showed clear correspondence to infarct transmurality, rotation was nonspecific to either infarct location or transmurality but could indicate the presence of functional abnormality. Regional contraction and rotation derived using this model could potentially aid in the assessment of severity of regional dysfunction of infarcted myocardium.