In this meeting report, particularly addressing the topic of protection of the cardiovascular system from ischemia/reperfusion injury, highlights are presented that relate to conditioning strategies of the heart with respect to molecular mechanisms and outcome in patients' cohorts, the influence of co-morbidities and medications, as well as the contribution of innate immune reactions in cardioprotection. Moreover, developmental or systems biology approaches bear great potential in systematically uncovering unexpected components involved in ischemia-reperfusion injury or heart regeneration. Based on the characterization of particular platelet integrins, mitochondrial redox-linked proteins, or lipid-diol compounds in cardiovascular diseases, their targeting by newly developed theranostics and technologies opens new avenues for diagnosis and therapy of myocardial infarction to improve the patients' outcome.
Among numerous artificial intelligence approaches, k-Nearest Neighbor algorithms, genetic algorithms, and artificial neural networks are considered as the most common and effective methods in classification problems in numerous studies. In the present study, the results of the implementation of a novel hybrid feature selection-classification model using the above mentioned methods are presented. The purpose is benefitting from the synergies obtained from combining these technologies for the development of classification models. Such a combination creates an opportunity to invest in the strength of each algorithm, and is an approach to make up for their deficiencies. To develop proposed model, with the aim of obtaining the best array of features, first, feature ranking techniques such as the Fisher's discriminant ratio and class separability criteria were used to prioritize features. Second, the obtained results that included arrays of the top-ranked features were used as the initial population of a genetic algorithm to produce optimum arrays of features. Third, using a modified k-Nearest Neighbor method as well as an improved method of backpropagation neural networks, the classification process was advanced based on optimum arrays of the features selected by genetic algorithms. The performance of the proposed model was compared with thirteen well-known classification models based on seven datasets. Furthermore, the statistical analysis was performed using the Friedman test followed by post-hoc tests. The experimental findings indicated that the novel proposed hybrid model resulted in significantly better classification performance compared with all 13 classification methods. Finally, the performance results of the proposed model was benchmarked against the best ones reported as the state-of-the-art classifiers in terms of classification accuracy for the same data sets. The substantial findings of the comprehensive comparative study revealed that performance of the proposed model in terms of classification accuracy is desirable, promising, and competitive to the existing state-of-the-art classification models.
There is a paucity of data on acute myocardial infarction (AMI) in young Asian women and of comparative data among various ethnic groups with respect to risk factor profile and clinical outcomes. We present a comprehensive overview of the clinical characteristics of young Asian women with AMI and a comparative analysis among Chinese, Malay and Indian women in a multi-ethnic Asian country.
INTRODUCTION: Peripartum cardiomyopathy (PPCM) is an uncommon form of congestive heart failure, affecting obstetric patients around the time of delivery. The epidemiology of PPCM is infrequently reported. This study was undertaken to define the prevalence, presentation and outcome of PPCM among women giving birth in a teaching hospital in Malaysia.
METHODS: A retrospective case record analysis was conducted on all patients admitted and diagnosed with PPCM at the University Malaya Medical Centre, Kuala Lumpur, Malaysia, from 1 January 2000 to 31 December 2009. All deliveries were undertaken in the same hospital.
RESULTS: A total of 12 patients were diagnosed with PPCM during the ten-year study period. The prevalence of PPCM was 2.48 in 100,000 (1 in 40,322) live births. Nine women were diagnosed with PPCM within five months of delivery. Three women had twin pregnancies. There was one death in the group (mortality rate 8.3%). The mean left ventricular ejection fraction at the time of diagnosis was 28.9% ± 8.5% (range 15%-40%). Following the index event, left ventricular function normalised in six of the nine patients (66.7%) who underwent subsequent echocardiography one year later. All patients were treated with standard heart failure therapy. Two patients with normalised left ventricular function had subsequent pregnancies - one pregnancy was terminated at seven weeks and the other patient delivered uneventfully at full term.
CONCLUSION: PPCM is uncommon. The outcome in our series was favourable, with 66.7% of patients with PPCM recovering their left ventricular function. The mortality rate was 8.3%.
We report a pulmonary artery (PA) aneurysm associated with severe aortic stenosis and an aortic root dilatation occurring in a 59-year-old woman who presented with dyspnoea and chest pain. PA aneurysms are rare, and there are no definitive guidelines on its management. There are contentious opinions on whether such aneurysms should be managed conservatively or surgically. Our patient had associated aortic stenosis and underwent a successful aortic valve replacement and PA aneurysm repair. This case illustrates that concomitant PA repair with other cardiothoracic surgery can be performed safely, even in patients with moderate surgical risks. We also discuss the natural history, prognosis and management of PA aneurysms.