MATERIALS & METHODS: This was a cross-sectional study involving 101 subjects recruited from the National Institute of Forensic Medicine (IPFN) Hospital Kuala Lumpur (HKL) over a period of 15 months, from December 2012 until April 2014. PMCT CS of the coronary arteries was calculated using Agatston-Janowitz score. Histological presence of calcification was observed and the degree of stenosis was calculated using an image analysis technique.
RESULTS: PMCT CS increased with increasing severity of stenosis (p<0.001). PMCT CS showed a positive correlation with the presence of calcification (r=-0.82, p<0.001).
CONCLUSION: Calcium score is strongly associated with coronary artery calcification and the degree of luminal stenosis in post mortem subjects. Thus, PMCT may be useful as a non-invasive tool in diagnosing CAD in the event that an autopsy is not possible.
Methods: Twenty-seven patients with history of anterior myocardial infarction (MI) and baseline left ventricular ejection fraction (LVEF) of less than 35% were recruited into this study. Patients who are eligible for revascularization were grouped into group A (MSCs infusion with concurrent revascularization) or group B (revascularization only) while patients who were not eligible for revascularization were allocated in group C to receive intracoronary MSCs infusion. LV function was measured using echocardiography.
Results: Patients who received MSCs infusion (either with or without revascularization) demonstrated significant LVEF improvements at 3, 6 and 12 months post-infusion when compared to baseline LVEF within its own group. When comparing the groups, the magnitude of change in LVEF from baseline for third visits i.e., 12 months post-infusion was significant for patients who received MSCs infusion plus concurrent revascularization in comparison to patients who only had the revascularization procedure.
Conclusions: MSCs infusion significantly improves LV function in ICM patients. MSCs infusion plus concurrent revascularization procedure worked synergistically to improve cardiac function in patients with severe ICM.
METHODOLOGY: The "Preferred Reporting Items for Systematic Reviews and Meta-Analyses" (PRISMA) guidelines were followed. Six databases were systematically searched using Medical Subject Headings/Index and Entree terms. After a thorough screening, fourteen publications spanning over ten years (2007-2017) were eligible for this systematic review and meta-analysis.
RESULTS: Out of 14 included studies, 12 reported presence of periodontal bacterial DNA in coronary atherosclerotic plaque specimens. Overall, Porphyromonas gingivalis and Aggregatibacter actinomycetemcomitans were the most frequently detected periodontal bacterial species. Meta-analysis revealed that the prevalence of P. gingivalis was significantly higher than A. actinomycetemcomitans in coronary atheromatous plaque samples. Apart from periodontal microbes, DNA from a variety of other microbes e.g. Pseudomonas fluorescens, Streptococcus species, Chlamydia pneumoniae were also recovered from the collected samples.
CONCLUSION: Consistent detection of periodontal bacterial DNA in coronary atheroma suggests their systemic dissemination from periodontal sites. It should further be investigated whether they are merely bystanders or induce any structural changes within coronary arterial walls.
DESIGN AND SETTINGS: This is a retrospective study of all patients who had undergone coronary angioplasty from 2007 to 2009 in 11 hospitals across Malaysia.
METHODS: Data were obtained from the NCVD-PCI Registry, 2007 to 2009. Patients were categorized into 2 groups-young and old, where young was defined as less than 45 years for men and less than 55 years for women and old was defined as more than or equals to 45 years for men and more than or equals to 55 years for women. Patients' baseline characteristics, risk factor profile, extent of coronary disease and outcome on dis.charge, and 30-day and 1-year follow-up were compared between the 2 groups.
RESULTS: We analyzed 10268 patients, and the prevalence of young CAD was 16% (1595 patients). There was a significantly low prevalence of Chinese patients compared to other major ethnic groups. Active smoking (30.2% vs 17.7%) and obesity (20.9% vs 17.3%) were the 2 risk factors more associated with young CAD. There is a preponderance toward single vessel disease in the young CAD group, and they had a favorable clinical outcome in terms of all-cause mortality at discharge (RR 0.49 [CI 0.26-0.94]) and 1-year follow-up (RR 0.47 [CI 0.19-1.15]).
CONCLUSION: We observed distinctive features of young CAD that would serve as a framework in the primary and secondary prevention of the early onset CAD.
METHODS: We first tested ten traditional machine learning algorithms, and then the three-best performing algorithms (three types of SVM) were used in the rest of the study. To improve the performance of these algorithms, a data preprocessing with normalization was carried out. Moreover, a genetic algorithm and particle swarm optimization, coupled with stratified 10-fold cross-validation, were used twice: for optimization of classifier parameters and for parallel selection of features.
RESULTS: The presented approach enhanced the performance of all traditional machine learning algorithms used in this study. We also introduced a new optimization technique called N2Genetic optimizer (a new genetic training). Our experiments demonstrated that N2Genetic-nuSVM provided the accuracy of 93.08% and F1-score of 91.51% when predicting CAD outcomes among the patients included in a well-known Z-Alizadeh Sani dataset. These results are competitive and comparable to the best results in the field.
CONCLUSIONS: We showed that machine-learning techniques optimized by the proposed approach, can lead to highly accurate models intended for both clinical and research use.