Acute coronary syndromes (ACS) remain a leading cause of mortality and morbidity in the Asia-Pacific (APAC) region. International guidelines advocate invasive procedures in all but low-risk ACS patients; however, a high proportion of ACS patients in the APAC region receive solely medical management due to a combination of unique geographical, socioeconomic, and population-specific barriers. The APAC ACS Medical Management Working Group recently convened to discuss the ACS medical management landscape in the APAC region. Local and international ACS guidelines and the global and APAC clinical evidence-base for medical management of ACS were reviewed. Challenges in the provision of optimal care for these patients were identified and broadly categorized into issues related to (1) accessibility/systems of care, (2) risk stratification, (3) education, (4) optimization of pharmacotherapy, and (5) cost/affordability. While ACS guidelines clearly represent a valuable standard of care, the group concluded that these challenges can be best met by establishing cardiac networks and individual hospital models/clinical pathways taking into account local risk factors (including socioeconomic status), affordability and availability of pharmacotherapies/invasive facilities, and the nature of local healthcare systems. Potential solutions central to the optimization of ACS medical management in the APAC region are outlined with specific recommendations.
BACKGROUND:Cardiovascular risk-prediction models are used in clinical practice to identify and treat high-risk populations, and to communicate risk effectively. We assessed the validity and utility of four cardiovascular risk-prediction models in an Asian population of a middle-income country.
METHODS:Data from a national population-based survey of 14,863 participants aged 40 to 65 years, with a follow-up duration of 73,277 person-years was used. The Framingham Risk Score (FRS), SCORE (Systematic COronary Risk Evaluation)-high and -low cardiovascular-risk regions and the World Health Organization/International Society of Hypertension (WHO/ISH) models were assessed. The outcome of interest was 5-year cardiovascular mortality. Discrimination was assessed for all models and calibration for the SCORE models.
RESULTS:Cardiovascular risk factors were highly prevalent; smoking 20%, obesity 32%, hypertension 55%, diabetes mellitus 18% and hypercholesterolemia 34%. The FRS and SCORE models showed good agreement in risk stratification. The FRS, SCORE-high and -low models showed good discrimination for cardiovascular mortality, areas under the ROC curve (AUC) were 0.768, 0.774 and 0.775 respectively. The WHO/ISH model showed poor discrimination, AUC=0.613. Calibration of the SCORE-high model was graphically and statistically acceptable for men (χ(2) goodness-of-fit, p=0.097). The SCORE-low model was statistically acceptable for men (χ(2) goodness-of-fit, p=0.067). Both SCORE-models underestimated risk in women (p<0.001).
CONCLUSIONS:The FRS and SCORE-high models, but not the WHO/ISH model can be used to identify high cardiovascular risk in the Malaysian population. The SCORE-high model predicts risk accurately in men but underestimated it in women.
KEYWORDS:Cardiovascular disease prevention; Mortality; Risk prediction; Risk score; Validation
Clinicians and other stakeholders recognize the need for clinical registries to monitor data in order to improve the outcome and quality of care in the delivery of medical interventions. The establishment of a collaboration across the Asia Pacific Region to inform on variations in patient and procedural characteristics and associated clinical outcomes would enable regional benchmarking of quality.
Interventional cardiologists (ICs) are exposed to X-rays and may be at risk to develop cataract earlier than common senile cataract. Excess risk of posterior subcapsular cataract, known as radiation-induced, was previously observed in samples of ICs from Malaysia, and Latin America. The O'CLOC study (Occupational Cataracts and Lens Opacities in interventional Cardiology) was performed to quantify the risk at the scale of France.
This study is conducted to investigate and compare image quality and radiation dose between prospective ECG-triggered and retrospective ECG-gated coronary CT angiography (CCTA) with the use of single-source CT (SSCT) and dual-source CT (DSCT).
The Malaysian National Cardiovascular Disease Database (NCVD) team presents Percutaneous Coronary Intervention (PCI) Registry report for the year 2007 to 2009. It provides comprehensive information regarding practice and outcome of PCI in Malaysia.
There is no consensus with respect to the use of analgesia during femoral arterial sheath removal after percutaneous coronary intervention (PCI). We performed a randomized controlled trial to assess the impact of intravenous sedation and local anesthesia during femoral sheath removal after PCI on patient comfort and the incidence of vasovagal reactions.
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.