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Background We studied the characteristics of ST-elevation myocardial infarction (STEMI) patients from a local acute coronary syndrome (ACS) registry in order to find and build an appropriate acute myocardial infarction (AMI) system of care in Jakarta, Indonesia. Methods Data were collected from the Jakarta Acute Coronary Syndrome (JAC) registry 2008-2009, which contained 2103 ACS patients, including 654 acute STEMI patients admitted to the National Cardiovascular Center Harapan Kita, Jakarta, Indonesia. Results The proportion of patients who did not receive reperfusion therapy was 59% in all STEMI patients and the majority of them (52%) came from inter-hospital referral. The time from onset of infarction to hospital admission was more than 12 h in almost 80% cases and 60% had an anterior wall MI. In-hospital mortality was significantly higher in patients who did not receive reperfusion therapy compared with patients receiving acute reperfusion therapy, either with primary percutaneous coronary intervention (PPCI) or fibrinolytic therapy (13.3% vs 5.3% vs 6.2%, p<0.001). ConclusionThe Jakarta Cardiovascular Care Unit Network System was built to improve the care of AMI in Jakarta. This network will harmonise the activities of all hospitals in Jakarta and will provide the best cardiovascular services to the community by giving two reperfusion therapy options (PPCI or pharmaco-invasive strategy) depending on the time needed for the patient to reach the cath-lab.

In clinical practice, Myocardial Blush Grade (MBG) has been used to obtain information about microvascular condition in myocardial infarction by using coronary angiogram. Quantitative Blush Evaluator (QuBE) program was developed for the calculation of myocardial perfusion score. Calculation of QuBE values is often affected by patient motion and become inaccurate. In this paper, we proposed an algorithm to reduce undesired motion in coronary angiogram. This algorithm correct frame motion by shifting each single frame according to the best correlation with the first frame. The effectiveness of this stablizing method achieved by searching scale-invariant feature from each frame of coronary angiogram in order to find the best correlation between two frame. The results showed that MBG categorization based on modified QuBE program exactly match with the original QuBE program. In addition, results also showed that application of stabilization algorithm using SIFT method decreased the deviation by 15% therefore it increased the accuracy of QuBE value calculation. Finally, this new algorithm also decreased the execution time by 71% so the doctor could faster patient diagnosis. In conclusion the new algorithm could enhance the qualitiy of QuBE value calculations in MBG scoring for coronary angiogram. Keyword: coronary angiography, myocardial blush grade, stabilization, scale-invariant feature transform, quantitative blush evaluator.

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