Manoefris Kasim, Geoffrey M Currie, Markus Tjahjono, Bambang B Siswanto, Ganesja M Harimurti, Hosen Kiat
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All had adenosine stress MPI. The end point was a major adverse cardiac event (MACE) defined as cardiac death or nonfatal myocardial infarction (MI).</p><p><strong>Results: </strong>Inclusion and exclusion criteria were satisfied by 300 patients with a mean follow-up of 26.7 ± 8.8 months. The incidence of MACEs was 18.3% among diabetic patients, versus 9% in the non-diabetic population (p < 0.001). A multivariable Cox proportional hazard model demonstratedin dependent predictors for a MACE as abnormal MPI [HR: 9.30 (3.01 - 28.72), p < 0.001], post stress left ventricular ejection fraction (LVEF) ≤30% [HR:2.72 (1.21 - 6.15), p = 0.016] and the patients diabetic status [HR:2.28 (1.04 - 5.01), p = 0.04]. The Kaplan Meier event free survival curve constructed for the different subgroups based on the patients' diabetic status and MPI findings demonstrated that diabetic patients with an abnormal MPI had the worst event free survival (log rank p value < 0.001).</p><p><strong>Conclusions: </strong>In an Indonesian population with suspected or known CAD abnormal adenosine stress MPI is an independent and potent predictor for adverse cardiovascular events and provides incremental prognostic value in cardiovascular risk stratification of patients with diabetes.</p>","PeriodicalId":504447,"journal":{"name":"The Open Cardiovascular Medicine Journal","volume":" ","pages":"82-9"},"PeriodicalIF":0.0000,"publicationDate":"2013-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/a0/b8/TOCMJ-7-82.PMC3795403.pdf","citationCount":"9","resultStr":"{\"title\":\"Myocardial Perfusion SPECT Utility in Predicting Cardiovascular Events Among Indonesian Diabetic Patients.\",\"authors\":\"Manoefris Kasim, Geoffrey M Currie, Markus Tjahjono, Bambang B Siswanto, Ganesja M Harimurti, Hosen Kiat\",\"doi\":\"10.2174/1874192401307010082\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>Indonesia has the fourth largest number of diabetes patients after India, China and the USA. Coronary artery disease (CAD) is the most common cause of death in diabetic patients. Early detection and risk stratification is important for optimal management. Abnormal myocardial perfusion imaging (MPI) is an early manifestation in the ischemic cascade. Previous studies have demonstrated the use of MPI to accurately diagnose obstructive CAD and predict adverse cardiac events. This study evaluated whether MPI predicts adverse cardiac event in an Indonesian diabetic population.</p><p><strong>Method: </strong>The study was undertaken in a consecutive cohort of patients with suspected or known CAD fulfilling entry criteria. All had adenosine stress MPI. The end point was a major adverse cardiac event (MACE) defined as cardiac death or nonfatal myocardial infarction (MI).</p><p><strong>Results: </strong>Inclusion and exclusion criteria were satisfied by 300 patients with a mean follow-up of 26.7 ± 8.8 months. The incidence of MACEs was 18.3% among diabetic patients, versus 9% in the non-diabetic population (p < 0.001). A multivariable Cox proportional hazard model demonstratedin dependent predictors for a MACE as abnormal MPI [HR: 9.30 (3.01 - 28.72), p < 0.001], post stress left ventricular ejection fraction (LVEF) ≤30% [HR:2.72 (1.21 - 6.15), p = 0.016] and the patients diabetic status [HR:2.28 (1.04 - 5.01), p = 0.04]. The Kaplan Meier event free survival curve constructed for the different subgroups based on the patients' diabetic status and MPI findings demonstrated that diabetic patients with an abnormal MPI had the worst event free survival (log rank p value < 0.001).</p><p><strong>Conclusions: </strong>In an Indonesian population with suspected or known CAD abnormal adenosine stress MPI is an independent and potent predictor for adverse cardiovascular events and provides incremental prognostic value in cardiovascular risk stratification of patients with diabetes.</p>\",\"PeriodicalId\":504447,\"journal\":{\"name\":\"The Open Cardiovascular Medicine Journal\",\"volume\":\" \",\"pages\":\"82-9\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-09-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/a0/b8/TOCMJ-7-82.PMC3795403.pdf\",\"citationCount\":\"9\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"The Open Cardiovascular Medicine Journal\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2174/1874192401307010082\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2013/1/1 0:00:00\",\"PubModel\":\"eCollection\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"The Open Cardiovascular Medicine Journal","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2174/1874192401307010082","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2013/1/1 0:00:00","PubModel":"eCollection","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 9
摘要
背景:印度尼西亚是继印度、中国和美国之后的第四大糖尿病患者。冠状动脉疾病(CAD)是糖尿病患者最常见的死因。早期发现和风险分层对优化管理至关重要。心肌灌注显像异常(MPI)是缺血级联的早期表现。先前的研究已经证明MPI可以准确诊断阻塞性CAD并预测不良心脏事件。本研究评估MPI是否能预测印尼糖尿病人群的不良心脏事件。方法:该研究是在一组符合入组标准的疑似或已知CAD患者中进行的。所有患者均有腺苷应激性MPI。终点为主要心脏不良事件(MACE),定义为心源性死亡或非致死性心肌梗死(MI)。结果:300例患者均满足纳入和排除标准,平均随访26.7±8.8个月。糖尿病患者的mace发生率为18.3%,非糖尿病人群为9% (p < 0.001)。多变量Cox比例风险模型显示MACE的依赖预测因子为MPI异常[HR: 9.30 (3.01 - 28.72), p < 0.001],应激后左室射血分数(LVEF)≤30% [HR:2.72 (1.21 - 6.15), p = 0.016]和患者糖尿病状态[HR:2.28 (1.04 - 5.01), p = 0.04]。根据患者的糖尿病状态和MPI结果为不同亚组构建的Kaplan Meier无事件生存曲线显示,MPI异常的糖尿病患者无事件生存最差(log rank p值< 0.001)。结论:在印度尼西亚疑似或已知CAD的人群中,异常腺苷应激MPI是不良心血管事件的独立且有效的预测因子,并在糖尿病患者心血管风险分层中提供了增加的预后价值。
Myocardial Perfusion SPECT Utility in Predicting Cardiovascular Events Among Indonesian Diabetic Patients.
Background: Indonesia has the fourth largest number of diabetes patients after India, China and the USA. Coronary artery disease (CAD) is the most common cause of death in diabetic patients. Early detection and risk stratification is important for optimal management. Abnormal myocardial perfusion imaging (MPI) is an early manifestation in the ischemic cascade. Previous studies have demonstrated the use of MPI to accurately diagnose obstructive CAD and predict adverse cardiac events. This study evaluated whether MPI predicts adverse cardiac event in an Indonesian diabetic population.
Method: The study was undertaken in a consecutive cohort of patients with suspected or known CAD fulfilling entry criteria. All had adenosine stress MPI. The end point was a major adverse cardiac event (MACE) defined as cardiac death or nonfatal myocardial infarction (MI).
Results: Inclusion and exclusion criteria were satisfied by 300 patients with a mean follow-up of 26.7 ± 8.8 months. The incidence of MACEs was 18.3% among diabetic patients, versus 9% in the non-diabetic population (p < 0.001). A multivariable Cox proportional hazard model demonstratedin dependent predictors for a MACE as abnormal MPI [HR: 9.30 (3.01 - 28.72), p < 0.001], post stress left ventricular ejection fraction (LVEF) ≤30% [HR:2.72 (1.21 - 6.15), p = 0.016] and the patients diabetic status [HR:2.28 (1.04 - 5.01), p = 0.04]. The Kaplan Meier event free survival curve constructed for the different subgroups based on the patients' diabetic status and MPI findings demonstrated that diabetic patients with an abnormal MPI had the worst event free survival (log rank p value < 0.001).
Conclusions: In an Indonesian population with suspected or known CAD abnormal adenosine stress MPI is an independent and potent predictor for adverse cardiovascular events and provides incremental prognostic value in cardiovascular risk stratification of patients with diabetes.