Glycemic variability predicts cardiovascular complications in acute myocardial infarction patients with type 2 diabetes mellitus

International Journal of Cardiology

Volumn 172, Issue 2, 2014, Pages 498-500

  Wang, Xiangfei ^a   Zhao, Xiaolong ^b   Dorje, Tashi ^a   Yan, Hongmei ^a   Qian, Juying ^a   Ge, Junbo ^a  

^a FUDAN UNIVERSITY   (China)

^b FUDAN UNIVERSITY   (China)

Author keywords

Acute myocardial infarction (AMI); Glycemic variability; Major adverse cardiac event

Indexed keywords

ACETYLSALICYLIC ACID; AMINO TERMINAL PRO BRAIN NATRIURETIC PEPTIDE; ANGIOTENSIN 1 RECEPTOR ANTAGONIST; ANTILIPEMIC AGENT; C PEPTIDE; C REACTIVE PROTEIN; CARVEDILOL; DIPEPTIDYL CARBOXYPEPTIDASE INHIBITOR; GLUCOSE; HEMOGLOBIN A1C; INSULIN; SPIRONOLACTONE; TROPONIN T; GLUCOSE BLOOD LEVEL; GLYCOSYLATED HEMOGLOBIN;

ACUTE HEART FAILURE; ACUTE HEART INFARCTION; ADULT; AGED; ANALYTICAL PARAMETERS; BLOOD GLUCOSE MONITORING; CAUSE OF DEATH; CLINICAL ARTICLE; CONTINUOUS GLUCOSE MONITORING SYSTEM; CONTROLLED STUDY; ESTIMATED GLOMERULAR FILTRATION RATE; FEMALE; FOLLOW UP; GLOMERULUS FILTRATION RATE; GLUCOSE BLOOD LEVEL; GLYCEMIC VARIABILITY; HEMOGLOBIN BLOOD LEVEL; HOSPITAL READMISSION; HOSPITALIZATION; HUMAN; INSULIN BLOOD LEVEL; INSULIN RESISTANCE; LETTER; MALE; NON INSULIN DEPENDENT DIABETES MELLITUS; OBSERVATIONAL STUDY; PREDICTION; PRIORITY JOURNAL; PROSPECTIVE STUDY; PROTEIN BLOOD LEVEL; RECEIVER OPERATING CHARACTERISTIC; RECURRENT DISEASE; SENSITIVITY AND SPECIFICITY; TRANSTHORACIC ECHOCARDIOGRAPHY; COMPLICATION; HEART INFARCTION; METABOLISM; MIDDLE AGED; PREDICTIVE VALUE; PROGNOSIS;

AGED; BLOOD GLUCOSE; DIABETES MELLITUS, TYPE 2; FEMALE; HEMOGLOBIN A, GLYCOSYLATED; HUMANS; MALE; MIDDLE AGED; MYOCARDIAL INFARCTION; PREDICTIVE VALUE OF TESTS; PROGNOSIS; PROSPECTIVE STUDIES;

EID: 84900649760     PISSN: 01675273     EISSN: 18741754     Source Type: Journal    
DOI: 10.1016/j.ijcard.2014.01.015     Document Type: Article

References (18)

1. L. Nalysnyk, M. Hernandez-Medina, and G. Krishnarajah Glycaemic variability and complications in patients with diabetes mellitus: evidence from a systematic review of the literature Diabetes Obes Metab 12 2010 288 298
2. S. Eslami, Z. Taherzadeh, and M.J. Schultz et al. Glucose variability measures and their effect on mortality: a systematic review Intensive Care Med 37 2011 583 593
3. P. Deedwania, M. Kosiborod, and E. Barrett et al. Hyperglycemia and acute coronary syndrome: a scientific statement from the American Heart Association Diabetes Committee of the Council on Nutrition, Physical Activity, and Metabolism Circulation 117 2008 1610 1619
4. S.E. Siegelaar, L. Kerr, and S.J. Jacober et al. A decrease in glucose variability does not reduce cardiovascular event rates in type 2 diabetic patients after acute myocardial infarction: a reanalysis of the Heart2d Study Diabetes Care 34 2011 855 857
5. K.J. Lipska, L. Venkitachalam, and K. Gosch et al. Glucose variability and mortality in patients hospitalized with acute myocardial infarction Circ Cardiovasc Qual Outcomes 5 2012 550 557
6. L.G. Mellbin, K. Malmberg, and L. Ryden et al. The relationship between glycaemic variability and cardiovascular complications in patients with acute myocardial infarction and type 2 diabetes: a report from the DIGAMI 2 Trial Eur Heart J 34 2013 374 379
7. R.P. Radermecker, A. Sultan, and C. Piot et al. Continuous glucose monitoring as a tool to identify hyperglycaemia in non-diabetic patients with acute coronary syndromes Diabet Med 26 2009 167 170
8. C.R. Sampaio, D.R. Franco, and D.J. Goldberg et al. Glucose control in acute myocardial infarction: a pilot randomized study controlled by continuous glucose monitoring system comparing the use of insulin glargine with standard of care Diabetes Technol Ther 14 2012 117 124
9. G. Su, S.H. Mi, and H. Tao et al. Impact of admission glycemic variability, glucose, and glycosylated hemoglobin on major adverse cardiac events after acute myocardial infarction Diabetes Care 36 2013 1026 1032
10. Standards of Medical Care in Diabetes - 2012 Diabetes Care 35 Suppl. 1 2012 S11 S63
11. K.A. Eagle, M.J. Lim, and O.H. Dabbous et al. A validated prediction model for all forms of acute coronary syndrome: estimating the risk of 6-month postdischarge death in an international registry JAMA 291 2004 2727 2733
12. A.S. Levey, L.A. Stevens, and C.H. Schmid et al. A new equation to estimate glomerular filtration rate Ann Intern Med 150 2009 604 612
13. T.M. Wallace, J.C. Levy, and D.R. Matthews Use and abuse of HOMA modeling Diabetes Care 27 2004 1487 1495
14. G. Meyfroidt, D.M. Keenan, and X. Wang et al. Dynamic characteristics of blood glucose time series during the course of critical illness: effects of intensive insulin therapy and relative association with mortality Crit Care Med 38 2010 1021 1029
15. R. Brunner, G. Adelsmayr, and H. Herkner et al. Glycemic variability and glucose complexity in critically ill patients: a retrospective analysis of continuous glucose monitoring data Critical Care 16 2012 R175
16. R.J. Heine, L.F. Van Gaal, and D. Johns et al. Exenatide versus insulin glargine in patients with suboptimally controlled type 2 diabetes: a randomized trial Ann Intern Med 143 2005 559 569
17. T. Haak, A. Tiengo, and E. Draeger et al. Lower within-subject variability of fasting blood glucose and reduced weight gain with insulin detemir compared to NPH insulin in patients with type 2 diabetes Diabetes Obes Metab 7 2005 56 64
18. I.A. Meynaar, S. Eslami, and A. Abu-Hanna et al. Blood glucose amplitude variability as predictor for mortality in surgical and medical intensive care unit patients: a multicenter cohort study J Crit Care 27 2012 119 124