Glycemic variability as predictor of contrast-induced nephropathy in diabetic patients with acute myocardial infarction undergoing percutaneous coronary intervention
Autor: | Xin Wang, Genshan Ma, Pengfei Zuo, Zhi Zuo, Yongjun Li |
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Rok vydání: | 2020 |
Předmět: |
medicine.medical_specialty
medicine.medical_treatment Contrast-induced nephropathy 030204 cardiovascular system & hematology Nephropathy 03 medical and health sciences 0302 clinical medicine Internal medicine Diabetes mellitus medicine 030212 general & internal medicine Myocardial infarction cardiovascular diseases neoplasms Glycemic business.industry Percutaneous coronary intervention General Medicine medicine.disease female genital diseases and pregnancy complications surgical procedures operative Conventional PCI Cardiology Original Article Complication business |
Zdroj: | Ann Transl Med |
ISSN: | 2305-5839 |
Popis: | Background Contrast-induced nephropathy (CIN) is a frequent complication in patients undergoing percutaneous coronary intervention (PCI). Diabetes mellitus (DM) and acute myocardial infarction (AMI) are associated with an increased risk of CIN. However, it remains unclear whether glycemic variability (GV) has the important prognostic significance of CIN in diabetic patients with AMI undergoing PCI. We conducted this study to investigate the independent prognostic value of the in-hospital GV in diabetic patients who presented with AMI and were treated with PCI. Methods The study group comprised 252 diabetic patients with AMI who underwent PCI and were assigned to CINand non-CIN groups. A continuous glucose monitoring system (CGMS) was used to determine the mean amplitude of glycemic excursion (MAGE), a representative index of GV. Independent risk factors for CIN were determined by multivariate logistic regression analysis (MLRA), and receiver-operating characteristic (ROC) analysis was used to measure the prognostic potential of GV. Results A total of 55 patients had CIN and they showed markedly elevated MAGE compared with the non-CIN group. MLRA revealed that MAGE had potential to independently predict CIN. The area under the ROC curve, optimal cut-point value, sensitivity and specificity for MAGE were 0.739, 2.95, 70.91% and 61.42%, respectively. Conclusions In diabetic AMI patients undergoing PCI, high GV is associated with increased risk of CIN. |
Databáze: | OpenAIRE |
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