ArticleAnnals of translational medicine2020
Glycemic variability as predictor of contrast-induced nephropathy in diabetic patients with acute myocardial infarction undergoing percutaneous coronary intervention.
Article in Annals of translational medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed, 11 citations in OpenAlex.
- Short-term Glycemic Variability and Its Association With Macrovascular and Microvascular Complications in Patients With Diabetes.Journal of diabetes science and technology · 2024Review
- Protective effect of recombinant human brain natriuretic peptide against contrast-induced nephropathy in elderly acute myocardial infarction patients: A randomized controlled trial.World journal of clinical cases · 2022Article
- The relationship between pre-procedural elevated arterial lactate and contrast-induced nephropathy following primary percutaneous coronary intervention.Journal of thoracic disease · 2021Article
- Novel nanoliposomes alleviate contrast-induced acute kidney injury in New Zealand rabbits by mediating inflammatory response.Annals of translational medicine · 2021Article
- Glycaemic variability and risk of adverse cardiovascular events in acute coronary syndrome.Diabetes & vascular disease researchReview
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Authors and funding
5 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundContrast-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.
methodsThe 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.
resultsA 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.
conclusionsIn diabetic AMI patients undergoing PCI, high GV is associated with increased risk of CIN.
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