Glycosylated hemoglobin and the risk of periprocedural myocardial infarction in non-diabetic patients

Association of serum laboratory parameters with periprocedural myocardial infarction after a primary percutaneous coronary intervention

BACKGROUND

Periprocedural myocardial infarction (PMI) is one of the mortality-related complications of percutaneous coronary intervention (PCI) and significantly affects short- and long-term adverse outcomes and immediate cardiovascular events. Our present study aimed to evaluate the association of preprocedural serum laboratory parameters and PMI in patients who received primary PCI and attempted to provide detailed data on the predictors of PCI-related PMI.

METHODS

A total of 1184 consecutive coronary artery disease (CAD) patients who received primary and elective PCI between July 2015 and June 2017 were included and divided into control group and PMI group. The data of serum laboratory parameters were collected from the electronic database of Meizhou People's Hospital.

RESULTS

The results indicated that preprocedural fasting blood glucose were higher in PMI group compared with the control group (p < .001). Patients with prior hyperlipidemia were more likely to have experienced PCI-related PMI (p = .018) and the preprocedural level of total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), non-HDL-C, apolipoprotein B (Apo B), and LDL-C/high density lipoprotein cholesterol (HDL-C) were significantly enhanced in PMI group (p < .001). Multivariate regression analysis revealed that preprocedural fasting blood glucose > 6.11 mmol/L (p < .001, OR = 1.949, 95% CI: 1.444-2.630) and LDL-C levels ≥130 mg/dL (p = .005, OR = 1.941, 95% CI: 1.217-3.098) independently predicted PCI-related PMI.

CONCLUSION

Our results indicated preprocedural fasting blood glucose >6.11 mmol/L and LDL-C levels ≥130 mg/dL may be useful predictors for PCI-related PMI. The study may provide a detailed data on the predictors of PCI-related PMI.

Periprocedural Myocardial Injury: Pathophysiology, Prognosis, and Prevention

The definition and clinical implications of myocardial infarction occurring in the setting of percutaneous coronary intervention have been the subject of unresolved controversy. The definitions of periprocedural myocardial infarction (PMI) are many and have evolved over recent years. Additionally, the recent advancement of different imaging modalities has provided useful information on a patients' pre-procedural risk of myocardial infarction. Nonetheless, questions on the benefit of different approaches to prevent PMI and their practical implementation remain open. This review aims to address these questions and to provide a current and contemporary perspective.

Glycated hemoglobin level is an independent predictor of major adverse cardiac events after nonfatal acute myocardial infarction in nondiabetic patients: A retrospective observational study

The effect of glycemic control on the prognosis of nondiabetic patients after acute myocardial infarction (AMI) remains uncertain. We investigated whether glycated hemoglobin (HbA1c) is associated with adverse outcomes after AMI in nondiabetic patients. In this observational study, we enrolled nondiabetic patients with AMI in the emergency department of 2 medical centers from January 2011 to September 2014. All patients received primary percutaneous coronary intervention and were divided into 4 groups according to the interquartile range of average HbA1c level (Group I, ≤5.6%; Group II, 5.6%-5.8%; Group III, 5.8%-6.0%; and Group IV, >6.0%). Multivariate logistic analysis was performed to estimate the correlation of HbA1c with major adverse cardiac events (MACEs) after AMI. In total, 267 eligible patients were enrolled; 48 patients (18%) developed MACEs within a median follow-up of 178 days. Univariate analysis showed HbA1c > 6.0%, with a higher risk of MACEs in Group IV than in Group I (odds ratio [OR]: 2.733; 95% confidence interval [CI]: 1.123-6.651 vs OR: 1.511; 95% CI: 0.595-3.835). Multivariate analysis revealed an approximately 3.8 times higher risk of MACEs in Group IV than in Group I (OR: 3.769; 95% CI: 1.30-10.86). The HbA1 level is a significant predictor of MACEs after AMI in nondiabetic patients.

Relationship of non-cardiac biomarkers with periprocedural myocardial injury in patients undergoing percutaneous coronary intervention

percutaneous coronary intervention (PCI) is one of the dominant methods for revascularization in patient with coronary artery disease (CAD), which accompanied with high incidence of periprocedural myocardial injury (PMI) evaluated by postprocedural cardiac biomarker elevation. For the convenience of risk stratification of PMI following PCI, the aim of present review provides a unique opportunity to summarize the relationship of non-cardiac biomarkers with PMI by extensively searching in the MEDLINE to identify all the relevant studies. In conclusion, we found that PCI related PMI might be correlated positively to those non-cardiac biomarkers such as low-density lipoprotein cholesterol (LDL-C), non-high-density lipoprotein cholesterol, total cholesterol, triglyceride, the ratios of LDL-C to high-density lipoprotein cholesterol (HDL-C), the ratios of HDL-C to apolipoprotein A-I, the ratio of eicosapentaenoic acid to arachidonic acid, lectin-like oxidized low-density lipoprotein receptor-1, C-reactive protein, high on-treatment platelet reactivity, platelet-monocyte aggregates, N-term pro-B-type natriuretic peptide, hemoglobin and albuminuria. Inversely, no relationships of PMI with those non-cardiac biomarkers such as mean platelet volume, platelet distribution width, platelet-larger cell ratio, uric acid, eosinophils count and the genetic variant of methylenetetrahydrofolate reductase (MTHFR) 677 C>T polymorphism. Moreover, there were controversial associations between PMI and those non-cardiac biomarkers such as high-density lipoprotein cholesterol, glycosylated hemoglobin, homocysteine and the polymorphism Leu33Pro of platelet glycoprotein IIbIIIa. However, almost all studies failed to provide definite mechanism of its findings, and further reaches are needed to focus on the potential mechanisms of association between non-cardiac biomarkers and PMI related to PCI.