Association Between Fasting Hyperglycemia and New-Onset Atrial Fibrillation in Patients With Acute Myocardial Infarction and the Impact on Short- and Long-Term Prognosis

Acute Hyperglycemia-Induced Injury in Myocardial Infarction

Acute hyperglycemia is a transient increase in plasma glucose level (PGL) frequently observed in patients with ST-elevation myocardial infarction (STEMI). The aim of this review is to clarify the molecular mechanisms whereby acute hyperglycemia impacts coronary flow and myocardial perfusion in patients with acute myocardial infarction (AMI) and to discuss the consequent clinical and prognostic implications. We conducted a comprehensive literature review on the molecular causes of myocardial damage driven by acute hyperglycemia in the context of AMI. The negative impact of high PGL on admission recognizes a multifactorial etiology involving endothelial function, oxidative stress, production of leukocyte adhesion molecules, platelet aggregation, and activation of the coagulation cascade. The current evidence suggests that all these pathophysiological mechanisms compromise myocardial perfusion as a whole and not only in the culprit coronary artery. Acute hyperglycemia on admission, regardless of whether or not in the context of a diabetes mellitus history, could be, thus, identified as a predictor of worse myocardial reperfusion and poorer prognosis in patients with AMI. In order to reduce hyperglycemia-related complications, it seems rational to pursue in these patients an adequate and quick control of PGL, despite the best pharmacological treatment for acute hyperglycemia still remaining a matter of debate.

Association of stress hyperglycemia ratio with in-hospital new-onset atrial fibrillation and long-term outcomes in patients with acute myocardial infarction

AIMS

To investigate the predictive value and prognostic impact of stress hyperglycemia ratio (SHR) for new-onset atrial fibrillation (NOAF) complicating acute myocardial infarction (AMI).

MATERIALS AND METHODS

This retrospective study included 2145 AMI patients without AF history between February 2014 and March 2018. SHR was calculated using fasting blood glucose (mmol/L)/[1.59*HbA1c (%)-2.59]. The association between SHR and post-MI NOAF was assessed with multivariable logistic regression analyses. The primary outcome was a composite of cardiac death, heart failure hospitalisation, recurrent MI, and ischaemic stroke (MACE). Cox regression-adjusted hazard ratios with 95% confidence intervals (CI) were estimated for MACE.

RESULTS

A total of 245 (11.4%) patients developed NOAF. In the multivariable logistic regression analyses, SHR (each 10% increase) was significantly associated with increased risks of NOAF in the whole population (OR: 1.05, 95% CI: 1.01-1.10), particularly in non-diabetic individuals (OR:1.08, 95% CI: 1.01-1.17). During a median follow-up of 2.7 years, 370 (18.5%) MACEs were recorded. The optimal cut-off value of SHR for MACE prediction was 1.119. Patients with both high SHR (≥1.119) and NOAF possessed the highest risk of MACE compared to those with neither high SHR nor NOAF after multivariable adjustment (HR: 2.18, 95% CI: 1.39-3.42), especially for diabetics (HR: 2.63, 95% CI: 1.41-4.91). Similar findings were observed using competing-risk models.

CONCLUSIONS

SHR is an independent predictor of post-MI NOAF in non-diabetic individuals. Diabetic patients with both high SHR and NOAF had the highest risk of MACE, suggesting that therapies targeting SHR may be considered in these patients.

TRIAL REGISTRATION

ClinicalTrials.gov, NCT03533543.

Dysglycemia and arrhythmias

Disorders in glucose metabolism can be divided into three separate but interrelated domains, namely hyperglycemia, hypoglycemia, and glycemic variability. Intensive glycemic control in patients with diabetes might increase the risk of hypoglycemic incidents and glucose fluctuations. These three dysglycemic states occur not only amongst patients with diabetes, but are frequently present in other clinical settings, such as during critically ill. A growing body of evidence has focused on the relationships between these dysglycemic domains with cardiac arrhythmias, including supraventricular arrhythmias (primarily atrial fibrillation), ventricular arrhythmias (malignant ventricular arrhythmias and QT interval prolongation), and bradyarrhythmias (bradycardia and heart block). Different mechanisms by which these dysglycemic states might provoke cardiac arr-hythmias have been identified in experimental studies. A customized glycemic control strategy to minimize the risk of hyperglycemia, hypoglycemia and glucose variability is of the utmost importance in order to mitigate the risk of cardiac arrhythmias.

The Presence of Diabetes Mellitus or Pre-diabetes Mellitus Increases Mortality from Heart Disease in a Taiwanese Population: A 10-year Follow-Up Study

BACKGROUND

We evaluated hyperglycemia-associated mortality in the Taiwanese population by conducting a 10-year retrospective cohort study.

METHODS

From 2007 to 2017, all participants, regardless of their age or underlying diseases, were identified at a Health Screening Center in Taiwan. Overall, 114,534 participants were included in the analysis. They were classified into three subgroups according to glycemia and smoking status by combining survival for data analysis.

RESULTS

The mean follow-up time, age, and body mass index (BMI) were 8.14 ± 2.22 years, 40.95 ± 12.14 years, and 23.24 ± 3.65 kg/m², respectively. The cumulative death rate increased from 0.9% in the normal fasting blood glucose(FBG) subgroup to approximately 6% in the diabetes FBG subgroup. After adjusting for age, gender, BMI, high-density lipoprotein, triglycerides, waist circumference(WC), and smoking status, the hazard ratio (HR) for all-cause, cancer, and heart disease mortality in the diabetes mellitus(DM) subgroup was 1.560, 1.381, and 1.828, respectively.HR was 0.989 in all-cause, 0.940 in cancer, and 1.326 in heart disease in the pre-DM subgroup.

CONCLUSION

Being tested for pre-DM is related to a higher risk of death from heart disease in the Taiwanese population at baseline. Therefore, cardiovascular risk must be actively measured among diabetes patients every visit.

Meta‑analysis of the efficacy and safety of nifekalant in the conversion of atrial fibrillation

Atrial fibrillation (AF) is the most common type of supraventricular tachyarrhythmia. Nifekalant is a new class III antiarrhythmic drug approved for the treatment of ventricular tachyarrhythmias, but its effectiveness in converting AF to sinus rhythm remains unclear. The present analysis aimed to investigate the effect of nifekalant in the conversion of AF. PubMed, Cochrane Library and China National Knowledge Infrastructure databases were systematically used to search relevant studies published between 1999 (data at which the drug was first approved for marketing in Japan) and 2022. Randomized clinical trials, prospective studies and retrospective studies on the use of nifekalant for AF were screened. The study metrics included the success rate of the conversion of AF, the mean time to conversion, the success rate of 12 months after a single AF catheter ablation procedure and the incidence of adverse events. The eligible studies screened included six randomized clinical trials, three prospective studies and three retrospective studies, totalling 12 studies with 1,162 patients. The risk ratio (RR) for successful conversion in the nifekalant and control groups was 1.95 [95% confidence interval (CI), 1.23-3.08; P=0.005] and the mean difference for the mean time to conversion was -1.73 [95% CI, -2.69-(-0.77); P=0.0004]. Statistically significant differences were observed between nifekalant and control groups. Subgroup analysis revealed a statistically significant difference in the success rate of conversion following catheter ablation in the nifekalant group compared with the amiodarone group and the RR value was 1.95 (95% CI, 1.37-2.77; P=0.0002). Statistically significant difference was observed compared with the electrical cardioversion group and the RR value was 0.90 (95% CI, 0.84-0.98; P=0.01). However, the combined RR values for the two groups were 1.18 (95% CI, 0.85-1.65; P<0.0002). The RR value for adverse events was 0.85 (95% CI, 0.51-1.43; P=0.55), with no statistically significant differences between nifekalant and control groups. In conclusion, the results demonstrated that the success rate and time to conversion in the nifekalant group were improved compared with those in the control group, particularly after catheter ablation, and the conversion effect with nifekalant was significantly improved compared with that in the control group.

Implications of new-onset atrial fibrillation on in-hospital and long-term prognosis of patients with acute myocardial infarction: A report from the CBD bank study

BACKGROUND

An increase in the incidence of atrial fibrillation (AF) during the acute phase of myocardial infarction (AMI) has been observed. But it is still unclear whether the implications of new-onset AF on in-hospital and long-term prognosis are of similar magnitude.

METHODS

Using data from the CBD Bank study, 3,824 consecutive AMI patients, without prior AF, were analyzed. During the index hospitalization, all patients were monitored by continuous cardiac monitoring, twice daily performed 12- or 18-lead ECGs and timely ECG checks when cardiac symptoms occurred. Follow-up visits were routinely scheduled after discharge. Primary outcomes were all-cause death and cardiovascular death occurring during hospitalization and long-term follow-up. Secondary outcome was MACEs during hospitalization.

RESULTS

During the median hospital stay of 9.0 (7.0, 11.0) days, new-onset AF was documented in 133 (3.48%) patients; 95 (71.43%) patients had AF attacks within 3 days following AMI. Independent risk factors associated with new-onset AF were older age, larger left atrial diameter, higher level of NT-proBNP, and primary PCI. New-onset AF was found to be significantly associated with in-hospital all-cause death (OR 4.33, 95%CI: 2.37-7.89, P < 0.001), cardiovascular death (OR 4.10, 95%CI: 2.18-7.73, P < 0.001), and MACEs (OR 2.51, 95%CI: 1.46-4.33, P = 0.001). A total of 112 new-onset AF and 3,338 non-AF patients were followed up for 1,090 (365, 1,694) days after discharge. There was no significant association between new-onset AF and long-term all-cause death (HR 1.21, 95%CI: 0.77-1.92, P = 0.406) or cardiovascular death (HR 1.09, 95%CI: 0.61-1.97, P = 0.764).

CONCLUSION

New-onset AF following AMI is strongly associated with an increased risk of adverse in-hospital prognosis, but it does not affect prognosis in those who survive until hospital discharge.