Higher long-term visit-to-visit glycemic variability predicts new-onset atrial fibrillation in patients with diabetes mellitus

Clinical prediction study on the risk of atrial fibrillation in hypertensive patients based on metabolism, inflammation, and gender differences

This study aimed to explore the risk factors for atrial fibrillation (AF) within one year after discharge in hypertensive patients and to construct a corresponding predictive model. This single-center, retrospective study included 566 patients admitted with hypertension. Patients were divided into two groups: those who developed AF within one year after discharge and those who did not. Variables were selected for multivariate regression analysis using univariate regression and variance inflation factor (VIF) analysis. Subgroup analysis was performed by gender to explore the predictive value of the variables, and a nomogram was constructed. The total sample was randomly divided into a training set and a validation set (7:3 ratio). The discrimination and calibration of the predictive model were evaluated using receiver operating characteristic (ROC) and calibration curves. Patients who developed AF within one year had significantly higher levels of white blood cells (WBC), neutrophils (NEUT), lymphocytes (LYMPH), creatinine (Scr), fasting blood glucose (FBG), triglycerides (TG), lipoprotein(a) [Lp(a)], glycated hemoglobin (HbA1c), neutrophil-to-lymphocyte ratio (NLR), and triglyceride-glucose (TyG) index compared to those who did not (P < 0.05). Males, smokers, and diabetic patients were more prevalent in the AF group (P < 0.05). Logistic regression analysis showed that male gender, Lp(a), HbA1c, NLR, and the TyG index were independent predictors of AF within one year after discharge in hypertensive patients. The nomogram constructed showed an area under the ROC curve (AUC) of 0.793 in the training set and 0.740 in the validation set. The calibration curves indicated good fit (P = 0.726 in the training set; P = 0.489 in the validation set). Male, Lp(a), HbA1c, NLR, and the TyG index are independent risk factors for AF within one year of discharge in hypertensive patients. The nomogram model constructed has high predictive accuracy. This study suggests that individualized management strategies should be employed based on these risk factors in clinical practice.

Association between hemoglobin glycation index and adverse outcomes in critically ill patients with myocardial infarction: A retrospective cohort study

BACKGROUND AND AIM

The prognosis of critically ill patients with myocardial infarction (MI) is associated with metabolic disturbances. The hemoglobin glycation index (HGI), a marker of glycemic variability, has been linked to adverse outcomes in critically ill populations. This study aimed to explore the relationship between HGI and adverse outcomes in critically ill MI patients.

METHODS AND RESULTS

This retrospective cohort study used data from the MIMIC-IV database, focusing on critically ill MI patients. Linear regression was applied to model the relationship between glucose and HbA1c, from which HGI values were calculated. Patients were grouped into quartiles based on HGI. Primary outcomes included 30-day, 180-day, and 365-day all-cause mortality. Kaplan-Meier survival analysis, logistic regression, Cox proportional hazards models, and restricted cubic spline (RCS) analysis were employed to assess the relationship between HGI and adverse outcomes. A total of 2480 patients were included. Lower HGI was associated with significantly increased risks of 30-day, 180-day, 365-day, and hospital all-cause mortality. RCS analysis revealed an inverse J-shaped relationship between HGI and mortality risk.

CONCLUSIONS

Low HGI in critically ill MI patients is significantly associated with higher all-cause mortality, highlighting its potential as a prognostic marker for early risk stratification and management optimization.

Phenotypes of atrial fibrillation in a Taiwanese longitudinal cohort: Insights from an Asian perspective

Background

Atrial fibrillation (AF) is a condition with heterogeneous underlying causes, often involving multiple cardiovascular comorbidities. Large-scale studies examining the heterogeneity of patients with AF in the Asian population are limited.

Objectives

The purpose of this study was to identify distinct phenotypic clusters of patients with AF and evaluate their associated risks of ischemic stroke, heart failure hospitalization, cardiovascular mortality, and all-cause mortality.

Methods

We analyzed 5002 adult patients with AF from the National Taiwan University Hospital between 2014 and 2019 using an unsupervised hierarchical cluster analysis based on the CHA2DS2-VASc score.

Results

We identified 4 distinct groups of patients with AF: cluster I included diabetic patients with heart failure preserved ejection fraction as well as chronic kidney disease (CKD); cluster II comprised older patients with low body mass index and pulmonary hypertension; cluster III consisted of patients with metabolic syndrome and atherosclerotic disease; and cluster IV comprised patients with left heart dysfunction, including reduced ejection fraction. Differences in the risk of ischemic stroke across clusters (clusters I, II, and III vs cluster IV) were statistically significant (hazard ratio [HR] 1.87, 95% confidence interval [CI] 1.00-3.48; HR 2.06, 95% CI 1.06-4.01; and HR 1.70, 95% CI 1.02-2.01). Cluster II was independently associated with the highest risk of hospitalization for heart failure (HR 1.19, 95% CI 0.79-1.80), cardiovascular mortality (HR 2.51, 95% CI 1.21-5.22), and overall mortality (HR 2.98, 95% CI 1.21-4.2).

Conclusion

A data-driven algorithm can identify distinct clusters with unique phenotypes and varying risks of cardiovascular outcomes in patients with AF, enhancing risk stratification beyond the CHA2DS2-VASc score.

The association of haemoglobin A1c variability with adverse outcomes in patients with atrial fibrillation prescribed anticoagulants

AIMS

The association of haemoglobin A1c (HbA1c) variability with the risk of adverse outcomes in patients with atrial fibrillation (AF) prescribed anticoagulants remains unclear. This study aimed to evaluate the association of HbA1c variability with the risk of ischaemic stroke (IS)/systemic embolism (SE) and all-cause mortality among patients with non-valvular AF prescribed anticoagulants.

METHODS AND RESULTS

Patients newly diagnosed with AF from 2013 to 2018 were included. Variability in HbA1c, indexed by the coefficient of variation (CV), was determined for those with at least three HbA1c measurements available from the time of study enrolment to the end of follow-up. To evaluate whether prevalent diabetes would modify the relationship between HbA1c variability and outcomes, participants were divided into diabetes and non-diabetes groups. The study included 8790 patients (mean age 72.7% and 48.5% female). Over a median follow-up of 5.5 years (interquartile range 5.2, 5.8), the incident rate was 3.74 per 100 person-years for IS/SE and 4.89 for all-cause mortality in the diabetes group. The corresponding incident rates in the non-diabetes group were 2.41 and 2.42 per 100 person-years. In the diabetes group, after adjusting for covariates including mean HbA1c, greater HbA1c variability was significantly associated with increased risk of IS/SE [hazard ratio (HR) = 1.65, 95% confidence interval (CI): 1.27-2.13) and all-cause mortality (HR = 1.24, 95% CI: 1.05-1.47) compared with the lowest CV tertile. A similar pattern was evident in the non-diabetes group (IS/SE: HR = 1.58, 95% CI: 1.23-2.02; all-cause mortality: HR = 1.35, 95% CI: 1.10-1.64).

CONCLUSION

Greater HbA1c variability was independently associated with increased risk of IS/SE and all-cause mortality among patients with AF, regardless of diabetic status.

Role of HbA1c in Mortality Among Patients With a Medical History of Ischemic Stroke and Paroxysmal Atrial Fibrillation: A Systematic Review

Elevated HbA1c, a marker of poor glycemic control, is associated with adverse cardiovascular outcomes and mortality. HbA1c influences outcomes through distinct mechanisms of vascular dysfunction and atherosclerosis in ischemic stroke, during atrial remodeling and thrombus formation in paroxysmal atrial fibrillation (PAF). Optimal HbA1c thresholds are generally below optimal levels, with levels above this being linked to higher mortality in both populations. At extremes of glycemic control in ischemic stroke, patients face recurrence and poor recovery, while PAF patients experience amplified thromboembolic risks. In patients with both conditions, poor HbA1c control synergistically raises mortality. This systematic review explores how HbA1c levels directly contribute to mortality in patients with ischemic stroke and PAF, aiming to establish a causal link between elevated HbA1c and increased mortality risk. This review includes a comprehensive analysis of four cross-sectional studies, five randomized controlled trials (RCTs), and 17 cohort studies, providing a diverse range of evidence on the topic. The inclusion of these study designs offers a well-rounded understanding of the impact and outcomes observed in the research. Mortality metrics include short-term mortality, such as 30-day or 90-day, and long-term mortality over one, three, or five years. Specific metrics, like cardiovascular mortality, focus on deaths from stroke; some studies link mortality to functional decline post-stroke, where complications from immobility or recurrent vascular events contribute to outcomes. Secondary outcomes include survival metrics, functional recovery metrics, and complications. Studies use narrative synthesis due to its ability to accommodate heterogeneity in study designs, populations, and outcome measures, enabling a nuanced interpretation of complex, context-dependent data. HbA1c levels' impact on stroke outcomes, considering age, gender, and severity, is also examined. Confounding factors, functional recovery, and complications are also considered. A narrative synthesis was chosen. The study emphasizes the importance of strict glycemic control in patients with ischemic stroke or PAF, especially those with elevated HbA1c levels. It supports clinical guidelines for individualized HbA1c targets, with most stroke patients having a target of <7%. Clinicians should prioritize close monitoring and tailor treatment plans to avoid extreme HbA1c levels, which could inform more personalized and effective treatment strategies. Tight control of HbA1c levels entails individualized targets based on patient characteristics, with an emphasis on personalized treatment strategies that may include lifestyle modifications, oral hypoglycemics, or insulin therapy to optimize glycemic control.

Effect of body mass index on mortality for diabetic patients with aortic stenosis

BACKGROUND

Several studies suggest an "obesity paradox," associating obesity with better cardiovascular outcomes in patients with type 2 diabetes mellitus (DM) or aortic stenosis (AS) compared to normal or underweight individuals. This study explores the impact of body mass index (BMI) on diabetic patients with AS.

METHODS

Between 2014 and 2019, patients with DM who underwent echocardiography were analyzed. Outcomes included all-cause mortality, cardiovascular, and non-cardiovascular death. Patients were categorized as underweight, normal weight, or obese based on BMI (<18.5, 18.5 to 27, and >27 kg/m2, respectively).

RESULTS

Among 74,835 DM patients, 734 had AS. Normal weight comprised 65.5% (n=481), underweight 4.1% (N=30), and 30.4% were obese. Over a 6-year follow-up, underweight patients had significantly higher all-cause mortality (HR 1.96, 95% CI 1.22 - 3.14, p = 0.005), while obese patients had significantly lower mortality (HR 0.79, 95% CI 0.68 - 0.91, p=0.001) compared to the normal group. Regarding etiologies, underweight patients had a higher risk of non-cardiovascular death (HR 2.47, 95% CI 1.44-4.25, p = 0.001), while obese patients had a lower risk of cardiovascular death (HR 0.66, 95% CI 0.50-0.86, p=0.003). Subgroup analysis showed a consistent trend without significant interaction.

CONCLUSIONS

BMI significantly impacts mortality in DM patients with AS. Being underweight is associated with worse non-cardiovascular death, while obesity is linked to improved cardiovascular death outcomes.

ECG abnormality and predictor of new-onset atrial fibrillation in hypertension and diabetes mellitus population: An observational analytic study from cardiovascular outpatient clinic at a National Cardiovascular Center in Indonesia

Background

Population-based studies have also found that diabetes mellitus (DM) and hypertension (HT) are independent risk factors for atrial fibrillation (AF). However, less is known about new-onset atrial fibrillation (NOAF) risk factors and its correlation with DM and HT. The aim of this study was to determine the prevalence and pattern of ECG abnormalities, and the predictor of NOAF in patients with HT and DM.

Methods

This cross-sectional study was conducted at a tertiary hospital from May until December 2021. All medical record data from outpatients who had both diagnoses HT and DM were included in this study. Data from patients with unstable hemodynamics and lack of complete medical record data were excluded. Then, patient history, medical records, ECG, and laboratory information were reviewed.

Results

There were 162 patients included in this study. Arrhythmia was found in 14.2% of the population, with new-onset AF (NOAF) as the most common finding with 8.6% incidence, followed by PVC (3.1%) and PAC (2.5%). Bivariate analysis showed that valvular heart disease, random blood glucose, LVEF, and infection status were associated with a higher incidence of NOA. Model from multivariate logistic regression showed that valvular heart disease and random blood glucose level were independently correlated with NOAF (p = .009).

Conclusion

It can be concluded that random blood glucose level at a certain point and valvular heart disease can be used as a risk predictor of NOAF in the hypertension population with concomitant DM.

Excessive dietary sodium intake augments long-term risk of atrial fibrillation in older adults with hyperglycemia: A community-based prospective cohort study

AIM

Studies investigating the association between sodium intake and new-onset atrial fibrillation (AF) have come to controversial results. This study aimed to assess the effect of excessive sodium intake on new-onset AF in individuals with hyperglycemia.

METHODS

Between April 2007 and November 2011, 2841 community-dwelling individuals aged 60 years and older were recruited from the Shandong area, China. Dietary sodium intake was estimated using 24-hour urine collection within seven consecutive days. Fasting plasma glucose (FPG) and glycated hemoglobin (HbA1c) were assessed. New-onset AF was diagnosed using ICD-10 with codes I48 (I48.0 - I48.9) during follow-up.

RESULTS

The findings were that excessive sodium intake significantly and independently increased the risk of new-onset AF in older adults with hyperglycemia: hazard ratio (HR) 1.525 [95% confidence interval 1.147;2.029] adjusted P = 0.004. The risk of new-onset AF increased by 29.3% (HR 1.293 [1.108;1.509] adjusted P = 0.001) with a one-standard deviation increase in sodium intake. Excessive sodium intake synergistically interacted with hyperglycemia on the increased risk of new-onset AF (HR 1.599 [1.342;1.905] adjusted P < 0.001 for FPG and HR 1.516 [1.271;1.808] adjusted P < 0.001 for HbA1c).

CONCLUSION

Our findings indicate that excessive sodium intake independently enhances the risk of new-onset AF among patients with hyperglycemia. A sodium-restricted diet may perhaps result in a multiplier effect on reducing the risk of new-onset AF.

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.

Glycemic variability and in-hospital death of critically ill patients and the role of ventricular arrhythmias

BACKGROUND

Abnormal glycemic variability is common in the intensive care unit (ICU) and is associated with increased in-hospital mortality and major adverse cardiovascular events, but little is known about whether adverse outcomes are partly mediated by ventricular arrhythmias (VA). We aimed to explore the association between glycemic variability and VA in the ICU and whether VA related to glycemic variability mediate the increased risk of in-hospital death.

METHODS

We extracted all measurements of blood glucose during the ICU stay from The Medical Information Mart for Intensive Care IV (MIMIC-IV) database version 2.0. Glycemic variability was expressed by the coefficient of variation (CV), which was calculated by the ratio of standard deviation (SD) and average blood glucose values. The outcomes included the incidence of VA and in-hospital death. The KHB (Karlson, KB & Holm, A) is a method to analyze the mediation effect for nonlinear models, which was used to decompose the total effect of glycemic variability on in-hospital death into a direct and VA-mediated indirect effect.

RESULTS

Finally, 17,756 ICU patients with a median age of 64 years were enrolled; 47.2% of them were male, 64.0% were white, and 17.8% were admitted to the cardiac ICU. The total incidence of VA and in-hospital death were 10.6% and 12.8%, respectively. In the adjusted logistic model, each unit increase in log-transformed CV was associated with a 21% increased risk of VA (OR 1.21, 95% CI: 1.11-1.31) and a 30% increased risk (OR 1.30, 95% CI: 1.20-1.41) of in-hospital death. A total of 3.85% of the effect of glycemic variability on in-hospital death was related to the increased risk of VA.

CONCLUSION

High glycemic variability was an independent risk factor for in-hospital death in ICU patients, and the effect was caused in part by an increased risk of VA.

Glycemic variability and the risk of atrial fibrillation: a meta-analysis

Background

Glycemic variability (GV) has been associated with vascular complications in patients with diabetes. However, the relationship between GV and risk of atrial fibrillation (AF) remains not fully determined. We therefore conducted a systematic review and meta-analysis to evaluate the above association.

Methods

Medline, Embase, Web of Science, Wanfang, and China National Knowledge Infrastructure were searched for longitudinal follow-up studies comparing the incidence of AF between patients with higher versus lower GV. A random-effects model incorporating the potential heterogeneity was used to pool the results.

Results

Nine cohort studies with 6,877,661 participants were included, and 36,784 (0.53%) participants developed AF during follow-up. Pooled results showed that a high GV was associated with an increased risk of AF (risk ratio [RR]: 1.20, 95% confidence interval [CI]: 1.11 to 1.30, p < 0.001, I² = 20%). Subgroup analyses suggested consistent association between GV and AF in prospective (RR: 1.29, 95% CI: 1.05 to 1.59, p = 0.01) and retrospective studies (RR: 1.18, 95% CI: 1.08 to 1.29, p = 0.002), in diabetic (RR: 1.24, 95% CI: 1.03 to 1.50, p = 0.03) and non-diabetic subjects (RR: 1.13, 95% CI: 1.00 to 1.28, p = 0.05), in studies with short-term (RR: 1.25, 95% CI: 1.11 to 1.40, p < 0.001) and long-term GV (RR: 1.18, 95% CI: 1.05 to 1.34, p = 0.006), and in studies with different quality scores (p for subgroup difference all > 0.05).

Conclusion

A high GV may predict an increased risk of AF in adult population.

Prediabetes as a risk factor for new-onset atrial fibrillation: the propensity-score matching cohort analyzed using the Cox regression model coupled with the random survival forest

BACKGROUND

The glycemic continuum often indicates a gradual decline in insulin sensitivity leading to an increase in glucose levels. Although prediabetes is an established risk factor for both macrovascular and microvascular diseases, whether prediabetes is independently associated with the risk of developing atrial fibrillation (AF), particularly the occurrence time, has not been well studied using a high-quality research design in combination with statistical machine-learning algorithms.

METHODS

Using data available from electronic medical records collected from the National Taiwan University Hospital, a tertiary medical center in Taiwan, we conducted a retrospective cohort study consisting 174,835 adult patients between 2014 and 2019 to investigate the relationship between prediabetes and AF. To render patients with prediabetes as comparable to those with normal glucose test, a propensity-score matching design was used to select the matched pairs of two groups with a 1:1 ratio. The Kaplan-Meier method was used to compare the cumulative risk of AF between prediabetes and normal glucose test using log-rank test. The multivariable Cox regression model was employed to estimate adjusted hazard ratio (HR) for prediabetes versus normal glucose test by stratifying three levels of glycosylated hemoglobin (HbA1c). The machine-learning algorithm using the random survival forest (RSF) method was further used to identify the importance of clinical factors associated with AF in patients with prediabetes.

RESULTS

A sample of 14,309 pairs of patients with prediabetes and normal glucose test result were selected. The incidence of AF was 11.6 cases per 1000 person-years during a median follow-up period of 47.1 months. The Kaplan-Meier analysis revealed that the risk of AF was significantly higher in patients with prediabetes (log-rank p < 0.001). The multivariable Cox regression model indicated that prediabetes was independently associated with a significant increased risk of AF (HR 1.24, 95% confidence interval 1.11-1.39, p < 0.001), particularly for patients with HbA1c above 5.5%. The RSF method identified elevated N-terminal natriuretic peptide and altered left heart structure as the two most important risk factors for AF among patients with prediabetes.

CONCLUSIONS

Our study found that prediabetes is independently associated with a higher risk of AF. Furthermore, alterations in left heart structure make a significant contribution to this elevated risk, and these structural changes may begin during the prediabetes stage.

In-hospital glycemic variability and all-cause mortality among patients hospitalized for acute heart failure

BACKGROUND

High glycemic variability (GV) is a poor prognostic marker in cardiovascular diseases. We aimed to investigate the association of GV with all-cause mortality in patients with acute heart failure (HF).

METHODS

The Korean Acute Heart Failure registry enrolled patients hospitalized for acute HF from 2011 to 2014. Blood glucose levels were measured at the time of admission, during hospitalization, and at discharge. We included those who had 3 or more blood glucose measurements in this study. Patients were divided into two groups based on the coefficient of variation (CoV) as an indicator of GV. Among survivors of the index hospitalization, we investigated all-cause mortality at 1 year after discharge.

RESULTS

The study analyzed 2,617 patients (median age, 72 years; median left-ventricular ejection fraction, 36%; 53% male). During the median follow-up period of 11 months, 583 patients died. Kaplan-Meier curve analysis revealed that high GV (CoV > 21%) was associated with lower cumulative survival (log-rank P < 0.001). Multivariate Cox proportional analysis showed that high GV was associated with an increased risk of 1-year (HR 1.56, 95% CI 1.26-1.92) mortality. High GV significantly increased the risk of 1-year mortality in non-diabetic patients (HR 1.93, 95% CI 1.47-2.54) but not in diabetic patients (HR 1.19, 95% CI 0.86-1.65, P for interaction = 0.021).

CONCLUSIONS

High in-hospital GV before discharge was associated with all-cause mortality within 1 year, especially in non-diabetic patients with acute HF.

Incidence, risk factors and predictors of cardiovascular mortality for aortic stenosis among patients with diabetes mellitus

AIMS

To find the incidence, risk factors and predictors of cardiovascular (CV) mortality for aortic stenosis (AS) in patients with type 2 diabetes mellitus (T2DM).

METHODS

Between 2014 and 2019, 20,979 patients with T2DM who underwent echocardiography were enrolled for analysis. The mean follow-up period was 34 months. Multiple risk factors and outcomes for patients with and without AS were presented.

RESULTS

AS was present in 776 (3.70%) patients. Age, female, chronic kidney disease, hyperlipidemia, and peripheral arterial disease statistically increased risk of AS. The CV mortality (adjusted hazard ratio [aHR] = 1.97; 95% confidence interval [CI] 1.336 - 2.906, p < 0.001) and risk of hospitalization for heart failure (HHF) (aHR = 1.73, 95% CI 1.442-2.082, p < 0.001) were significantly increased in patients with AS, without significant differences in acute myocardial infarction and stroke. Severity of AS, body mass index (<27 kg/m²), hypertension, hyperuricemia, left ventricular dysfunction (ejection fraction < 50%), and hematocrit (<38%) were significantly associated with increased CV mortality and HHF.

CONCLUSIONS

AS was associated with an increased risk of CV mortality and HHF in patients with T2DM.

The complex interplay between diabetes mellitus and atrial fibrillation

INTRODUCTION

: A growing body of evidence suggests that diabetes mellitus (DM) is associated with an increased risk of new-onset atrial fibrillation (AF) and contributes to suboptimal arrhythmia control and poor prognosis in patients with AF. The high prevalence of AF among patients with DM is primarily attributed to common risk factors, shared pathophysiological mechanisms, and associated atrial remodeling and autonomic dysfunction.

AREAS COVERED

: This comprehensive review covers the current data on the role of DM in the development and prognosis of AF. In addition, we review the impact of anti-DM medications on AF prevention and the role of anticoagulation in patients with coexisting DM and AF.

EXPERT OPINION

: DM is independently associated with new-onset AF, and the coexistence of these two conditions contributes to poor outcomes, from reduced quality of life to increased risks of thromboembolic events, heart failure, and mortality. Despite this strong link, the current evidence is insufficient to recommend routine screening for AF in patients with DM. Although some observations exist on preventing AF with anti-DM medications, randomized controlled trials are warranted to explore the proposed benefits of novel anti-DM medicines in reducing the risk of incident AF.

Glycemic control and atrial fibrillation: an intricate relationship, yet under investigation

Atrial fibrillation (AF) and diabetes mellitus (DM) constitute two major closely inter-related chronic cardiovascular disorders whose concurrent prevalence rates are steadily increasing. Although, the pathogenic mechanisms behind the AF and DM comorbidity are still vague, it is now clear that DM precipitates AF occurrence. DM also affects the clinical course of established AF; it is associated with significant increase in the incidence of stroke, AF recurrence, and cardiovascular mortality. The impact of DM on AF management and prognosis has been adequately investigated. However, evidence on the relative impact of glycemic control using glycated hemoglobin levels is scarce. This review assesses up-to-date literature on the association between DM and AF. It also highlights the usefulness of glycated hemoglobin measurement for the prediction of AF and AF-related adverse events. Additionally, this review evaluates current anti-hyperglycemic treatment in the context of AF, and discusses AF-related decision-making in comorbid DM. Finally, it quotes significant remaining questions and sets some future strategies with the potential to effectively deal with this prevalent comorbidity.