Impaired fasting glucose: a risk factor for atrial fibrillation and heart failure

Development and validation of a nomogram model for all-cause mortality risk in patients with chronic heart failure and atrial fibrillation

BACKGROUND

As the global aging process continues to accelerate, heart failure (HF) has become an important cause of increased morbidity and mortality in elderly patients. Chronic atrial fibrillation (AF) is a major risk factor for HF. Patients with HF combined with AF are more difficult to treat and have a worse prognosis. The aim of this study was to explore the risk factors for 1-year mortality in patients with HF combined with AF and to develop a risk prediction assessment model.

METHODS

We recruited hospitalized patients with HF and AF who received standardized care in the Department of Cardiology at Shengjing Hospital of China Medical University from January 2013 to December 2018. The patients were randomly divided into modeling and internal validation groups using a random number generator at a 1:1 ratio. Multivariate Cox regression analysis was used to identify risk factors for all-cause mortality during a one-year follow-up period. Then, a nomogram was constructed based on the weights of each index and validated. Receiver operating characteristic curve, the area under the curve (AUC), decision curve, and calibration curve analyses for survival were used to evaluate the model's predictive and clinical validities and calibration.

RESULTS

We included 3,406 patients who met the eligibility criteria; 1,703 cases each were included in the modeling and internal validation groups. Eight statistically significant predictors were identified: age, sex, New York Heart Association cardiac function class III or IV, a history of myocardial infarction, and the albumin, triglycerides, N-terminal pro-b-type natriuretic peptide, and blood urea nitrogen levels. The AUCs were 0.793 (95% confidence interval: 0.763-0.823) and 0.794 (95% confidence interval: 0.763-0.823) in the modeling and validation cohorts, respectively.

CONCLUSIONS

We present a predictive model for all-cause mortality in patients with coexisting HF and AF comprising eight key factors. This model gives clinicians a simple assessment tool that may improve the clinical management of these patients.

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.

Effects of an Impaired Fasting Glucose on the Left Atrial Strain Evaluated by Speckle Tracking Echocardiography

Background and Objectives: Similar to diabetes, the presence of left ventricular (LV) diastolic function (DD) has been reported in various studies which were conducted with people with a diagnosis of an impaired fasting blood glucose (FBG). This study aimed to examine the effects of the fasting blood glucose (FBG) levels on the left atrial strain (LAS) estimated by two-dimensional echocardiography speckle tracking analyses in patients without known diabetes. Material and Methods: The study included 148 participants (74 female and 74 male) without a history of diabetes mellitus or chronic disease. The patients were divided into two groups as follows: individuals with an FBG < 100 mg/dL and those with an FBG between 100 and 125 mg/dL after at least 8 h of overnight fasting. According to these FBG levels, speckle tracking echocardiography (STE) measures were compared. Results: There was a significant decrease in the LA reservoir (52.3 ± 15 vs. 44.5 ± 10.7; p = 0.001) and conduit strain (36.9 ± 11.7 vs. 28.4 ± 9.7; p = 0.001) in the impaired FBG group. When the STE findings of both ventricles were compared, no significant difference was observed between the groups in right and left ventricular strain imaging. Conclusions: In the earliest stage of LVDD, changes in atrial functional parameters become particularly evident. Echocardiographic analyses of these parameters can help to diagnose and determine the degree of LVDD while the morphological parameters are still normal. The addition of LAS imaging to routine transthoracic echocardiography (TTE) studies in patients with an impaired FBG but without a DM diagnosis may be helpful in demonstrating subclinical LVDD or identifying patients at risk for LVDD in this patient group.

Diabetes, prediabetes, and atrial fibrillation-A population-based cohort study based on national and regional registers

BACKGROUND

Previous studies have shown an increased risk for atrial fibrillation and atrial flutter (AF) in people with type 2 diabetes and prediabetes. It is unclear whether this increase in AF risk is independent of other risk factors for AF.

OBJECTIVE

To investigate the association between diabetes and different prediabetic states, as independent risk factors for the onset of AF.

METHODS

We performed a population-based cohort study in Northern Sweden, including data on fasting plasma glucose, oral glucose tolerance test, major cardiovascular risk factors, medical history, and lifestyle factors. Participants were divided into six groups depending on glycemic status and followed through national registers for AF diagnosis. Cox proportional hazard model was used to assess the association between glycemic status and AF, using normoglycemia as reference.

RESULTS

The cohort consisted of 88,889 participants who underwent a total of 139,661 health examinations. In the model adjusted for age and sex, there was a significant association between glycemic status and development of AF in all groups except the impaired glucose tolerance group, with the strongest association for the group with known diabetes (p-value <0.001). In a model adjusted for sex, age, systolic blood pressure, body mass index, antihypertensive drugs, cholesterol, alcohol, smoking, education level, marital status, and physical activity, there was no significant association between glycemic status and AF.

CONCLUSIONS/INTERPRETATION

The association between glycemic status and AF disappears upon adjustment for potential confounders. Diabetes and prediabetes do not appear to be independent risk factors for AF.

SGLT2 inhibition, circulating metabolites, and atrial fibrillation: a Mendelian randomization study

BACKGROUND

Sodium-glucose cotransporter 2 (SGLT2) inhibitors have shown promise in reducing the risk of atrial fibrillation (AF). However, the results are controversial and the underlying metabolic mechanism remains unclear. Emerging evidence implied that SGLT2 inhibitors have extra beneficial metabolic effects on circulating metabolites beyond glucose control, which might play a role in reducing the risk of AF. Hence, our study aimed to investigate the effect of circulating metabolites mediating SGLT2 inhibition in AF by Mendelian randomization (MR).

METHODS

A two-sample and two-step MR study was conducted to evaluate the association of SGLT2 inhibition with AF and the mediation effects of circulating metabolites linking SGLT2 inhibition with AF. Genetic instruments for SGLT2 inhibition were identified as genetic variants, which were both associated with the expression of SLC5A2 gene and glycated hemoglobin level (HbA1c). Positive control analysis on type 2 diabetes mellitus (T2DM) was conducted to validate the selection of genetic instruments.

RESULTS

Genetically predicted SGLT2 inhibition (per 1 SD decrement in HbA1c) was associated with reduced risk of T2DM (odds ratio [OR] = 0.63 [95% CI 0.45, 0.88], P = 0.006) and AF (0.51 [0.27, 0.97], P = 0.039). Among 168 circulating metabolites, two metabolites were both associated with SGLT2 inhibition and AF. The effect of SGLT2 inhibition on AF through the total concentration of lipoprotein particles (0.88 [0.81, 0.96], P = 0.004) and the concentration of HDL particles (0.89 [0.82, 0.97], P = 0.005), with a mediated proportion of 8.03% (95% CI [1.20%, 14.34%], P = 0.010) and 7.59% ([1.09%, 13.34%], P = 0.011) of the total effect, respectively.

CONCLUSIONS

This study supported the association of SGLT2 inhibition with a reduced risk of AF. The total concentration of lipoprotein particles and particularly the concentration of HDL particles might mediate this association. Further mechanistic and clinical studies research are needed to understand the mediation effects of circulating metabolites especially blood lipids in the association between SGLT2 inhibition and AF.

Risk of atrial fibrillation in individuals with dysglycemia and diabetes

OBJECTIVE

Diabetes is a risk factor for atrial fibrillation (AF), and increases the risk of thromboembolic events in persons with AF. However, the link between the two conditions is not fully elucidated. Few studies have investigated the association of dysglycemia and incident AF. We investigated the risk of incident AF and prognosis according to diabetes status.

RESEARCH DESIGN AND METHODS

The Copenhagen Primary Care Laboratory Database was merged with data on medical prescriptions, in- and outpatient contacts and vital status. The risk of AF according to diabetes status was investigated by use of Cox regression models.

RESULTS

Of 354.807 individuals with a hemoglobin A1c (HbA1c) measurement, 28.541 (8 %) had known diabetes, 13.038 (4 %) had new onset diabetes and 27.754 (8 %) had prediabetes (HbA1c 42-47 mmol/mol). Persons with dysglycemia (HbA1c > 42 mmol/mol) and diabetes were older, more were men, they had lower level of education and were more likely to be living alone. We observed a gradual increase in risk of developing AF from HbA1c levels of 40 to 60 mmol/mol. In adjusted analyses we found a stepwise increase in hazard of AF from normoglycemia over prediabetes to persons with diabetes (no diabetes: 1.00 [ref.]; prediabetes: 1.12 [1.08-1.16]; new-onset diabetes: 1.16 [1.10-1.22]; known diabetes: 1.15 [1.11-1.20]). Persons with known diabetes had a significant higher hazard of stroke, cardiovascular and all-cause mortality.

CONCLUSION

Increasing levels of HbA1c were associated with an increased hazard of developing AF. Persons with new onset of diabetes and those with known diabetes had similar hazard of developing AF, however persons with known diabetes had a significant higher hazard of stroke, cardiovascular- and all-cause mortality.

Diabetes mellitus and atrial fibrillation-from pathophysiology to treatment

Type 2 diabetes mellitus (T2DM) is a leading risk factor for cardiovascular complications around the globe and one of the most common medical conditions. Atrial fibrillation (AF) is the most common supraventricular arrhythmia, with a rapidly increasing prevalence. T2DM has been closely associated with the risk of AF development, identified as an independent risk factor. Regarding cardio-vascular complications, both AF and T2DM have been linked with high mortality. The underlying pathophysiology has not been fully determined yet; however, it is multifactorial, including structural, electrical, and autonomic pathways. Novel therapies include pharmaceutical agents in sodium-glucose cotransporter-2 inhibitors, as well as antiarrhythmic strategies, such as cardioversion and ablation. Of interest, glucose-lowering therapies may affect the prevalence of AF. This review presents the current evidence regarding the connection between the two entities, the pathophysiological pathways that link them, and the therapeutic options that exist.

Prevalence of glucose metabolism disorders and its association with left atrial remodelling before and after catheter ablation in patients with atrial fibrillation

AIMS

To investigate the exact prevalence of glucose metabolism disorders, and their impact on left atrial (LA) remodelling and reversibility in patients with atrial fibrillation (AF).

METHODS AND RESULTS

We examined 204 consecutive patients with AF who underwent their first catheter ablation (CA). Oral glucose tolerance test was used to evaluate glucose metabolism disorders in 157 patients without known diabetes mellitus (DM). Echocardiography was performed before and 6 months after CA. Oral glucose tolerance test identified abnormal glucose metabolism in 86 patients [11 with newly diagnosed DM, 74 with impaired glucose tolerance (IGT) and 1 with impaired fasting glucose (IFG)]. Ultimately, 65.2% of patients had abnormal glucose metabolism. Diabetes mellitus group had the worst LA reservoir strain and LA stiffness (both P < 0.05), while there was no significant difference in baseline LA parameters between normal glucose tolerance (NGT) group and IGT/IFG group. The prevalence of LA reverse remodelling (≥15% decrease in the LA volume index at 6 months after CA) was significantly higher in NGT group compared with IGT/IFG and DM group (64.1 vs. 38.6 vs. 41.5%, P = 0.006). Both DM and IFG/IGT carry a significant risk of lack of LA reverse remodelling independent of baseline LA size and AF recurrence.

CONCLUSION

Approximately 65% of patients with AF who underwent their first CA had abnormal glucose metabolism. Patients with DM had significantly impaired LA function compared with non-DM patients. Impaired glucose tolerance/IFG as well as DM carries significant risk of unfavourable LA reverse remodelling. Our observations may provide valuable information regarding the mechanisms and therapeutic strategies of glucose metabolism-related AF.

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.

Association between serum uric acid levels and atrial fibrillation in different fasting glucose patterns: A case-control study

BACKGROUND

Previous studies have shown both dysglycaemia and hyperuricemia are associated with an increased risk of atrial fibrillation (AF), while the relationship between serum uric acid (SUA) levels and AF in different fasting glucose patterns (FBG) is unclear. Therefore, this study aimed to determine the association between SUA and AF in different FBG patterns.

METHODS

A total of 1840 patients in this case-control study were enrolled, including 920 AF patients and 920 controls. Patients were divided into three groups according to the different FBG patterns: normoglycemic, impaired fasting glucose (IFG), and diabetes mellitus (DM). Multivariate logistic regression models were performed to evaluate the relationship between SUA and AF in different FBG patterns. Pearson correlation analysis was used to explore the correlation between SUA and metabolic factors. Receiver operating characteristic (ROC) curve models indicated the diagnostic efficiency of SUA for diagnosing AF.

RESULTS

SUA was independently associated with AF after adjusting for all confounding factors in different FBG patterns(normoglycemic: OR=1.313, 95% CI:1.120-1.539; IFG: OR=1.386, 95% CI:1.011-1.898; DM: OR=1.505, 95% CI:1.150-1.970). Pearson's correlation analysis suggested that SUA in AF patients was correlated with several different metabolic factors in different FBG patterns (p<0.05). ROC curve analysis showed that SUA in the normoglycemic group combined with CHD and APOB [AUC: 0.906 (95% CI: 0.888-0.923)], in the IFG group combined with CHD and Scr [AUC: 0.863 (95% CI: 0.820-0.907)], in the DM group combined with CHD and SBP [AUC: 0.858 (95% CI: 0.818-0.898)] had the highest AUC for predicting AF.

CONCLUSION

Findings implied a significant association between SUA and AF in different FBG patterns and provide specific models combined with other factors (CHD, APOB, SCr, SBP), which might contribute to the diagnosis of AF.

Construction and Validation of a Model for Predicting Impaired Fasting Glucose Based on More Than 4000 General Population

Purpose

Impaired fasting glucose (IFG) is associated with an increased risk of multiple diseases. Therefore, the early identification and intervention of IFG are particularly significant. Our study aims to construct and validate a clinical and laboratory-based nomogram (CLN) model for predicting IFG risk.

Patients and Methods

This cross-sectional study collected information on health check-up subjects. Risk predictors were screened mainly by the LASSO regression analysis and were applied to construct the CLN model. Furthermore, we showed examples of applications. Then, the accuracy of the CLN model was evaluated by the receiver operating characteristic (ROC) curve, the area under the ROC curve (AUC) values, and the calibration curve of the CLN model in the training set and validation set, respectively. The decision curve analysis (DCA) was used to estimate the level of clinical benefit. Furthermore, the performance of the CLN model was evaluated in the independent validation dataset.

Results

In the model development dataset, 2340 subjects were randomly assigned to the training set (N = 1638) and validation set (N = 702). Six predictors significantly associated with IFG were screened and used in the construction of the CLN model, a subject was randomly selected, and the risk of developing IFG was predicted to be 83.6% by using the CLN model. The AUC values of the CLN model were 0.783 in the training set and 0.789 in the validation set. The calibration curve demonstrated good concordance. DCA showed that the CLN model has good clinical application. We further performed independent validation (N = 1875), showed an AUC of 0.801, with the good agreement and clinical diagnostic value.

Conclusion

We developed and validated the CLN model that could predict the risk of IFG in the general population. It not only facilitates the diagnosis and treatment of IFG but also helps to reduce the medical and economic burdens of IFG-related diseases.

Prediabetes Is Associated With Increased Risk of Heart Failure Among Patients With Atrial Fibrillation

OBJECTIVE

To evaluate the association between prediabetes and heart failure (HF) and the association of HF with changes in glycemic status.

RESEARCH DESIGN AND METHODS

Patients newly diagnosed with atrial fibrillation (AF) between 2015 and 2018 were divided into three groups (normoglycemia, prediabetes, and type 2 diabetes) according to their baseline glycemic status. The primary outcome was incident HF. The Fine and Gray competing risks model was applied, with death defined as the competing event.

RESULTS

Among 17,943 patients with AF (mean age 75.5 years, 47% female), 3,711 (20.7%) had prediabetes, and 10,127 (56.4%) had diabetes at baseline. Over a median follow-up of 4.7 years, HF developed in 518 (14%) patients with normoglycemia, 646 (15.7%) with prediabetes, and 1,795 (17.7%) with diabetes. Prediabetes was associated with an increased risk of HF compared with normoglycemia (subdistribution hazard ratio [SHR] 1.12, 95% CI 1.03-1.22). In patients with prediabetes at baseline, 403 (11.1%) progressed to diabetes, and 311 (8.6%) reversed to normoglycemia at 2 years. Compared with remaining prediabetic, progression to diabetes was associated with an increased risk of HF (SHR 1.50, 95% CI 1.13-1.97), whereas reversion to normoglycemia was associated with a decreased risk (SHR 0.61, 95% CI 0.42-0.94).

CONCLUSIONS

Prediabetes was associated with an increased risk of HF in patients with AF. Compared with patients who remained prediabetic, those who progressed to diabetes at 2 years experienced an increased risk of HF, whereas those who reversed to normoglycemia incurred a lower risk of HF.

Prediabetes and incident heart failure in hypertensive patients: Results from the Swedish Primary Care Cardiovascular Database

BACKGROUNDS AND AIMS

The cardiovascular risk conferred by concomitant prediabetes in hypertension is unclear. We aimed to examine the impact of prediabetes on incident heart failure (HF) and all-cause mortality, and to describe time in therapeutic blood pressure range (TTR) in a hypertensive real-world primary care population.

METHODS AND RESULTS

In this retrospective cohort study, 9628 hypertensive individuals with a fasting plasma glucose (FPG) in 2006-2010 but no diabetes, cardiovascular or renal disease were followed to 2016; median follow-up was 9 years. Prediabetes was defined as FPG 5.6-6.9 mmol/L, and in a secondary analysis as 6.1-6.9 mmol/L. Study outcomes were HF and all-cause mortality. Hazard ratios (HR) were compared for prediabetes with normoglycemia using Cox regression. All blood pressure values from 2001 to the index date (first FPG in 2006-2010) were used to calculate TTR. At baseline, 51.4% had prediabetes. The multivariable-adjusted HR (95% confidence intervals) was 0.86 (0.67-1.09) for HF and 1.06 (0.90-1.26) for all-cause mortality. For FPG defined as 6.1-6.9 mmol/L, the multivariable-adjusted HR were 1.05 (0.80-1.39) and 1.42 (1.19-1.70), respectively. The prediabetic group had a lower TTR (p < 0.05).

CONCLUSIONS

Prediabetes was not independently associated with incident HF in hypertensive patients without diabetes, cardiovascular or renal disease. However, prediabetes was associated with all-cause mortality when defined as FPG 6.1-6.9 mmol/L (but not as 5.6-6.9 mmol/L). TTR was lower in the prediabetic group, suggesting room for improved blood pressure to reduce incident heart failure in prediabetes.

Clinical outcomes of off-pump coronary artery bypass graft in patients with diabetes and non-diabetics: A systematic review and meta-analysis

BACKGROUND AND AIM

Diabetes mellitus is a prevalent risk factor for developing coronary artery disease which worsens the clinical outcomes of patients undergoing coronary artery bypass grafting (CABG). This study aimed to determine the clinical outcomes of patients with diabetes and non-diabetic patients who underwent off-pump CABG surgery.

METHOD

Medline, Scopus, Proquest, Embase, Web of Science, and Google scholar were searched until September 10, 2021. The effect sizes including unstandardized mean difference and odds ratio with 95% confidence interval were calculated using "Metan" package. The Cochran's Q-test and I² statistic were used to assess heterogeneity, a random-effects model was applied to estimate the pooled effect sizes, and meta-regression was used to investigate the factors affecting heterogeneity between studies.

RESULTS

10 studies with 6200 sample sizes were included in the study. In groups with diabetes, Summary odds ratio (SOR) and 95% confidence interval of infection was 2.18 more than non-diabetic groups. Also, odds renal complication was 1.74 more than non-diabetic groups, and the odds cardiovascular complication in groups with diabetes was 1.30 more than non-diabetics. There were no differences in mortality, neurologic, respiratory and surgical complications between groups with diabetes and non-diabetics. Based on meta-regression results, age (Coefficient: 0.942; p = 0.009) had a significant direct relationship and sample size (Coefficient: 0.001; p = 0.009) had an indirect significant relationship with heterogeneity of neurologic outcomes. There was no significant publication bias in our results.

CONCLUSION

Our study revealed that off-pump CABG led to some significant outcomes in patients with diabetes compared to non-diabetics. Renal and infection complications were higher in patients with diabetes but no significant differences were seen in most of other postoperative outcomes between the two groups.

Long-term cardiovascular outcomes of gestational diabetes mellitus: a prospective UK Biobank study

BACKGROUND

Previous studies showed that gestational diabetes mellitus (GDM) can be a risk factor for subsequent atherosclerotic cardiovascular disease. However, there is a paucity of information regarding diverse cardiovascular outcomes in elderly women after GDM. In the current study, we examined whether women with a history of GDM have an increased risk for long-term overall cardiovascular outcomes.

METHODS

Among the UK participants, we included 219,330 women aged 40 to 69 years who reported at least one live birth. The new incidence of diverse cardiovascular outcomes was compared according to GDM history by multivariable Cox proportional hazard models. In addition, causal mediation analysis was performed to examine the contribution of well-known risk factors to observed risk.

RESULTS

After enrollment, 13,094 women (6.0%) developed new overall cardiovascular outcomes. Women with GDM history had an increased risk for overall cardiovascular outcomes [adjusted HR (aHR) 1.36 (95% CI 1.18-1.55)], including coronary artery disease [aHR 1.31 (1.08-1.59)], myocardial infarction [aHR 1.65 (1.27-2.15)], ischemic stroke [aHR 1.68 (1.18-2.39)], peripheral artery disease [aHR 1.69 (1.14-2.51)], heart failure [aHR 1.41 (1.06-1.87)], mitral regurgitation [aHR 2.25 (1.51-3.34)], and atrial fibrillation/flutter [aHR 1.47 (1.18-1.84)], after adjustment for age, race, BMI, smoking, early menopause, hysterectomy, prevalent disease, and medication. In mediation analysis, overt diabetes explained 23%, hypertension explained 11%, and dyslipidemia explained 10% of the association between GDM and overall cardiovascular outcome.

CONCLUSIONS

GDM was associated with more diverse cardiovascular outcomes than previously considered, and conventional risk factors such as diabetes, hypertension, and dyslipidemia partially contributed to this relationship.

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.