Independent Predictors Of Atrial Fibrillation Research Articles

The potentially underestimated influence of atrial fibrillation on NT-proBNP in chest pain

Abstract Introduction/Purpose NT-proBNP is a widely used diagnostic marker in the emergency department (ED). The main objective of the current study was to determine the association of NT-proBNP in patients with chest pain presenting with sinus rhythm (SR) compared to atrial fibrillation (AFib). Hereby, a focus was the evaluation of serum NT-proBNP head-to-head to urinary NT-proBNP. Methods In this study, urinary as well as blood concentrations of NT-proBNP were measured in a total of 601 patients, who presented with acute chest pain in the ED (mean age = 61.1 y, SD = 16.9 y). In the initial ECG 68 patients suffered from AFib and 533 showed SR. The participants were categorized according to their diagnosis into acute coronary syndrome (ACS, AFib n = 28, SR n = 261), acute decompensated heart failure (ADHF, AFib n= 16, SR n = 21), non-ischemic chest pain without congestion (NICP, AFib n = 24, SR n = 96) or chest-wall syndrome (CWS, SR n = 155). Results In the overall study cohort, patients with AFib showed significantly higher concentrations of urinary as well as blood NT-proBNP compared to those in sinus rhythm (each p < 0.001). Additionally, among patients with acute coronary syndrome (ACS), there were significantly increased biomarker concentrations in patients presenting with AFib compared to sinus rhythm (each p < 0.001, AUCblood = 0.801, AUCurine = 0.701), similarly for patients categorized into NICP (each p < 0.001, AUCblood = 0.833, AUCurine = 0.756). The same pattern was observed among the ACS subcategories (each p < 0.001). Regarding ROC analysis, promising predictive values were shown for detection of AFib: STEMI (AUCblood = 0.902, AUCurine = 0.867), NSTEMI (AUCblood = 0.757, AUCurine = 0.696) and UA (AUCblood = 0.821, AUCurine = 0.681). Comparing ROC curves, significant differences were noted in UA (p < 0.001), opposite to STEMI as well as NSTEMI (each p = n. s.). Regarding ADHF, paradoxically higher NT-proBNP concentrations were noted among patients showing sinus rhythms compared to AFib. Furthermore, a multivariate binary regression analysis showed blood NT-proBNP and age as independent predictors of atrial fibrillation (p < 0.05), opposite to urinary NT-proBNP, high-sensitivity troponin T and diabetes (each p = n. s.). Conclusion Urinary and to a larger extent blood NT-proBNP showed significantly higher concentrations in AFib. In conclusion, in ED patients elevated NT-proBNP may potentially be frequently caused by a coexisting AFib. Regarding ADHF patients, the effect of AFib might be consumed by other conditions that have a greater impact on NT-proBNP.

Incidence of atrial fibrillation in patients with renal infarction: A retrospective cohort analysis of the Korean national health insurance registry

BackgroundRegarding the pathophysiology of renal infarction (RI), cardioembolic causes could have large proportion. However, there are notable variations in prevalence of atrial fibrillation (AF) among patients with RI across different studies, ranging from 17 to 65%. The primary objective of this study is to analyze the incidence of AF in patients with RI. MethodsThis nationwide retrospective cohort study enrolled 5200 patients with RI from the Korean National Institute of Health Services database spanning the years 2013 to 2019. The study accessed the AF incidence rate within 12 months in patients without a prior history of AF. Events occurring within 3 months of RI diagnosis were excluded to mitigate cases diagnosed during the initial screening or those with AF diagnoses that were potentially overlooked in the past. ResultsAF occurred in 19.1% of patients with RI over the entire period (median: 2.5 years, interquartile range 1.04–4.25 years). The majority of AF cases (16.1%) occured within the first year, resulting in an overall incidence rate of 7.0 per 100 person-years. Patients with newly developed AF were, on average, older than those who did not develop AF (64.1 vs. 57.3 years, P < 0.001). The independent predictors of AF were identified as age, male sex, higher body mass index, current smoking, ischemic heart disease, and heart failure. ConclusionsPhysicians should consider the implementation of active rhythm monitoring for patients with RI to identify potential occurrence of subclinical AF, even if not initially diagnosed during the initial screening after RI diagnosis.

Left Atrial Enlargement as a Predictor of Atrial Fibrillation in Rheumatic Mitral Valve Disease: An Echocardiography-based Retrospective Cross-sectional Study.

Rheumatic heart disease is a major cause of cardiovascular morbidity and mortality in developing nations and is a leading cause of hospital admission due to cardiac problems in our country. This study will evaluate the association between left atrial size and the occurrence of atrial fibrillation and describe the clinical characteristics along with complications related to Rheumatic Mitral valve disease. A retrospective cross-sectional study was conducted at a tertiary care center from January 2018 to December 2019. Reports of 207 patients admitted to medical and/or surgical wards with echocardiographic diagnosis of rheumatic mitral valve disease with or without atrial fibrillation were reviewed. Data were collected, entered, and analyzed using the Statistical Package for the Social Science version 25.0. Among 207 patients, atrial fibrillation was present in 90 (43.5%) patients. Atrial fibrillation was higher in patients with mixed mitral valvular lesions compared to isolated mitral stenosis or mitral regurgitation. Univariate and multivariate analysis revealed left atrial size [aOR=1.067, 95% CI: 1.023 - 1.113, P= 0.002] and age [aOR = 1.073, 95% CI: 1.042 - 1.105, P<0.001] as an independent predictor of atrial fibrillation. Larger left atrium was an independent predictor of atrial fibrillation. Besides this, atrial fibrillation was associated with increasing age, mixed mitral valvular lesion, and moderately reduced left ventricular ejection fraction, but not associated with gender and mitral stenosis severity. Left atrial clot was significantly higher in patients with atrial fibrillation than in sinus rhythm.

Predictors of atrial fibrillation detection in embolic stroke of undetermined source patients with implantable loop recorder.

Covert atrial fibrillation (AF) is a predominant aetiology of embolic stroke of undetermined source (ESUS). Evidence suggested that AF is more frequently detected by implantable loop recorder (ILR) than by conventional monitoring. However, the predictive factors associated with occult AF detected using ILRs are not well established yet. In this study we aim to investigate the predictors of AF detection in patients with ESUS undergoing an ILR. This observational multi-centre study included consecutive ESUS patients who underwent ILR implantation. The infarcts were divided in deep, cortical infarcts or both. The infarction sites were categorized as anterior and middle cerebral artery, posterior cerebral artery with and without brainstem/cerebellum involvement. Multivariable logistic regression analysis was performed to investigate variables associated with AF detection. Overall, 3,000 patients were initially identified. However, in total, 127 patients who consecutively underwent ILR implantation were included in our analysis. AF was detected in 33 (26%) out of 127 patients. The median follow-up was 411 days. There were no significant differences in clinical characteristics and comorbidities between patients with and without AF detected. AF was detected more often after posterior cerebral artery infarct with brainstem/cerebellum involvement (p < 0.001) whereas less often after infarction in the anterior and middle cerebral artery (p = 0.021). Multivariable regression analysis demonstrated that posterior cerebral artery infarct with brainstem/cerebellum involvement was an independent predictor of AF detection. Our study showed that posterior circulation infarcts with brainstem/cerebellum involvement are associated with AF detection in ESUS patients undergoing ILR. Larger prospective studies are needed to validate our findings.

The significance of two-dimensional speckle-tracking echocardiography of the left atrium in patients with atrial fibrillation.

This article is a review of the literature devoted to the analysis of promising directions for the use of left atrial strain evaluated using speckle-tracking echocardiography to predict atrial fibrillation (AF). Left atrial strain parameters in various phases of the cardiac cycle are independent predictors of AF both in patients with heart failure and in the general population. The addition of left atrial strain parameters to the traditional echocardiographic parameters will make it possible to effectively select patients with AF both for catheter ablation and to identify patients with a high risk of AF recurrence after catheter ablation.

P-wave characteristics as electrocardiographic markers of atrial abnormality in prediction of incident atrial fibrillation – The Malmö Preventive Project

BackgroundP-wave indices reflect atrial abnormalities contributing to atrial fibrillation (AF). We aimed to assess a comprehensive set of P-wave characteristics for prediction of incident AF in a population-based setting. MethodsMalmö Preventative Project (MPP) participants were reexamined in 2002–2006 with electrocardiographic (ECG) and echocardiographic examinations and followed for 5 years. AF-free subjects (n = 983, age 70 ± 5 years, 38% females) with sinus rhythm ECGs were included in the study. ECGs were digitally processed using the Glasgow algorithm. P-wave duration, axis, dispersion, P-terminal force in lead V1 and interatrial block (IAB) were evaluated. ECG risk score combining the morphology, voltage and length of P-wave (MVP score) was calculated. New-onset diagnoses of AF were obtained from nation-wide registers. ResultsDuring follow up, 66 patients (7%) developed AF. After adjustment for age and gender, the independent predictors of AF were abnormal P-wave axis > 75° (HR 1.63 CI95% 1.95–11.03) and MVP score 4 (HR 6.17 CI 95% 1.76–21.64), both correlated with LA area: Person r − 0.146, p < 0.001 and 0.192, p < 0.001 respectively. Advanced IAB (aIAB) with biphasic P-wave morphology in leads III and aVF was the most prevalent variant of aIAB and predicted AF in a univariate model (HR 2.59 CI 95% 1.02–6.58). ConclusionP-wave frontal axis and MVP score are ECG-based AF predictors in the population-based cohort. Our study provides estimates for prevalence and prognostic importance of different variants of aIAB, providing a support to use biphasic P-wave morphology in lead aVF as the basis for aIAB definition.

Ratio of early transmitral inflow velocity to early diastolic strain rate predicts atrial fibrillation following acute myocardial infarction.

The ratio of early transmitral filling velocity to early diastolic strain rate (E/SRe) has been proposed as a new non-invasive measurement of left ventricular filling pressure. We aimed to investigate the ability of E/SRe to predict atrial fibrillation (AF) after ST-elevation myocardial infarction (STEMI). This was a prospective cohort study of patients (n = 369) with STEMI. Patients underwent an echocardiographic examination a median of two days after pPCI. By echocardiography, transmitral early filling velocity (E) was measured by pulsed-wave Doppler, and early diastolic strain rate (SRe) was measured by speckle tracking of the left ventricle. E was indexed to SRe and the early myocardial relaxation velocity (e') to obtain the E/SRe and E/e', respectively. The endpoint was new-onset AF. During follow-up (median 5.6years, IQR: 5.0-6.1years), 23 (6%) of the 369 patients developed AF. In unadjusted analyses, both E/SRe and E/e' were significantly associated with AF [E/SRe: HR = 1.06; (1.03-1.10); p < 0.001, per 10 increase] and [E/e': HR = 1.11 (1.05-1.17); p < 0.001, per 1 increase] and had equal Harrell's C-statistic of 0.71. However, only E/SRe remained an independent predictor after multivariable adjustments for clinical and echocardiographic parameters [E/SRe: HR = 1.06 (1.00-1.11); p = 0.044, per 10 increase]. E/SRe was further significantly associated with AF in patients with E/e' < 14 HR = 1.09 (1.01-1.17); p = 0.030, per 10 increase), also after multivariable adjustments. E/SRe is an independent predictor of AF in STEMI patients, even in subjects with seemingly normal filling pressure.

The importance of active rhythm monitoring in patients with renal infarction: Korean national health insurance registry

Abstract Background/Introduction Several studies reported that approximately 50% of renal infraction (RI) is caused by cardioembolic disease, particularly associated with atrial fibrillation (AF). However, in the Korean national health insurance database (NHIS), from 2013 to 2019, the prevalence of AF in patients with RI was only 15%. So, we aimed to analyze the incidence of newly developed AF in RI patients. Method This nationwide population-based retrospective cohort study included 5,200 patients with RI using the NHIS database from 2002 to 2012. We analyzed the incidence rate of AF during 12 months among the patients without previous history of AF. We selected clinical events after three months of RI diagnosis to exclude cases diagnosed by initial screening or with previously missed diagnosis of AF. The definition of RI, AF, and comorbidities use the ICD-10-CM codes. Result During the total follow-up period (median 2.5 years, interquartile range 1.04-4.25), AF occurred in 19.1% of RI patients (n=993). Most cases (n=837, 16.1%) occurred within a year, and the incidence of AF was 3.965 per 10,000 person-year. Patients with newly developed AF had a higher proportion of older age than those without AF (64.1 vs. 57.3 years, P&amp;lt;0.001). The prevalence of comorbidities, including hypertension (HTN), ischemic heart disease (IHD), and heart failure (HF), was higher in those with AF. The independent predictors of AF were age (adjusted hazard ratio [aHR] 1.05, 95% CI 1.04-1.05, P&amp;lt;0.001), male (aHR 1.26, 95% CI 1.09-1.45, P=0.002), body mass index (BMI) (aHR 1.04, 95% CI 1.02-1.06, P &amp;lt;0.001), current smoker (aHR 1.20, 95% CI 1.03-1.40, P =0.023), IHD (aHR 1.20, 95% CI 1.00-1.45, P =0.050) and HF (aHR 1.70, 95% CI 1.25-2.33, P =0.001). Additionally, the incidence of all-cause death was 14.264 per 10,000 person-year during the follow-up period. Conclusion Even if AF is not diagnosed in the initial screening after diagnosis of RI, the physician should consider active rhythm monitoring to detect subclinical AF for optimal management in these patients. Especially it might be helpful to reduce the burden of recurrent embolic events in those with risk factors, such as older age, male, higher BMI, current smoker, IHD, or HF.Cox regression analysisAtrial fibrillation cumulative incidence

Impact of diabetes mellitus severity, treatment regimen and glycaemic control on atrial fibrillation prevalence. A report from the NOMED-AF prospective cross-sectional observational study

Abstract Introduction Diabetes mellitus (DM) is a well-known risk factor for atrial fibrillation (AF), but the mechanism(s) by which DM affects AF prevalence remains unclear. The pathophysiological background underlying the frequent coexistence of diabetes and AF seems to be multifactorial, involving changes in left atrial size, abnormal proinflammatory mediators and endothelial dysfunction. Purpose This study aims to evaluate the impact of diabetes mellitus severity, expressed as its known duration, antihyperglycemic treatment regimen and glycaemic control reflected by HbA1c level on AF and its silent, asymptomatic form (SAF) prevalence. Methods The cross-sectional NOMED-AF trial schedule comprised multistage, stratified and clustered population sampling with subsequent clinical evaluation and long-term non-invasive AF screening. AF was screened using a telemonitoring vest for a mean of 21.9± 9.1 days. From the representative sample of 3014 participants (mean age 77.5, 49.1% female), 881 participants (mean age 77.6 ± 0.25, 46.4% female) with concomitant DM were involved in the analysis. Results The mean DM duration was 12 ± 0.35 years, but no significant impact of DM timespan on AF and SAF prevalence was observed. There were also no differences in the course of DM treatment pattern (oral medication vs insulin vs both - oral + insulin) among the study population with and without concomitant AF (p=0.106). From the study population 72% (95% CI: 68.7-75.1) received only oral hypoglycaemic medication; 12.9% (95% CI: 10.7-15.5) was taking both oral treatment + insulin injections; and 15.1% (95% CI: 12.7-17.8) were administered with insulin only. Metabolic control reflected by HbA1c levels showed no significant association with AF prevalence (p=0.635; p=0.094). On multivariate analyses, age (Odds Ratio (OR) 1.35, 95%CI: 1.18-1.53, p&amp;lt;0.001), p=0.042), body mass index (BMI; OR 1.043, 95%CI: 1.01-1.08, p=0.027) and LDL&amp;lt;100 mg/dl (OR 0.64, 95%CI: 0.42-0.97, p=0.037) were independent risk factors for AF prevalence, while age (OR 1.45, 95%CI: 1.20-1.75, p&amp;lt;0.001), LDL&amp;lt;100 mg/dl (OR 0.43, 95%CI 0.23-0.82, p=0.011), use of statins (OR 0.51, 95%CI: 0.28-0.94, p=0.031) and HbA1c ≤6.5 (OR 0.46, 95%CI: 0.25-0.85, p=0.013) were associated with silent AF prevalence. Conclusions Diabetes duration, diabetic treatment pattern or metabolic control per se did not significantly impact the prevalence of AF, including silent AF detected by prospective continuous monitoring. Independent predictors of AF were age, BMI and low LDL levels, with statins and HbA1c ≤6.5 being additional independent predictors for SAF.

Abstract 18192: Sleep Apnea and Incident Atrial Fibrillation : Implications for Targeted Screening

Introduction: In younger individuals, the factors contributing to atrial fibrillation (AF) and ischemic stroke are not entirely understood. Despite the frequent coexistence of obstructive sleep apnea (OSA) and AF, current guidelines do not advise routine screening for either condition. Hypothesis: OSA may be an independent predictor of AF in younger adults Methods: We mined electronic health records of patients aged 20-50 Y who have had &gt;=2 visits within Stanford Healthcare System during the period of 2008 to 2022. Our primary endpoint was incident AF. A comprehensive list of risk factors was mined as covariates. Time-varying covariate survival analysis was done to relate the covariates to the primary endpoint. Analysis was performed in R. Results: From a total population of approximately 1.3 million patients aged between 20 and 50 years, we identified 541168 individuals. Among them, 66088 (12.2%) had OSA. During the follow-up, 5060 young adults (67 per 100,000 person-years) developed new AF. In the multivariable adjusted time-varying analysis, apart from previously reported cardiovascular and demographic risk factors, sleep apnea [aHR:1.13 (1.06,1.20)], CKD [aHR:1.91 (1.22,1.44)], cancer [aHR:1.12, (1.04,1.20)], chronic liver disease [aHR:1.13, (1.05,1.21)] were independent risk factors of AF (Fig 1a). Although risk portended by sleep apnea may be slightly lower than some CHADS2VASC factors, sleep apnea is much more prevalent than them, which may support the benefit for screening in this young population (Fig 1b). Conclusions: In a cohort of over half a million adults aged between 20 and 50, sleep apnea significantly and independently predicts incident AF, which may have implications in screening and treatment strategies for younger patients.

Impact of diabetes mellitus severity, treatment regimen and glycaemic control on atrial fibrillation prevalence in the Polish population aged ≥ 65

Diabetes mellitus (DM) is a well-known risk factor for atrial fibrillation (AF), but the mechanism(s) by which DM affects AF prevalence remains unclear. This study aims to evaluate the impact of diabetes mellitus severity (expressed as its known duration), antihyperglycemic treatment regimen and glycaemic control on AF prevalence. From the representative sample of 3014 participants (mean age 77.5, 49.1% female) from the cross-sectional NOMED-AF study, 881 participants (mean age 77.6 ± 0.25, 46.4% female) with concomitant DM were involved in the analysis. AF was screened using a telemonitoring vest for a mean of 21.9 ± 9.1 days. The mean DM duration was 12 ± 0.35 years, but no significant impact of DM timespan on AF prevalence was observed. No differences in the treatment pattern (oral medication vs insulin vs both oral + insulin) among the study population with and without AF were shown (p = 0.106). Metabolic control reflected by HbA1c levels showed no significant association with AF and silent AF prevalence (p = 0.635; p = 0.094). On multivariate analyses, age (Odds Ratio (OR) 1.35, 95%CI: 1.18–1.53, p < 0.001), p = 0.042), body mass index (BMI; OR 1.043, 95%CI: 1.01–1.08, p = 0.027) and LDL < 100 mg/dl (OR 0.64, 95%CI: 0.42–0.97, p = 0.037) were independent risk factors for AF prevalence, while age (OR 1.45, 95%CI: 1.20–1.75, p < 0.001), LDL < 100 mg/dl (OR 0.43, 95%CI 0.23–0.82, p = 0.011), use of statins (OR 0.51, 95%CI: 0.28–0.94, p = 0.031) and HbA1c ≤ 6.5 (OR 0.46, 95%CI: 0.25–0.85, p = 0.013) were associated with silent AF prevalence. Diabetes duration, diabetic treatment pattern or metabolic control per se did not significantly impact the prevalence of AF, including silent AF detected by prospective continuous monitoring. Independent predictors of AF were age, BMI and low LDL levels, with statins and HbA1c ≤ 6.5 being additional independent predictors for silent AF.Trial registration: NCT03243474.

Left atrial area index provides the best prediction of atrial fibrillation in ischemic stroke patients: results from the LAETITIA observational study.

Left atrial (LA) enlargement has been repeatedly shown to be associated with the diagnosis of atrial fibrillation (AF). In clinical practice, several parameters are available to determine LA enlargement: LA diameter index (LADI), LA area index (LAAI), or LA volume index (LAVI). We investigated the predictive power of these individual LA parameters for AF in patients with acute ischemic stroke or transient ischemic attack (TIA). LAETITIA is a retrospective observational study that reflects the clinical reality of acute stroke care in Germany. Consecutive patient cases with acute ischemic cerebrovascular event (CVE) in 2019 and 2020 were identified from the Mannheim stroke database. Predictive power of each LA parameter was determined by the area under the curve (AUC) of receiver operating characteristic curves. A cutoff value was determined. A multiple logistic regression analysis was performed to confirm the strongest LA parameter as an independent predictor of AF in patients with acute ischemic CVE. A total of 1,910 patient cases were included. In all, 82.0% of patients had suffered a stroke and 18.0% had a TIA. Patients presented with a distinct cardiovascular risk profile (reflected by a CHA2DS2-VASc score ≥2 prior to hospital admission in 85.3% of patients) and were moderately affected on admission [median NIHSS score 3 (1; 8)]. In total, 19.5% of patients had pre-existing AF, and 8.0% were newly diagnosed with AF. LAAI had the greatest AUC of 0.748, LADI of 0.706, and LAVI of 0.719 (each p < 0.001 vs. diagonal line; AUC-LAAI vs. AUC-LADI p = 0.030, AUC-LAAI vs. AUC-LAVI p = 0.004). LAAI, increasing NIHSS score on admission, and systolic heart failure were identified as independent predictors of AF in patients with acute ischemic CVE. To achieve a clinically relevant specificity of 70%, a cutoff value of ≥10.3 cm2/m2 was determined for LAAI (sensitivity of 69.8%). LAAI revealed the best prediction of AF in patients with acute ischemic CVE and was confirmed as an independent risk factor. An LAAI cutoff value of 10.3 cm2/m2 could serve as an inclusion criterion for intensified AF screening in patients with embolic stroke of undetermined source in subsequent studies.

Atrial fibrillation during hospitalization for acute st-segment elevation myocardial infarction: prevalence, predictors, therapeutic impact and mortality

Abstract Funding Acknowledgements Type of funding sources: None. Introduction The presence of Atrial Fibrillation (AF) in Acute Myocardial Infarction (AMI) is an important challenge in antiplatelet and anticoagulant therapy and may have an impact on the prognosis of these patients. Purpose To determine the incidence of AF during hospitalization for ST-elevated AMI (STEMI), identify possible predictors of its onset and assess its impact on therapy and mortality. Methods We studied 3254 patients with the diagnosis of STEMI included in a multicenter national registry. We considered 2 groups: patients with AF and patients without AF. Age, gender, cardiovascular and non-cardiovascular history, number of vessels with lesions, number of angioplasties performed, therapy performed at admission and at discharge were recorded. Left ventricular function (LVF), presence of heart failure (HF), the need for invasive mechanical ventilation, mechanical complications, stroke, major hemorrhage, and high-grade atrioventricular block (AVB) were evaluated. In-hospital mortality was compared. Multivariate analysis was performed to identify predictors of AF and to assess the impact of AF on in-hospital mortality. Results The presence of AF was found in 6.1% (197 patients). The patients with AF were older (71±12 vs 62±14 years; p&amp;lt;0.001), higher prevalence of females (34.5% vs 24.4%, p=0.002), of hypertension (72.4% vs 59.6%, p&amp;lt;0.001), valvular disease (3.7% vs 1.1%, p=0.008), HF (5.6% vs 1.8%, p=0.002), stroke (9.6% vs 5.6%, p=0.021) and chronic renal failure (6.2% vs 2.8%, p=0.007). At the time of coronary angiography, there were no differences in the number and type of vessels with lesions. Patients with AF received more therapy at admission and at discharge with vitamin K antagonists (7.7% vs 1.5% and 12.3% vs 2.5%, p&amp;lt;0.001), diuretics (59.4% vs. 24.3% and 51.3% vs 19.3%, p&amp;lt;0.001), aldosterone antagonists (27.0% vs 12.0% and 25.0% vs 11.1% p&amp;lt;0.001), amiodarone (67.9% vs 4.1% and 37.4% vs 1.6%, p&amp;lt;0.001) and digoxin (10.2% vs 0.3% and 2.6% vs 0.3%, p&amp;lt;0 .05). The presence of AF was associated with worse LVF (p&amp;lt;0.001), higher prevalence of HF (46.2% vs 16.2%, p&amp;lt;0.001), need for invasive mechanical ventilation (10.7% vs 3.4 %, p&amp;lt;0.001), mechanical complications (3.65 vs 1.2%, p=0.013), stroke (4.65 vs 0.8%, p&amp;lt;0.001), AVB (12.7% vs 5.4 %, p&amp;lt;0.001) and major bleeding (6.1% vs 1.8%, p&amp;lt;0.001). In-hospital mortality was higher in patients with AF (13.7% vs 4.6%, p&amp;lt;0.001). By multivariate analysis, the presence of AF per se was not an independent predictor of in-hospital mortality. The following were identified as independent predictors of AF: age and history of HF. Conclusion In our population of patients with STEMI, the incidence of AF was 6.1% and is associated with an increase in complications and in-hospital mortality. Age and history of HF were independent predictors of AF.

Echocardiographic Measures of Left Atrial Structure and Function and the Association with Atrial Fibrillation following Acute Coronary Syndrome

Introduction: Acute coronary syndrome (ACS) is associated with an increased risk of developing atrial fibrillation (AF). This arrhythmia is associated with adverse outcomes, making it important to identify high-risk patients. The aim was to evaluate the prognostic value of measures of left atrial (LA) structure and function in AF prediction following ACS. Methods: Three hundred and eighty-one patients who had a percutaneous coronary intervention for ACS were included in the study. Our endpoint was new-onset AF. Results: With a median follow-up time of 5.4 [3.9–6.8] years, 56 patients (14.7%) developed AF. Patients developing AF had significantly (p ≤ 0.05) increased maximal and minimal LA volumes (LAV_max and LAV_min, respectively). LAV_max and LAV_min remained significantly increased in AF patients when indexing to either body surface area (LAV_max/BSA and LAV_min/BSA, respectively), left ventricle length in end diastole (LAV_max/LVLd and LAV_min/LVLd, respectively), or late mitral annular diastolic velocity (LAV_max/a’ and LAV_min/a’, respectively), while LA expansion index (LAEi), LA emptying fraction (LAEF), and peak LA longitudinal strain (PALS) were decreased. In univariable Cox regressions, all LA measures were found to be predictors of AF. After multivariable adjustment for clinical and echocardiographic parameters, all measures reflecting atrial function (LAV_min, LAV_min/BSA, LAV_min/LVLd, LAV_min/a’, LAV_max/a’, LAEF, LAEi, and PALS) (p ≤ 0.05) but no structural measures (LAV_max, LAV_max/BSA, and LAV_max/LVLd) remained significant independent predictors of AF. Conclusion: Echocardiographic measures of LA function are independent predictors of AF following ACS. Evaluation of LA function might improve the prognostic workup, aid in risk stratification for AF, and improve selection for further examinations.

Correlation between epicardial adipose tissue and atrial fibrillation burden in coronary artery bypass graft surgery

Recent studies suggest an association between epicardial adipose tissue (EAT) and atrial fibrillation. The aim of the study is to evaluate the quantitative and qualitative characteristics of EAT in relation to atrial fibrillation burden after coronary artery bypass graft (CABG). This prospective single-centre study included patients undergoing CABG. The patients underwent transthoracic echocardiography and collection of a bioptic sample containing right appendage and EAT during CABG for histological characterization. After surgery, clinical and telemetry data were collected. Fifty-six consecutive patients were enrolled. The mean postsurgical hospitalization was 7.9 ± 3.7 days. Twenty-two patients had at least one episode of atrial fibrillation. In the atrial fibrillation group, there was a bigger atrial volume, a higher degree of diastolic disfunction, a thicker layer of EAT and an older median age in comparison with the group that did not develop it. EAT with a cut-off of 4 mm was a predictor of atrial fibrillation with an odds ratio (OR) of 1.49 (confidence interval (CI) 1.09-2.04), 73% of sensibility and 89% of specificity. From the histological analyses, the patients with atrial fibrillation had a significantly higher percentage of fibrosis. At univariate analysis, atrial volume [OR 1.05, CI 1.01-1.09, P = 0.022], E/A rate (OR 0.04, CI 0.02-0.72 P = 0.29), the percentage of fibrosis (OR 1.12, CI 1.00-1.25, P = 0.045) and age (OR 1.17, CI 1.07-1.28, P = 0.001) were predictors of atrial fibrillation. At multivariate analysis, atrial volume (P = 0.027), fibrosis (P = 0.003) and age (P = 0.039) were independent predictors of atrial fibrillation. Postcardiac surgical atrial fibrillation is frequent. EAT thickness, atrial volume, fibrosis and age are predictors of postcardiac surgical atrial fibrillation.

A new biomarker to predict atrial fibrillation and its adverse events after coronary artery bypass surgery: red blood cell distribution volume.

Recent studies suggest that increased red blood cell distribution width may be associated with increased risk of atrial fibrillation. This study aimed to evaluate the relationship between pre-operative and postoperative erythrocyte distribution volume, postoperative atrial fibrillation and related adverse events in patients undergoing isolated coronary artery bypass surgery. A total of 790 patients (611 males, mean age 58.3 ± 6.2 years) in pre-operative sinus rhythm, who underwent isolated coronary artery bypass grafting with cardiopulmonary bypass at the same centre and by the same surgical team between January 2015 and December 2021, were enrolled retrospectively. Two groups were created, group 1 (n = 183) and group 2 (n = 607), with regard to the occurrence of atrial fibrillation in the early postoperative period or not, respectively. Clinical and demographic data, biochemical and complete blood count parameters, and intra-operative and postoperative data of the patients were recorded. Univariate and subsequent multivariate logistic regression analysis was done to determine significant clinical factors and independent predictors of postoperative atrial fibrillation. Among the patients, 182 (23.2%) developed atrial fibrillation during the 72 hours postoperatively. Pre-operative and postoperative first-, third- and seventh-day red blood cell distribution volume (p = 0.0001), C-reactive protein (p = 0.0001) and erythrocyte sedimentation rate (p = 0.0001) were significantly increased in group 1. Multivariate logistic regression analysis showed elevated pre-operative and postoperative first-, thirdand seventh-day red blood cell distribution volume, erythrocyte sedimentation rate and C-reactive protein as independent predictors of early postoperative atrial fibrillation. Pre-operative and postoperative red blood cell distribution volume was found to be an independent predictor of atrial fibrillation and associated adverse events in the early postoperative period of isolated coronary artery bypass grafting.

Conventional and two-dimensional strain echocardiography in predicting postoperative atrial fibrillation after coronary artery bypass grafting surgery.

Atrial fibrillation (AF) is a common complication after heart surgeries. Advances in imaging technologies and an understanding of the pathophysiology of preoperative left atrial (LA) dysfunction can lead to more definitive potential therapeutic approaches. This study aimed to determine the role of conventional echocardiography and LA two-dimensional (2D) strain echocardiography in assessing LA function and predicting POAF after CABG surgery. All patients with sinus rhythm who underwent CABG surgery were enrolled. All the patients had undergone conventional echocardiography and LA 2D-strain echocardiography 24 hours before surgery. In addition to demographic, clinical, and perioperative features, electrocardiogram (ECG) and Holter monitoring were recorded. Of the 105 patients included, 85 patients (81%) were men with a mean age of 60.26±10.61 years. POAF was seen in 22.9% of patients during hospitalization, and AF duration was 10 hours (median; IQR: 2.0-19.5). AF patients had a higher LA volume index (LAVI) than patients with sinus rhythm (p=0.018). Patients with sinus rhythm had higher rates of LA reservoir (26.97±6.87 VS. 20.46±4.27, p<0.001), LA contractile (14.98±3.68 VS. 12.76±3.72, p =0.012) and LA global strain (24.28±6.57 VS. 17.71±4.11, p<0.001) than AF patients. The results of the multivariate logistic regression showed that LAVI (p=0.014) and LA global strain (p=0.027) were independent predictors of AF detection. Compared to conventional echocardiography, 2D-strain echocardiography is a more effective diagnostic method to predict the possibility of post-CABG AF.

Incidence and predictors of atrial fibrillation in a large cohort of implantable cardiac monitors after cryptogenic stroke

Up to 20% of ischemic strokes are associated with overt atrial fibrillation (AF). In addition, silent AF is detected by an implantable cardiac monitor in one in three cryptogenic strokes. After ischemic stroke, ESC guidelines recommend continuous ECG monitoring for at least 72 hours, and additional ECG monitoring with long-term non-invasive ECG monitors or implanted cardiac monitors (ICMs) in cryptogenic stroke. However, in the CRYSTAL AF trial, 70% of implanted cardiac monitors did not record an AF episode during three years of follow-up. To date, no predictors or scores are available to assist in patient selection prior to ICM. We sought to identify factors associated with AF after cryptogenic stroke in a large cohort of ICM patients. All patients implanted with an ICM for cryptogenic stroke between February 2016 and February 2022 at the University Hospital of Dijon and Besançon were retrospectively included. Clinical, electrocardiographic, imaging, biological and follow-up data were collected. Of the 383 patients included, 98 (25.6%) developed AF during a mean follow-up of 23 months. Kaplan-Meier estimates of AF on ICM were 16% at 1 year, 24% at 2 years and 31% at 3 years of follow-up. Compared to patients in sinus rhythm, AF patients were significantly older, more often had previous hypertension and dyslipidemia. In addition, AF patients had larger left atrial index volumes (LAVI), lower creatinine clearance and higher CRP. After multivariable Cox analysis, age > 69 years (HR (95%CI) 3.79 (1.90–7.58), P < 0.001) and LAVI > 34 mL/m2 (HR (95%CI) 2.97 (1.54–5.72) remained independently associated with AF. In a large ICM cohort, we identified two independent predictors of AF, age > 69yo and LAVI > 34 mL/m2, which are readily available in daily practice. Based on these results, we aim to construct a simple score for the diagnostic efficacy of ICM to be validated in another cohort. This score would improve the diagnostic efficiency of ICM and decrease the number of time-consuming and costly implantations.

Validation of seven risk scores in an independent cohort: the challenge of predicting recurrence after atrial fibrillation ablation

PurposeSeveral predictive scores for atrial fibrillation (AF) recurrence after AF ablation have been developed. We compared the predictive value of seven previously described risk scores ((CHADS2 and CHA2DS2-VASC, HATCH, APPLE, CAAP-AF, BASE-AF2, MB-LATER) for prediction of AF recurrence risk at 12 months after AF ablation in our patient cohort. Further, we aimed to identify additional variables to predict recurrences after AF ablation.MethodsWe used data from our digital AF ablation registry to compare the previously published scores in an independent cohort (n = 883, 50.8% with paroxysmal AF). The scores were chosen based on earlier publications and availability of relevant data.ResultsThe BASE-AF2 (AUC 0.630, p < 0.001), MB-LATER (AUC 0.612, p < 0.001), CAAP-AF (AUC 0.591, p < 0.001), APPLE (AUC 0.591, p < 0.001) and CHA2DS2-VASC (AUC 0.547, p = 0.018) scores had a statistically significant but modest predictive value for 12-month AF recurrence. None of the scores were significantly superior. Other analyzed scores had no predictive value. There was no difference in the predictive value for 12-month recurrence of AF between first procedure vs. redo procedure and RF ablation vs. cryoablation. Unlike other scores, MB-LATER showed better predictive value for paroxysmal vs. persistent AF (AUC 0.632 vs. 0.551, p = 0.038). In the multivariate logistic regression, only age (p = 0.006), number of prior electrical cardioversions (p < 0.001) and early AF recurrence (p < 0.001) were independent predictors of AF recurrence.ConclusionDespite numerous available scores, predicting recurrences after AF ablation remains challenging. New predictors are needed, potentially based on interventions, as well as novel genetic, functional and anatomic parameters.

Morphological changes in the orifices of the left atrial appendage and left atrium in patients with atrial fibrillation.

As an integral part of the left atrium (LA), the left atrial appendage (LAA) plays an important role in atrial fibrillation (AF). However, the relationship between LAA remodeling and AF has not been clearly defined. This retrospective case-control study aimed to assess the morphological and functional features of the LA and the LAA in AF patients using images obtained by computed tomography angiography (CTA). A total of 140 AF patients and 64 patients without AF or other cardiovascular diseases who underwent CTA scans between September 2016 and August 2017 were enrolled in this observational study as the experimental and the control groups, respectively. The major and minor axes, area, and perimeter of the LAA orifice, the LAA depth, and the volume of both the LAA and LA were analyzed. The data of the AF group and the control group were compared. The t-test was used to analyze the normally distributed data, and the Wilcoxon rank-sum test was used for abnormally distributed data. The best critical value of predictors of AF was calculated using receiver operating characteristic (ROC) curve analysis. The correlation of the LAA volume change with the major and minor axes, area, and perimeter of the LAA orifice, and the LAA depth were analyzed using the Pearson correlation coefficient. The LAA orifice's minor axis, LAA volume, and LA volume were significantly greater (P=0.004, P=0.010, and P<0.001, respectively) in patients with AF than in those without AF. The LAA volume [95% confidence interval (CI): 1.01 to 1.30; P=0.038] and LA volume (95% CI: 1.03 to 1.07; P<0.001) were significantly independent predictors of AF. An LAA volume of 8.75 mL had the highest predictive value for AF [area under the curve (AUC), 0.612], with a sensitivity of 76.6% and a specificity of 48.6%. In contrast, an LA volume of 97.15 mL had the highest predictive value for AF (AUC, 0.771), with a sensitivity of 90.6% and a specificity of 53.6%. The change of LAA volume was positively weakly correlated with the area and perimeter of the LAA orifice (r=0.1703 and r=0.1378, respectively). The LAA emptying fraction was negatively correlated with the major axis and the area of the LAA orifice. The major and minor axes, area, and perimeter of the LAA orifice, and LAA depth were significantly greater in female than in male patients (P=0.003, P=0.003, P=0.001, P=0.019, and P<0.001, respectively). The AF patients had a longer minor axis of the LAA orifice than that of the control group, resulting in a more circular LAA orifice. The LAA orifice area and perimeter were positively correlated with LAA volume change. The LAA orifice major and minor axes, area, and perimeter, and the LAA depth of the female patients were significantly greater than those of their male counterparts in AF patients.