Risk Stratification In Atrial Fibrillation Research Articles

Risk stratification of atrial fibrillation and stroke using single nucleotide polymorphism and circulating biomarkers.

Atrial fibrillation (AF) is the most common sustained arrhythmia, and it causes a high rate of complications such as stroke. It is known that AF begins as paroxysmal form and gradually progresses to persistent form, and sometimes it is difficult to identify paroxysmal AF (PAF) before having stroke. The aim of this study is to evaluate the risk of PAF and stroke using genetic analysis and circulating biomarkers. A total of 600 adult subjects were enrolled (300 from PAF and control groups). Peripheral blood was drawn to identify the genetic variation and biomarkers. Ten single nucleotide polymorphisms (SNPs) were analyzed, and circulating cell-free DNA (cfDNA) was measured from plasma. Four microRNAs (miR-99a-5p, miR-192-5p, miR-214-3p, and miR-342-5p) were quantified in serum using quantitative RT-PCR. Genotyping identified 4 single nucleotide polymorphisms (SNPs) that were significantly associated with AF (rs6817105, rs3807989, rs10824026, and rs2106261), and the genetic risk score using 4 SNPs showed the area under the curve (AUC) of 0.631. Circulating miRNAs and cfDNA did not show significant differences between PAF and control groups. The concentration of cfDNA was significantly higher in patients with a history of stroke, and the AUC was 0.950 to estimate the association with stroke. The risk of AF could be assessed by genetic risk score. Furthermore, the risk of stroke might be evaluated by plasma cfDNA level.

Left Atrial Strain and Incident Atrial Fibrillation in Older Adults

Atrial fibrillation (AF) is frequent in older adults and associated with left atrial (LA) dysfunction. LA strain (LAε) and LA strain rate (LASR) may detect subclinical LA disease. We investigated whether reduced LAε and LASR predict new-onset AF in older adults without history of AF or stroke. LAε and LASR were assessed by speckle-tracking echocardiography in 824 participants from the community-based Cardiovascular Abnormalities and Brain Lesions study. Positive longitudinal LAε and LASR during ventricular systole, LASR during early ventricular diastole, and LASR during LA contraction were measured. Cause-specific hazards regression modelevaluated the association of LAε and LASR with incident AF, adjusting for pertinent covariates. The mean age was 71.1 ± 9.2 years (313 men, 511 women). During a mean follow-up of 10.9years, new-onset AF occurred in 105 participants (12.7%). Lower LAε and LASR at baseline were observed in patients with new-onset AF (all p <0.01). In multivariable analysis, positive longitudinal LAε (adjusted hazard ratio [HR] per SD decrease 2.05, confidence interval [CI] 1.24 to 3.36) and LASR during LA contraction (HR per SD increase 2.24, CI 1.37 to 3.65) remained associated with new-onset AF, independently of LA volumes and left ventricular function. Along with positive longitudinal LAε, reduced LASR during ventricular systole predicted AF in participants with LA volume below the median value (HR 2.54, CI 1.10 to 6.09), whereas reduced LASR during LA contraction predicted AF in participants with larger LA (HR 2.35, CI 1.31 to 4.23). In conclusion, reduced positive longitudinal LAε and LASR predict new-onset AF in older adults regardless of LA size and may improve AF risk stratification.

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.

Relationship between left atrial myopathy and atrial fibrillation in adults with coarctation of aorta

BackgroundAlthough patients with coarctation of aorta (COA) have clinical risk factors for atrial fibrillation (AF), there are limited data about AF prevalence, and role of left atrial (LA) indices for risk stratification in this population. We hypothesized that LA indices (LA reservoir strain and LA volume index) were associated with AF, and would identify patients at risk for AF progression. MethodsWe analyzed electrocardiograms/Holters, and echocardiograms of adult COA patients at Mayo Clinic (2000–2018). ResultsOf 776 patients, 726(94 %), 46(5.9 %) and 4(0.5 %) had no history of AF, paroxysmal AF, and persistent AF respectively; yielding AF prevalence of 6.4 %. LA reservoir strain (AUC 0.782 [0.751–0.808]) had more robust association with AF as compared to LA volume index (AUC difference −0.115, p < 0.001).Among 726 patients without prior AF, 25(3.4 %) had new-onset AF during follow-up. LA reservoir strain <25 % and LA volume index >34 ml/m2 were independent predictors of new-onset AF (HR 1.81 [1.15–3.85], and HR 1.41 [1.03–4.78], respectively). Of 46 patients with paroxysmal AF, 22(48 %) had recurrent AF, and LA reservoir strain <25 % was an independent predictor of recurrent AF (HR 1.94 [1.41–4.17]). LV pressure overload and stiffness indices were associated with progressive LA dysfunction and new-onset AF. ConclusionsCollectively, these data suggest that LA strain can potentially be used for AF risk stratification. Further studies are required to determine whether LA strain can proactively identify patients that will respond favorably to different antiarrhythmic therapies, and whether interventions to reduce LV pressure overload will improve LA function and reduce AF progression.

Predictive value of systemic inflammatory indicators in atrial fibrillation risk stratification after coronary artery bypass grafting

Predictive value of systemic inflammatory indicators in atrial fibrillation risk stratification after coronary artery bypass grafting

Peak atrial longitudinal strain represents atrial fibrillation burden in daily practice: clinical implication of routine left atrial strain measurements.

Usefulness of left atrial (LA) strain measurements using speckle tracking echocardiography has been reported in various clinical settings. However, clinical implication of routine LA strain measurements in daily practice remains unclear. The purpose of this study was to evaluate clinical utility of routine LA strain measurements in daily practice. From January 6, 2020 to December 28, 2021, 338 consecutive patients underwent echocardiography in Takagi Cardiology Clinic, and all comers were enrolled to the study. Echocardiographic measurements including peak atrial longitudinal strain (PALS) measurement using speckle tracking echocardiography were attempted in all patients. PALS was obtained in 335 patients (age 71 ± 16years, male 43%, hypertensive 74%), and mean value was 22.3 ± 11.5%. PALS was progressively impaired with worsening atrial fibrillation (AF) burden. PALS in patients without AF, in patients with history of AF (paroxysmal AF &/or ablation therapy), and in patients with AF onsite were 26.8 ± 9.8%, 20.3 ± 7.9%, and 8.1 ± 3.3%, respectively (anova p < 0.0001). In patients without history of AF at the time of echocardiography, using cut-off value of 15.0% (i.e., mean + 2SD of PALS in AF patients), Kaplan-Meier analysis revealed that impaired PALS was associated with increased new-onset AF during follow-up period (log-rank p < 0.0001). In daily practice, PALS represents AF burden. Furthermore, impaired PALS is associated with increased new-onset AF. Therefore, routine LA strain measurements using speckle tracking echocardiography will be useful in risk stratification of AF in daily practice.

Low lipoprotein(a) concentration is associated with atrial fibrillation: a large retrospective cohort study

Background and aimsThe role of serum lipoprotein(a) [Lp(a)] levels in atrial fibrillation (AF) is still uncertain, especially in the Chinese population. Here, we aimed to elucidate the potential relationship between Lp(a) quantiles and AF.MethodsAll data were collected through inpatients with electronic health records from the Second Affiliated Hospital of Nanchang University, Jiangxi Province, China. The propensity score matching (PSM) method was used to match control and case groups. Interactions between AF, Lp(a) quantiles, and other clinical indices were analyzed by logistic regression and stratified analysis. Statistical analyses were performed with IBM SPSS statistical software and R software.ResultsFrom 2017 to 2021, 4,511 patients with AF and 9,022 patients without AF were 1:2 matched by the propensity score matching method. A total of 46.9% of the study group was women, and the baseline mean age was 65 years. The AF group exhibited lower median Lp(a) than the non-AF group (15.95 vs. 16.90 mg/dL; P < 0.001). Based on the Lp(a) quantiles, the study population was divided into four groups: Q1 (≤ 8.71 mg/dL), Q2 (8.71–16.54 mg/dL), Q3 (16.54–32.42 mg/dL) and Q4 (> 32.42 mg/dL). The AF prevalence of each group decreased from 34.2% (Q1) to 30.9% (Q4) (P < 0.001). Lp(a) quantiles 1–3 significantly increased AF to 1.162-fold (1.049–1.286), 1.198-fold (1.083–1.327), and 1.111-fold (1.003–1.231) in the unadjusted logistic regression model, respectively. In the adjusted model, Lp(a) < 32.42 mg/dL still showed a significant inverse association with AF. In the stratified analysis, Lp(a) levels in female patients exhibited a significant negative correlation with AF (OR of Q1: 1.394[1.194–1.626], P = 0.001). Age and hypertension did not affect the adverse correlation.ConclusionLow circulating Lp(a) levels were associated with AF, especially in the female Han population, suggesting that Lp(a) may be useful for risk stratification of AF in female individuals.

Artificial intelligence-based risk stratification of atrial fibrillation among women with peripartum cardiomyopathy compared to other cardiomyopathies

Abstract Background Atrial fibrillation (AF) is diagnosed in up to 50% of patients with heart failure. However, the prevalence of AF among patients with peripartum cardiomyopathy (PPCM) ranges from only 2–10%, with the lowest rates in Black women. An artificial intelligence enhanced electrocardiogram (AI-ECG) has previously been shown to be effective in detecting AF while in sinus rhythm, and for AF risk prediction in a population-based study. Purpose Our objective was to evaluate the use of an AI-ECG for AF risk stratification among women of reproductive age (18 to 49 years) with PPCM compared to other forms of cardiomyopathy. Methods We identified 59 reproductive age women with a diagnosis of PPCM between January 2007, and October 2018 and included matched controls in a 3:1 fashion. Matching was performed based on sex, age, race, and left ventricular ejection fraction. We excluded patients with a diagnosis of AF prior to cardiomyopathy diagnosis date. AI-ECG prediction probabilities were generated for ECGs performed within a 30-day window prior to the patient's first cardiomyopathy diagnosis date for the entire study cohort. Results A total of 236 patients were included in the final analysis (59 cases, 177 controls). Overall, the median age at cardiomyopathy diagnosis was 31.7 years (IQR: 18.5, 49.4), 76.3% were White, 8.5% were Black, and 15.3% represented other or unknown race. Over the period studied, 3.4% of women with PPCM developed AF compared to 5.6% of women with other cardiomyopathies. The frequency of positive AI-ECG predictions for AF was more common among women with other cardiomyopathies (40.7%) compared to women with PPCM (20.3%). The predicted odds ratio for AF development following a cardiomyopathy diagnosis based on AI-ECG results was 0.37 (95% CI: 0.18, 0.73) for PPCM compared to other cardiomyopathies (p=0.006). Conclusion We demonstrated that an AI-ECG model for AF prediction may play a potential role in arrhythmia risk stratification/prediction among young women with PPCM who have a demonstrable lower risk for AF compared to women with other cardiomyopathies. Mechanisms for lower AF risk among patients with PPCM remain unknown. Further studies evaluating mechanistic pathways will be essential. Funding Acknowledgement Type of funding sources: None.

Association between atrial fibrillation and cardiac implantable defibrillator detected heart failure status

Abstract Funding Acknowledgements Type of funding sources: None. Background In heart failure (HF) patients, atrial fibrillation (AF) is a common comorbidity and is associated with a worse prognosis. Implantable defibrillator (ICD) diagnostics allow continuous monitoring of atrial high-rate events (AHRE), as a surrogate of AF, and are equipped with algorithms for HF monitoring. We evaluated the association between the values of the multisensor HF HeartLogic Index and the incidence of AF, and assessed the performance of the Index in detecting follow-up periods of significantly increased AF risk. Methods The HeartLogic feature was activated in 568 ICD patients. The median follow-up was 25 months [25th–75th percentile: 15-35]. The HeartLogic algorithm calculates a daily HF index and identifies periods IN the alert state on the basis of a configurable threshold. The endpoints were: daily AF burden of ≥5 minutes, ≥6 hours and ≥23 hours. Results The HeartLogic index crossed the threshold value 1200 times (0.71 alerts/patient-year). The time IN the alert state was 13% of the total observation period. During the observation period, an AF burden of ≥5 minutes/day was documented in 183 (32%) patients, ≥6 hours/day in 118 (21%) patients, and ≥23 hours/day in 89 (16%). On using a time-dependent Cox model, the weekly time IN the alert state was independently associated with an AF burden of ≥5 minutes/day (HR:1.95, 95%CI:1.22-3.13, p=0.005), ≥6 hours/day (HR:2.66, 95%CI:1.60-4.44, p&amp;lt;0.001), and ≥23 hours/day (HR:3.32, 95%CI:1.83-6.02, p&amp;lt;0.001), after correction for baseline confounders. Comparison of the episode rates in the IN-alert state with those in the OUT-of-alert state yielded HRs ranging from 1.57 to 3.11 for AF burden from ≥5 minutes to ≥23 hours. Conclusions The HeartLogic alert state was independently associated with AF occurrence. The intervals of time defined by the algorithm as periods of increased risk of HF allow risk stratification of AF according to various thresholds of daily burden.

Association between Gut Microbiota Dysbiosis and the CHA2DS2-VASc Score in Atrial Fibrillation Patients.

Background In our previous studies, we found a disordered taxonomic composition and function of gut microbiota (GM) in atrial fibrillation (AF) patients. However, direct evidence about the association between dysbiotic microbiota and thromboembolic risk in AF is lacking. Aims In this study, we analyzed the interaction of GM and related functional patterns in AF with different CHA2DS2-VASc scores to assess its potential as a biomarker for predicting stroke risk. Patients and Methods. The CHA2DS2-VASc score was used for thromboembolic risk stratification in AF according to American Heart Association (AHA) guidelines. We investigated the taxonomic and functional annotation of GM based on metagenomic data from 50 AF patients (32 with high thromboembolic risk (CHA2DS2-VASc score ≥2 (males) or CHA2DS2-VASc score ≥3 (females)) and 18 individuals with low thromboembolic risk (CHA2DS2-VASc score <2 (males) or CHA2DS2-VASc score <3 (females))). Results The gut microbial diversity, composition, and function in AF were different in high and low CHA2DS2-VASc score groups. In high thromboembolic risk group, the abundance of Prevotella, Lachnospiraceae, and Eubacterium rectale, related to the production of short-chain fatty acids and anti-inflammatory were reduced (all P < 0.05). Furthermore, annotated by Kyoto Encyclopedia of Genes and Genomes (KEGG), a database of genes and genomes, the KEGG orthology-based scoring approach exhibited a significant association with thromboembolic risk in AF patients. Conclusions Imbalance of GM and microbial dysfunction are involved in aggravated thromboembolic risk of AF.

Implantable defibrillator-detected heart failure status predicts atrial fibrillation occurrence.

In heart failure (HF) patients, atrial fibrillation (AF) is associated with a worse prognosis. Implantable cardioverter-defibrillator (ICD) diagnostics allow continuous monitoring of AF and are equipped with algorithms for HF monitoring. We evaluated the association between the values of the multisensor HF HeartLogic index and the incidence of AF, and assessed the performance of the index in detecting follow-up periods of significantly increased AF risk. The HeartLogic feature was activated in 568 ICD patients. Median follow-up was 25 months [25th-75th percentile (15-35)]. The HeartLogic algorithm calculates a daily HF index and identifies periods of IN-alert state on the basis of a configurable threshold. The endpoints were daily AF burden ≥5 minutes, ≥6 hours, and ≥23 hours. The HeartLogic index crossed the threshold value 1200 times. AF burden ≥5 minutes/day was documented in 183 patients (32%), ≥6 hours/day in 118 patients (21%), and ≥23 hours/day in 89 patients (16%). The weekly time of IN-alert state was independently associated with AF burden ≥5 minutes/day (hazard ratio [HR] 1.95; 95% confidence interval [CI] 1.22-3.13; P = .005), ≥6 hours/day (HR 2.66; 95% CI 1.60-4.44; P<.001), and ≥23 hours/day (HR 3.32; 95% CI 1.83-6.02; P<.001), after correction for baseline confounders. Comparison of the episode rates in the IN-alert state with those in the OUT-of-alert state yielded HR ranging from 1.57 to 3.11 for AF burden from ≥5 minutes to ≥23 hours. The HeartLogic alert state was independently associated with AF occurrence. The intervals of time defined by the algorithm as periods of increased risk of HF allow risk stratification of AF according to various thresholds of daily burden.

Control study of the intelligent calculation method and the traditional calculation method in risk assessments of hospitalization

To explore the accuracy of intelligent calculation (IC) method for risk assessment of hospitalization for patients, aiming to build a more advantageous risk assessment system. The "Search Engine" program was developed based on hospital information system (HIS) of the Fifth Center Hospital in Tianjin, which automatically captured patient information and generated nutritional risk screening 2002 (NRS 2002) score, Caprini thrombosis risk assessment model and Padua thrombosis risk assessment model for venous thromboembolism (VTE), the CHA2DS2-VASc for predicting stroke risk stratification in atrial fibrillation and the HAS-BLED for predicting bleeding risk in anticoagulated patients with atrial fibrillation. A randomized controlled trial was conducted. According to the applicable conditions of each risk assessment, 100 risk scores from "Search Engine" program belonged to each risk assessment were randomly selected, defined as the IC group. Manual scoring with the data of the same case at the same time, defined as the traditional calculation (TC) group, compared the consistency of the scores and the difference in time-consuming between the two groups. The Bland-Altman plots showed that the 95% limits of agreement (95%LoA) of NRS 2002 score, Caprini score, Padua score, CHA2DS2-VASc score and HAS-BLED score was -0.46 to 0.41, -0.49 to 0.52, -0.50 to 0.41, -0.67 to 0.60, -0.44 to 0.43, respectively, all P > 0.05. In this study, the Bland-Altman plot showed that 95%, 96%, 97%, 97%, 95% plots fell within the 95%LoA in NRS 2002 score, Caprini score, Padua score, wwCHA2DS2-VASc score and HAS-BLED score by the two methods, respectively. The all plots of 95%LoA were within the clinically acceptable range (-0.5 to 0.5 scores). The time-consuming of NRS 2002 score, Caprini score, Padua score, CHA2DS2-VASc score and HAS-BLED score in IC group were significantly shorter than those in TC group [0.72 (0.71, 0.73) seconds vs. 361.02 (322.41, 361.02) seconds, 0.72 (0.72, 0.73) seconds vs. 196.68 (179.99, 291.20) seconds, 0.72 (0.72, 0.73) seconds vs. 105.75 (92.32, 114.70) seconds, 0.72 (0.71, 0.72) seconds vs. 72.66 (56.24, 84.20) seconds, 0.72 (0.71, 0.72) seconds vs. 51.30 (38.88, 57.15) seconds, respectively, all P < 0.001]. For the above five risk assessments, the TC method and IC method has good consistency in scores, and the IC method is faster, which has good application prospect for clinical application.

Abstract 11604: The Cincinnati Atrial Fibrillation Score (CAFS): Multi-Center Derivation of the First Polysomnography-Based Risk Scoring System for Predicting Incident Atrial Fibrillation in Asymptomatic Community Adults

Introduction: Early diagnosis of atrial fibrillation (AF) leading to early therapy can improve clinical outcomes (e.g., stroke). Current approaches for AF risk stratification are limited. Dynamic ECG analysis during sleep is an alternate, underexplored approach for AF risk stratification. Hypothesis: Dynamic ECG analysis during sleep predicts AF incidence in community adults, and adds major independent prognostic value to conventional AF risk factors and scores. Methods: In the multi-center prospective Sleep Heart Health Study, we studied consecutive, asymptomatic, ostensibly healthy, middle-aged and older community adults without a history of AF who were in sinus rhythm during home polysomnography. We performed comprehensive and systematic univariate and multivariate analyses of all available clinical, ECG and polysomnography parameters for association with AF incidence over follow-up. Results: Over 5.3±0.29 years, 315 (11.2%) of 2,807 people had new onset AF. We identified the major independent significant AF predictors, including established risk factors and ECG dynamics, and derived a multivariate prediction model entitled, the Cincinnati AF score (CAFS) ( FIGURE 1 ). Addition of CAFS to a multivariate model with (1) CHA 2 DS 2 -VASc score increased ROC curve area by 9% and yielded net reclassification improvement (NRI) of 90% [43+47% for cases and non-cases, respectively]; or with (2) CHARGE-AF score increased ROC curve area by 3.5% and yielded NRI of 54% [23+31%]. These improvements were driven primarily by the ECG dynamics, independent of sleep apnea and other risk factors. Conclusion: Dynamic ECG analysis during sleep adds major independent prognostic value to established AF risk factors and scores. The ability to better identify individuals who will and will not develop AF has potential for broad clinical impact. We are currently validating CAFS in another multi-center cohort of asymptomatic ambulatory adults with a diverse demographic profile.

Is the Median Hourly Ambulatory Heart Rate Range Helpful in Stratifying Mortality Risk among Newly Diagnosed Atrial Fibrillation Patients?

Background: The application of heart rate variability is problematic in patients with atrial fibrillation (AF). This study aims to explore the associations between all-cause mortality and the median hourly ambulatory heart rate range () compared with other parameters obtained from the Holter monitor in patients with newly diagnosed AF. Material and Methods: A total of 30 parameters obtained from 521 persistent AF patients’ Holter monitor were analyzed retrospectively from 1 January 2010 to 31 July 2014. Every patient was followed up to the occurrence of death or the end of 30 June 2017. Results: was the most feasible Holter parameter. Lower was associated with increased risk of all-cause mortality (adjusted hazard ratio [aHR] for every 10-bpm reduction: 2.70, 95% confidence interval [CI]: 1.75–4.17, p < 0.001). The C-statistic of alone was 0.707 (95% CI: 0.658–0.756), and 0.697 (95% CI: 0.650–0.744) for the CHA2DS2-VASc score alone. By combining with the CHA2DS2-VASc score, the C-statistic could improve to 0.764 (95% CI: 0.722–0.806). While using 20 bpm as the cut-off value, the aHR was 3.66 (95% CI: 2.05–6.52) for patients with < 20 bpm in contrast to patients with ≥ 20 bpm. Conclusions: could be helpful for risk stratification for AF in addition to the CHA2DS2-VASc score.

The association of stroke rate with low density lipoprotein and statin exposure in patients with atrial fibrillation (AF)

Abstract Background There are limited data on the association between cholesterol levels and stroke risk in atrial fibrillation (AF). Objective To quantify the association of stroke rate in AF with low-density lipoprotein (LDL) levels and statin use. Methods Using linked administrative databases in Ontario, Canada, we conducted a population-based retrospective cohort study of patients aged ≥66 years, diagnosed with AF between 2009–2019. We used cause-specific hazard regression to determine the association of statin use with stroke rate. We developed a second cause-specific regression model for patients with at least one lipid profile measurement in the year before AF diagnosis to study the association of LDL levels with stroke rate, while adjusting for statin use. LDL levels were modeled using restricted cubic splines (RCS). Both models were adjusted for age, sex, heart failure, hypertension, diabetes, stroke or transient ischemic attack, and vascular disease at baseline, plus anticoagulation as a time-varying covariate. Results We studied 261,659 qualifying patients (median age 78 years, 49% female), of whom 3,954 (1.5%) developed a stroke during one-year follow-up. A total of 142,834 (54.6%) patients were treated with statins and 145,775 (55.7%) had lipid measurements before AF diagnosis. The adjusted RCS analyses (see Figure) indicated increasing hazard ratios (HRs) for stroke with increasing low-density lipoprotein (LDL) values above 1.5mmol/L. Statin use was associated with a lower stroke rate relative to non-users (hazard ratio 0.87, 95% confidence interval 0.81–0.93, p-value &amp;lt;0.0001). Conclusion LDL levels above 1.5mmol/L were independently associated with higher stroke rates in patients with AF, while statins were associated with lower stroke rates independent of anticoagulation. This suggests that LDL measurements may improve stroke risk stratification in AF, while statins may offer an underutilized pathway to lower stroke risk in AF. Funding Acknowledgement Type of funding sources: Foundation. Main funding source(s): 1) Heart and stroke foundation of Canada HR for Stroke and LDL level

Risk Stratification for Atrial Fibrillation and Outcomes in Tachycardia-Bradycardia Syndrome: Ablation vs. Pacing.

Background: Catheter ablation of atrial fibrillation is an alternative treatment for patients with tachycardia-bradycardia syndrome (TBS) to avoid pacemaker implantation. The risk stratification for atrial fibrillation and outcomes between ablation and pacing has not been fully evaluated.Methods: This retrospective study involved 306 TBS patients, including 141 patients who received catheter ablation (Ablation group, age: 62.2 ± 9.0 months, mean longest pauses: 5.2 ± 2.2 s) and 165 patients who received pacemaker implement (Pacing group, age: 62.3 ± 9.1 months, mean longest pauses: 6.0 ± 2.3 s). The primary endpoint was a composite of call cause mortality, cardiovascular-related hospitalization or thrombosis events (stroke, or peripheral thrombosis). The second endpoint was progress of atrial fibrillation and heart failure.Results: After a median follow-up of 75.4 months, the primary endpoint occurred in significantly higher patients in the pacing group than in the ablation group (59.4 vs.15.6%, OR 6.05, 95% CI: 3.73–9.80, P < 0.001). None of deaths was occurred in ablation group, and 1 death occurred due to cancer. Cardiovascular-related hospitalization occurred in 50.9% of the pacing group compared with 14.2% in the ablation group (OR: 4.87, 95% CI: 2.99–7.95, P < 0.001). More thrombosis events occurred in the pacing group than in the ablation group (12.7 vs. 2.1%, OR 6.06, 95% CI: 1.81–20.35, P = 0.004). Significant more patients progressed to persistent atrial fibrillation in pacing group than in ablation group (23.6 vs. 2.1%, P < 0.001). The NYHA classification of the pacing group was significantly higher than that of the ablation group (2.11 ± 0.83 vs. 1.50 ± 0.74, P < 0.001). The proportion of antiarrhythmic drugs and anticoagulants used in the pacing group was significantly higher than that in the ablation group (41.2 vs. 7.1%, P < 0.001; 16.4 vs. 2.1%, P = 0.009).Conclusion: Catheter ablation for patients with TBS was associated with a significantly lower rate of a composite end point of cardiovascular related hospitalization and thromboembolic events. Furthermore, catheter ablation reduced the progression of atrial fibrillation and heart failure.

Atrial fibrillation risk scores to evaluate left atrial substrate based on voltage analysis in long-standing persistent type of arrhythmia.

Pre-ablation identification of left atrial (LA) low voltage areas (LVA) among long-standing persistent atrial fibrillation (LSPAF) population remains challenging. The aim of the study was to analyze the potential of selected scores originally developed to assess arrhythmia recurrences, thromboembolic complications, or progression from paroxysmal to persistent AF to predict the presence of LA-LVA in LSPAF patients. One hundred and fifty-two patients underwent pulmonary vein isolation followed by high-density-high-resolution LA voltage mapping. AF risk scores, such as APPLE, ATLAS, CAAP-AF, DR-FLASH, CHA2DS2-VASc, and HATCH were retrospectively calculated. A receiver operating characteristic curve analysis was performed to evaluate the ability of the scores to predict LVA. Low voltage areas were detected in 52% of the patients. 28% of the patients with LVA presented severe global LVA burden, whereas 56% of the patients showed a disseminated pattern of remodeling. CAAP-AF ≥7, DR-FLASH ≥4, and CHA2DS2-VASc ≥3 predicted the presence of LVA, whereas ATLAS ≤7 indicated the absence of LVA. ATLAS ≤8, CAAP-AF ≤9, DR-FLASH ≤4, and CHA2DS2-VASc ≤3 predicted the absence of severe LVA. APPLE ≤3 and CHA2DS2-VASc ≤2 predicted the absence of a LVA disseminated pattern. Among predictive scores, ATLAS (AUC, 0.633, 95% CI, 0.543-0.723, P = 0.004), DR-FLASH (AUC, 0.696; 95% CI, 0.594-0.81; P <0.001), and CHA2DS2-VASc (AUC, 0.644; 95% CI 0.518-0.77; P = 0.025) were the best predictors for the absence of LVA, severe LVA and a disseminated pattern of LVA, respectively. Atrial fibrillation risk stratification with specific scoring systems can unmask the presence of LA-LVA in the LSPAF population.

Electrocardiographic and Echocardiographic Abnormalities in Patients with Risk Factors for Atrial Fibrillation.

The electrocardiogram and various echocardiography modalities are important risk markers for atrial fibrillation (AF). Electrocardiographic criteria of left atrial enlargement, advanced interatrial block, and PR-interval prolongation are atrial risk markers for AF. Transthoracic echocardiography is elementary for risk stratification of AF. Transesophageal echocardiography is a valuable tool to detect cardiac sources of embolism if early cardioversion is necessary. Intracardiac echocardiography is a real-time tool for guidance of percutaneous interventions, including radiofrequency ablation and left atrial appendage closure in patients with AF.

Preventive Cardio-Oncology: Cardiovascular Disease Prevention in Cancer Patients and Survivors

To review the most common forms of cardiovascular toxicities from anti-cancer drugs, with a focus on their prevention via cardioprotective pharmacologic or lifestyle therapy, risk factors management, screening, monitoring, and surveillance methods. There are almost 20 million cancer survivors in the USA, and their leading cause of death besides cancer recurrence or a secondary cancer is cardiovascular disease (CVD). CVD is prevalent in this population, with the most common forms being cardiomyopathy, ischemia, atrial fibrillation, and hypertension from cancer drugs or radiation therapy. The field of cardio-oncology is continuously evolving with multi-modality risk prediction strategies, moving towards precision surveillance and interventions that allow for safe continuation of life-saving chemotherapy. Preventative measures with implementation of novel drugs (including sodium-glucose cotransporter inhibitors) and modulated chemotherapy administration can aid in cardiotoxicity risk reduction. Recently, clonal hematopoiesis of indeterminate potential has been identified as a common risk factor for atherosclerotic cardiovascular disease present in > 10% of those age 70 or older. Also, risk stratification for atrial fibrillation appears pivotal. Multidisciplinary team management might have a central role in patient management and care. There is a central role for the optimization of cardiovascular disease risk for cancer patients and survivors in multidisciplinary teams, with descriptions of four forms of cardiovascular toxicities. In addition to pharmacologic cardioprotection, lifestyle modification is becoming more prominent as a preventive tool. Moreover, studies relevant to one type of toxicity should be scrutinized routinely to determine how those result may play out in the setting of other types of toxicities. All of these areas of investigation should ultimately be pursued in the setting of personalized medicine, and will likely benefit from the integration of artificial intelligence methods. Studies in genomics and transcriptomics have identified variations in the genome and gene expression profiles that associate with induction of or protection from cardiovascular toxicity and can affect cardioprotection efforts. Larger randomized clinical trials will be needed for all patients, with a focus on incorporation of ethnic minorities likely by intentional oversampling, to overcome decades of demographic homogeneity in the trials.

Left Atrial Diameter and Atrial Ectopic Burden in Patients with Embolic Stroke of Undetermined Source: Risk Stratification of Atrial Fibrillation with Insertable Cardiac Monitor Analysis.

Background and PurposeAn insertable cardiac monitor (ICM) has been demonstrated to be a useful tool for detecting subclinical atrial fibrillation (AF) in patients with embolic stroke of undetermined source (ESUS). This study aimed to identify the clinical predictors of AF in ESUS patients with ICMs.MethodsWe retrospectively selected consecutive patients with an ICM implanted for AF detection following ESUS. The primary endpoint was defined as any AF episode lasting for longer than 5 min. The atrial ectopic burden (AEB) was calculated as the percentage of the number of conducted QRS from atrial ectopy on Holter monitoring.ResultsThis study included 136 patients. AF lasting ≥5 min was detected in 20 patients (14.7%) during a median follow-up period of 6.6 months (interquartile range, 3.3–10.8 months). AF patients had a higher AEB (0.20% vs. 0.02%, p<0.001) and a larger left atrial diameter (LAD, 41.0 mm vs. 35.3 mm, p<0.001) than those without AF. The areas under the receiver operating characteristic curves were 0.795 and 0.816 for the LAD and log-transformed AEB, respectively, for the best cutoff values of 38.5 mm for LAD and 0.050% for AEB. AF lasting ≥5 min was detected in 34.6% (9/26) of patients with LAD ≥38.5 mm and AEB ≥0.050%, and in 0% (0/65) of those with LAD <38.5 mm and AEB <0.050%.ConclusionsAF was detected in a significant proportion of ESUS patients during a 6.6-month follow-up. The LAD and AEB are good predictors of AF and might be useful for AF risk stratification in ESUS patients.