Predictors Of New-onset Atrial Fibrillation Research Articles

Abstract 4137989: Notched P-wave by digital ECG analysis was associated with new-onset atrial fibrillation onset and ischemic stroke

Background: A bimodal P wave in lead II reflects left atrial remodeling and is described as a notched P wave. A notched P wave is usually defined as a dip over the smallest unit of electrocardiography (ECG) recording paper, 40 ms, but automated analysis of ECGs has shown that even a notch of 20 ms is associated with cardiovascular events. A notched P wave is also known to predict atrial fibrillation (AF) after catheter ablation. However, the relationship between automatically assessed notched P waves and new-onset AF and ischemic stroke in patients without documented AF has not been clarified. Hypothesis: A notched P-wave by digital ECG analysis was associated with both new-onset AF and ischemic stroke. Methods: We enrolled 4,216 subjects from the Cardiovascular Prognostic Coupling Study in Japan (Coupling Registry) who had one or more cardiovascular risk factors. Twelve-lead electrocardiography was conducted, and the peak-to-peak distance in the M shape was calculated automatically using a 12-lead ECG analysis system. We compared two definitions: P-waves defined as “notched” at the the peak-to-peak (“M shape”) distance in lead II of ≥20 ms or ≥40 ms. New-onset AF was confirmed through routine medical care as well as annual ECGs. We defined the primary endpoint as new-onset AF and the secondary endpoint as ischemic stroke. Results: The mean follow-up period was 53 ± 17 months, during which 17 AF cases developed. When a notched P-wave was defined as ≥20 ms (n = 319), it was a significant predictor of both new-onset AF (hazard ratio [HR] 2.91, 95% confidence interval [CI] 1.41–6.01, p=0.004) and ischemic stroke (HR 3.02, 95% CI 1.56–5.83, P=0.001). A notched P-wave defined as ≥40 ms (n = 63) was also a predictor of new-onset AF (HR 4.57; 95% CI:1.42–14.71, p = 0.011) and ischemic stroke (HR 3.84, 95% CI 1.20–12.29, P=0.024). Conclusions: A notched P-wave by digital ECG analysis was associated with ischemic stroke as well as the new-onset AF.

Predictors of New-Onset Atrial Fibrillation in Patients With Chronic Coronary Artery Disease After Coronary Artery Bypass Grafting: a Prospective, Observational, Single-Centre, Non-Randomized Study

Aim. To study the factors that influence the occurrence of postoperative atrial fibrillation (POAF) in patients with chronic ischemic heart disease (IHD) after coronary artery bypass grafting (CABG).Material and methods. This single-center prospective observational non-randomized study included 152 patients with chronic IHD. Mean age of patients was 64.4±5.9 years. All patients after CABG were divided into two groups based on the occurrence of atrial fibrillation (AF) in the early postoperative period: group 1, with POAF (n=43; 28.3%) and group 2, without POAF (n=109; 71.7%). The primary study endpoint was new-onset POAF in the early postoperative (hospital) period after CABG. The secondary study endpoint was in-hospital postoperative complications (non-fatal/fatal acute coronary syndrome (ACS), non-fatal/fatal stroke, major bleeding, death).Results. Patients with POAF had significantly more pronounced structural and functional changes in the heart than patients with preserved sinus rhythm after CABG: larger left ventricular (LV) volume, greater LV myocardial mass, lower LV systolic function parameters and impaired diastolic function, and an enlarged left atrial (LA) cavity. Analysis of in-hospital complications did not show any differences between the groups associated with the development of POAF. The following risk factors for POAF were identified: age older than 65 years (p=0.022), body mass index ≥30.5 kg/m2 (p=0.020), epicardial adipose tissue thickness >10.5 mm (p=0.015), indexed LA volume >33 ml/m2 (p<0.001), LV myocardial mass index >115 g/m2 (p=0.042), left main coronary artery disease >50% (p=0.043), duration of cardiopulmonary bypass during CABG >60 min (p=0.019), blood potassium concentration in the early postoperative period after CABG (on the first day) <3.6 mmol/l (p<0.001), and pericardial effusion volume in the early postoperative period >88 ml (p<0.001).Conclusion. Determining the risk of developing POAF is important and necessary for the closest monitoring of a patient with chronic IHD in the postoperative period.

Prediction of new-onset atrial fibrillation in patients with hypertrophic cardiomyopathy using plasma proteomics profiling.

Atrial fibrillation (AF) is the most common sustained arrhythmia among patients with hypertrophic cardiomyopathy (HCM), increasing symptom burden and stroke risk. We aimed to construct a plasma proteomics-based model to predict new-onset AF in patients with HCM and determine dysregulated signalling pathways. In this prospective, multi-centre cohort study, we conducted plasma proteomics profiling of 4986 proteins at enrolment. We developed a proteomics-based machine learning model to predict new-onset AF using samples from one institution (training set) and tested its predictive ability using independent samples from another institution (test set). We performed a survival analysis to compare the risk of new-onset AF among high- and low-risk groups in the test set. We performed pathway analysis of proteins significantly (univariable P < 0.05) associated with new-onset AF using a false discovery rate (FDR) threshold of 0.001. The study included 284 patients with HCM (training set: 193, test set: 91). Thirty-seven (13%) patients developed AF during median follow-up of 3.2 years [25-75 percentile: 1.8-5.2]. Using the proteomics-based prediction model developed in the training set, the area under the receiver operating characteristic curve was 0.89 (95% confidence interval 0.78-0.99) in the test set. In the test set, patients categorized as high risk had a higher rate of developing new-onset AF (log-rank P = 0.002). The Ras-MAPK pathway was dysregulated in patients who developed incident AF during follow-up (FDR < 1.0 × 10-6). This is the first study to demonstrate the ability of plasma proteomics to predict new-onset AF in HCM and identify dysregulated signalling pathways.

Predictors of New-Onset Atrial Fibrillation in Patients with ESKD: A Multicenter, Retrospective, Observational Cohort Study

Predictors of New-Onset Atrial Fibrillation in Patients with ESKD: A Multicenter, Retrospective, Observational Cohort Study

Prediction of new-onset atrial fibrillation in patients with non-small cell lung cancer treated with curative-intent conventional radiotherapy

BackgroundAtrial fibrillation (AF) is an important side effect of thoracic Radiotherapy (RT), which may impair quality of life and survival. This study aimed to develop a prediction model for new-onset AF in patients with Non-Small Cell Lung Cancer (NSCLC) receiving RT alone or as a part of their multi-modal treatment. Patients and MethodsPatients with stage I-IV NSCLC treated with curative-intent conventional photon RT were included. The baseline electrocardiogram (ECG) was compared with follow-up ECGs to identify the occurrence of new-onset AF. A wide range of potential clinical predictors and dose-volume measures on the whole heart and six automatically contoured cardiac substructures, including chambers and conduction nodes, were considered for statistical modeling. Internal validation with optimism-correction was performed. A nomogram was made. Results374 patients (mean age 69 ± 10 years, 57 % male) were included. At baseline, 9.1 % of patients had AF, and 42 (11.2 %) patients developed new-onset AF. The following parameters were predictive: older age (OR=1.04, 95 % CI: 1.013–1.068), being overweight or obese (OR=1.791, 95 % CI: 1.139–2.816), alcohol use (OR=4.052, 95 % CI: 2.445–6.715), history of cardiac procedures (OR=2.329, 95 % CI: 1.287–4.215), tumor located in the upper lobe (OR=2.571, 95 % CI: 1.518–4.355), higher forced expiratory volume in 1 s (OR=0.989, 95 % CI: 0.979–0.999), higher creatinine (OR=1.008, 95 % CI: 1.002–1.014), concurrent chemotherapy (OR=3.266, 95 % CI: 1.757 to 6.07) and left atrium Dmax (OR=1.022, 95 % CI: 1.012–1.032). The model showed good discrimination (area under the curve = 0.80, 95 % CI: 0.76–0.84), calibration and positive net benefits. ConclusionThis prediction model employs readily available predictors to identify patients at high risk of new-onset AF who could potentially benefit from active screening and timely management of post-RT AF.

Evaluating the effect of coronary atherosclerosis on the occurrence of atrial fibrillation through coronary computed tomography angiography.

The direct impact of atherosclerotic lesions in coronary vessels on the occurrence of atrial fibrillation (AF) in patients without a history of acute myocardial ischemia, previous myocardial infarction, or revascularization procedures remains largely unknown. To assess the risk and predictors of new-onset AF in patients with coronary atherosclerosis confirmed by coronary computed tomography angiography (CCTA). We included consecutive patients referred for CCTA who had been observed and diagnosed with new-onset AF over 10 years. Of the 549 patients enrolled in the study, 208 (37.9%) were diagnosed with atherosclerotic lesions in the coronary vessels and 63 (11.5%) developed AF during the 10 years of observation. Patients with AF were older (61.8 [10.4] years vs. 58.3 [9.2] years; P = 0.005), had an enlarged left atrium in the anteroposterior dimension (38.2 [7.2] mm vs. 34.4 [5.4] mm; P < 0.001), and had a widened interventricular septum (12.3 [2.0] mm vs. 11.0 [2.1] mm; P < 0.001). We also found a significant correlation between the occurrence of AF in patients with coronary atherosclerotic lesions and with increased thickness of the interventricular septum relative to the posterior wall of the left ventricle (P = 0.017). Our data indicate an association between coronary atherosclerosis and the greater risk of AF in patients with increased thickness of the interventricular septum relative to the posterior wall of the left ventricle. This finding suggests that by using CCTA we can predict which patients are at higher risk of developing AF.

CHA2DS2-VASc Score as Predictor of New-Onset Atrial Fibrillation and Mortality in Critical COVID-19 Patients.

Pre-existing and new-onset atrial fibrillation (NOAF) is a common arrhythmia in COVID-19 patients and is related to increased mortality. CHA2DS2-VASc score was initially developed to evaluate thromboembolic risk in patients with AF. Moreover, it predicted adverse outcomes in other clinical conditions, including SARS-CoV-2 infection. We aimed to evaluate the association of CHA2DS2-VASc with NOAF, ICU length of stay (LOS) and mortality in critically ill COVID-19 patients. We also examined the relationship of NOAF with mortality. We reviewed the literature to describe the link between cardiovascular risk factors and inflammatory response of severe COVID-19. We retrospectively studied 163 COVID-19 patients admitted to a level 3 general ICU from March 2020 to April 2022. Patients were of advanced age (median 64 years, IQR 56.5-71) and the majority of them were male (67.5%). Regarding NOAF, we excluded 12 patients with AF history. In this group, CHA2DS2VASc score was significantly elevated (3 IQR (1-4) versus 1 IQR (1-2.75), p = 0.003). Specifically, three components of CHA2DS2VASc were notably increased: age (p < 0.001), arterial hypertension (p = 0.042) and stroke (p = 0.047). ICU mortality was raised in the NOAF group [75.8% versus 34.8%, p < 0.001 OR 5.87, 95% CI (2.43, 14.17)]. This was significant even after adjusting for ICU clinical scores (APACHE II and SOFA). About mortality in the entire sample, survivors were younger (p = 0.001). Non-survivors had greater APACHE II (p = 0.04) and SOFA (p = 0.033) scores. CHA2DS2VASc score was positively associated with mortality [p = 0.031, OR 1.28, 95% CI (1.03, 1.6)]. ICU length of stay was associated with mortality (p = 0.016) but not with CHA2DS2VASc score (p = 0.842). NOAF and CHA2DS2VASc score were associated with higher mortality in COVID-19 ICU patients. CHA2DS2VASc score was also associated with NOAF but not with ICU LOS.

Role of the Electrocardiogram for Identifying the Development of Atrial Fibrillation.

Atrial fibrillation (AF), a prevalent cardiac arrhythmia, is associated with increased morbidity and mortality worldwide. Stroke, the leading cause of serious disability in the United States, is among the important complications of this arrhythmia. Recent studies have demonstrated that certain clinical variables can be useful in the prediction of AF development in the future. The electrocardiogram (ECG) is a simple and cost-effective technology that is widely available in various healthcare settings. An emerging body of evidence has suggested that ECG tracings preceding the development of AF can be useful in predicting this arrhythmia in the future. Various variables on ECG especially different P wave parameters have been investigated in the prediction of new-onset AF and found to be useful. Several risk models were also introduced using these variables along with the patient's clinical data. However, current guidelines do not provide a clear consensus regarding implementing these prediction models in clinical practice for identifying patients at risk of AF. Also, the role of intensive screening via ECG or implantable devices based on this scoring system is unclear. The purpose of this review is to summarize AF and various related terminologies and explain the pathophysiology and electrocardiographic features of this tachyarrhythmia. We also discuss the predictive electrocardiographic features of AF, review some of the existing risk models and scoring system, and shed light on the role of monitoring device for screening purposes.

Cardiac Mechanics and the Risk of Atrial Fibrillation in a Community-Based Cohort of Older Adults.

Assessment of cardiac structure and function improves risk prediction of new-onset atrial fibrillation (AF) in different populations. We aimed to comprehensively compare standard and newer measures of cardiac structure and function in improving prediction of AF in a cohort of older adults without history of AF and stroke. We included 5050 participants without prevalent AF and stroke (mean age 75 ± 5 years, 59% women and 22% Black) from the Atherosclerosis Risk in Communities (ARIC) study who underwent complete 2-dimensional echocardiography, including speckle-tracking analysis of the left ventricle (LV) and left atrium (LA). We assessed the association of cardiac measures with incident AF (including atrial flutter) and quantified the extent to which these measures improved model discrimination and risk classification of AF compared with the CHARGE-AF score. Over a median follow-up time of 7 years, 676 participants developed AF (incidence rate, 2.13 per 100 person-years). LV mass index and wall thickness, E/e' and measures of LA structure and function, but not LV systolic function, were associated with incident AF, after accounting for confounders. Above all, LA reservoir strain, contraction strain, and LA minimal volume index (C-statistics [95%Confidence interval]: 0.73 [0.70,0.75], 0.72 [0.70,0.75] and 0.72 [0.69,0.75], respectively) significantly improved the risk discrimination of the CHARGE-AF score (baseline C-statistic: 0.68 [0.65,0.70]) and achieved the highest category-based net reclassification improvement (29%, 24% and 20%, respectively). In a large cohort of older adults without prevalent AF and stroke, measures of LA function improved the prediction of AF more than other conventional cardiac measures.

Prediction of New-Onset Atrial Fibrillation in Transcatheter Aortic Valve Implantation.

This study investigates the association between prolonged total atrial conduction time and the development of new-onset atrial fibrillation (AF) following transcatheter aortic valve implantation (TAVI). We enrolled 307 patients who underwent TAVI. Total atrial conduction time was calculated as the time between the onset of the P wave on the electrocardiography and the peak of the a' wave velocity (PA-TDI duration) on tissue Doppler imaging echocardiography. A total of 263 patients were analyzed after excluding 44 with pre-existing AF. Of these 263 patients, 47 (17.8%) experienced new-onset AF after the TAVI procedure. The new-onset AF group had an older median age (80.6 vs. 77.5 years) and a higher incidence of paravalvular aortic regurgitation than those without AF (none 29.8%, mild 46.8%, moderate 23.4%). The new-onset AF group had increased end-systolic diameter (35.0 vs. 31.7 mm, p = 0.03), left atrial diameter (44.7 vs. 41.9 mm, p = 0.049), and PA-TDI duration (137.0 vs. 125.4 ms, p = 0.009). Older age, the presence of paravalvular aortic regurgitation, and prolonged PA-TDI duration were independently associated with new-onset AF in multivariate analysis. The optimal cut-off value for PA-TDI duration was 123.5 ms. AF in patients treated with TAVI may pose significant risks for morbidity and mortality. PA-TDI duration, a readily available echocardiographic parameter, can detect patients with a high risk of new-onset AF.

Precise risk-prediction model including arterial stiffness for new-onset atrial fibrillation using machine learning techniques.

Atrial fibrillation (AF) is the most common clinically significant cardiac arrhythmia and is an important risk factor for ischemic cerebrovascular events. This study used machine learning techniques to develop and validate a new risk prediction model for new-onset AF that incorporated the use electrocardiogram to diagnose AF, data from participants with a wide age range, and considered hypertension and measures of atrial stiffness. In Japan, Industrial Safety and Health Law requires employers to provide annual health check-ups to their employees. This study included 13 410 individuals who underwent health check-ups on at least four successive years between 2005 and 2015 (new-onset AF, n=110; non-AF, n=13 300). Data were entered into a risk prediction model using machine learning methods (eXtreme Gradient Boosting and Shapley Additive Explanation values). Data were randomly split into a training set (80%) used for model construction and development, and a test set (20%) used to test performance of the derived model. The area under the receiver operator characteristic curve for the model in the test set was 0.789. The best predictor of new-onset AF was age, followed by the cardio-ankle vascular index, estimated glomerular filtration rate, sex, body mass index, uric acid, γ-glutamyl transpeptidase level, triglycerides, systolic blood pressure at cardio-ankle vascular index measurement, and alanine aminotransferase level. This new model including arterial stiffness measure, developed with data from a general population using machine learning methods, could be used to identify at-risk individuals and potentially facilitation the prevention of future AF development.

Incidence and predictors of new-onset atrial fibrillation in ST-elevation myocardial infarction: A single-center study.

Atrial fibrillation (AF) is a common arrhythmia that occurs following ST-elevation myocardial infarction (STEMI) and can significantly impact clinical outcomes. We investigated the incidence and predictors of AF following STEMI in patients, as well as its association with major adverse cardiac and cerebrovascular events (MACCE). We conducted a retrospective cohort study, including all STEMI patients who presented under code 247 to Tehran Heart Center between 2016 and 2020 and completed a 1-year follow-up. Patients were divided into two groups based on the development of AF during follow-up, and their baseline and clinical characteristics were compared. We used multivariable regression models to identify predictors of MACCE. Out of 3647 STEMI patients, 84 (2.3%) developed new-onset AF (NOAF). Patients with AF were significantly older and had lower levels of total and low-density lipoprotein cholesterol, triglyceride, and hemoglobin, but higher levels of fasting blood sugar and creatinine. AF patients were also more likely to have a history of hypertension, chronic kidney disease (CKD), congestive heart failure, and cerebrovascular accidents. The multivariable logistic regression model identified the CHA2DS2-VASc score and CKD as independent predictors of NOAF following primary percutaneous coronary intervention. Furthermore, the incidence of MACCE was higher in the AF group, and AF independently predicted MACCE with a hazard ratio of 2.766. The CHA2DS2-VASc score and the presence of CKD can serve as useful predictors of NOAF among patients with STEMI. Early detection and appropriate management are crucial to improve outcomes.

Multi-inflammatory index as a novel predictor of new-onset atrial fibrillation after off-pump coronary artery bypass grafting.

To our knowledge, a possible predictive relationship of the multi-inflammatory index (MII) with new-onset atrial fibrillation (AF) after off-pump coronary artery bypass grafting (CABG) has not yet been studied in the literature. We aimed to investigate whether the MII is a novel group of hematological markers for predicting postoperative new-onset AF in patients undergoing off-pump CABG. A total of 427 patients undergoing isolated off-pump CABG between October 2021 and December 2023 were enrolled in this retrospective observational cohort study and allocated to two groups: the AF group (n = 108) and the non-AF group (n = 319). The groups were compared in terms of baseline clinical patient characteristics, laboratory parameters, and operative and postoperative data. The median values of age, length of hospital stay, platelet and neutrophil count, C-reactive protein level, systemic immune-inflammation index, MII-1, MII-2, and MII-3 were significantly greater in the AF group compared to the non-AF group in univariate analyses. In multiple explanatory variable logistic regression analysis, MII-1, MII-2, and MII-3 were determined to be significant hematological variables, and thereby these indices were considered the independent predictors of postoperative new-onset AF. Receiver operating characteristic curve analyses showed that to predict postoperative new-onset AF, MII-1 of 22.47 constituted the cut-off value with 62.0% sensitivity and 57.0% specificity, MII-2 of 141.77 constituted the cut-off value with 43.5% sensitivity and 76.8% specificity, and MII-3 of 5669 constituted the cut-off value with 63.8% sensitivity and 58.3% specificity. This study demonstrated for the first time that all MIIs predicted new-onset AF after off-pump CABG.

Wybrane czynniki predykcyjne migotania przedsionków u pacjentów z niewydolnością serca

Atrial fibrillation, which is one of the most commonly diagnosed arrhythmias in adults, is associated with high morbidity and mortality. Atrial fibrillation is also the most common arrhythmia in patients with heart failure, and it has been shown to increase the risk of death, heart failure-related hospitalization, and stroke or transient ischemic attack. Considering these clinical and therapeutic implications, it seems advisable to assess patients for risk factors of atrial fibrillation. The purpose of this study was to present the predictors of new-onset atrial fibrillation particularly in patients with heart failure.

Prediction of new-onset atrial fibrillation with the C2HEST score in patients admitted with community-acquired pneumonia

PurposePatients hospitalized for community-acquired pneumonia (CAP) may have a higher risk of new-onset atrial fibrillation (NOAF). The C2HEST score was developed to evaluate the NOAF risk in the general population. Data on the value of the C2HEST score in acute patients admitted with CAP are lacking. We want to establish the predictive value of C2HEST score for NOAF in patients with CAP.MethodsPatients with CAP enrolled in the SIXTUS cohort were enrolled. C2HEST score was calculated at baseline. In-hospital NOAF was recorded. Receiver-operating Characteristic (ROC) curve and multivariable Cox proportional hazard regression analysis were performed.ResultsWe enrolled 473 patients (36% women, mean age 70.6 ± 16.5 years), and 54 NOAF occurred. Patients with NOAF were elderly, more frequently affected by hypertension, heart failure, previous stroke/transient ischemic attack, peripheral artery disease and hyperthyroidism. NOAF patients had also higher CURB-65, PSI class and CHA2DS2-VASc score. The C-index of C2HEST score for NOAF was 0.747 (95% confidence interval [95%CI] 0.705–0.786), higher compared to CURB-65 (0.611, 95%CI 0.566–0.655, p = 0.0016), PSI (0.665, 95%CI 0.621–0.708, p = 0.0199) and CHA2DS2-VASc score (0.696, 95%CI 0.652–0.737, p = 0.0762). The best combination of sensitivity (67%) and specificity (70%) was observed with a C2HEST score ≥ 4. This result was confirmed by the multivariable Cox analysis (Hazard Ratio [HR] for C2HEST score ≥ 4 was 10.7, 95%CI 2.0–57.9; p = 0.006), independently from the severity of pneumonia.ConclusionThe C2HEST score was a useful predictive tool to identify patients at higher risk for NOAF during hospitalization for CAP.Clinical Trial Registrationwww.clinicaltrials.gov (NCT01773863)

Left atrial strain and long-term risk of atrial fibrillation in hypertrophic cardiomyopathy

Abstract Background The prevalence of atrial fibrillation (AF) in hypertrophic cardiomyopathy (HCM) patients is higher than in the general population, and it is associated with an increased risk of adverse outcomes, such as stroke, heart failure, and mortality. The left atrium (LA) plays an important role in maintaining normal cardiac function, and alterations in its structure and function can contribute to the development of AF. LA strain, a surrogate of LA remodeling, has been suggested a predictor of future AF. Purpose The aim of this study was to explore risk factors of new onset AF highlighting LA strain in patients with HCM. Methods Among a prospective cohort of 865 HCM patients collected at two large tertiary centers, 696 with adequate echocardiographic images to measure LA strain without a history of AF were included in the analysis. LA strain was measured on apical four-chamber view at initial evaluation using vendor-independent speckle-tracking software. The primary endpoint was new onset AF during 10 years after initial evaluation. Results The median age was 55.0 years and 74.3% were male. A median value of LA reservoir strain (LARS) was 26.2 % [interquartile range 20.4, 33.3]. Among the 696 patients, 66 had new onset AF 10 years, with a 10-year incidence of 15.8%. The unadjusted risk factors for new onset AF were previous stroke, non-apical HCM, family history of HCM, non-sustained ventricular tachycardia, obstructive HCM, extensive late gadolinium enhancement, larger LA diameter, larger LA volume, and lower LARS. LARS remained an independent predictor of new onset AF in multivariable analysis. The best cut-off value of LARS was 17.9% (hazard ratio 4.00, 95% confidence interval 2.44–6.55, p&amp;lt;0.001). Compared with LARS ≥17.9%, LARS &amp;lt;17.9% was significantly associated with a higher incidence of new onset AF, irrespective of presence of clinical risk factors (Figure 1) and LA enlargement (Figure 2). Conclusions In patients with HCM, low LA strain is an independent predictor of new onset AF.

Abstract 12822: Prediction of New-Onset Atrial Fibrillation in Patients With Hypertrophic Cardiomyopathy Using RNA-Sequencing of Plasma Small Non-Coding RNAs

Background: It is known that about 20% of patients with hypertrophic cardiomyopathy (HCM) develop atrial fibrillation (AF), which can lead to stroke and worsening of heart failure. The current clinical model to predict new-onset AF in patients with HCM (HCM-AF score) offers only modest accuracy. RNA-sequencing (RNA-Seq) can determine concentrations of thousands of small non-coding RNAs (sncRNAs) in plasma. Hypothesis/Aims: To test the hypothesis that RNA-Seq of plasma sncRNAs predicts new-onset AF in HCM. Methods: In this prospective, multi-center cohort study, we conducted RNA-Seq of 3,740 plasma sncRNAs at enrollment on 283 patients with HCM without a prior history of AF. The outcome was new-onset AF. We developed a sncRNA-Seq-based LASSO classification model (sncRNA-Seq-based model) to predict new-onset AF using data from one institution (training set, n=193). We tested the predictive ability of the model in independent samples from the other institutions (test set, n=90). We also developed a clinical model with LASSO using all components of HCM-AF score - i.e., left atrial diameter, age, age at HCM diagnosis, and New York Heart Association functional class ≥2. We then compared the area under the receiver-operating characteristic curve (AUC) between the sncRNA-Seq-based model and the clinical model in the test set. Results: During a median follow-up of 2.8 [1.9-5.1] years, 25 patients (13%) in the training set and 7 (8%) in the test set developed new-onset AF. Using the sncRNA-Seq-based model developed in the training set, the AUC to predict new-onset AF in the test set was 0.82 (95% confidence interval [CI] 0.71-0.94, Figure ). This model outperformed the clinical model (AUC 0.59; 95% CI 0.38-0.81; Delong’s test P=0.02). Conclusion: This study serves as the first to demonstrate the ability of plasma sncRNA-Seq to predict new-onset AF in patients with HCM. The prediction model may help physicians identify patients with HCM who are at high risk of developing new-onset AF.

Incorporating uric acid into the CHA2DS2-VASc score improves the prediction of new-onset atrial fibrillation in patients with acute myocardial infarction

BackgroundNew-onset atrial fibrillation (NOAF) is a common cardiac arrhythmia observed in patients with acute myocardial infarction (AMI) and is associated with worse outcomes. While uric acid has been proposed as a potential biomarker for predicting atrial fibrillation, its association with NOAF in patients with AMI and its incremental discriminative ability when added to the CHA2DS2-VASc score are not well established.MethodsWe conducted a retrospective analysis of 1000 consecutive patients with AMI without a history of atrial fibrillation between January 2018 and December 2020. Continuous electrocardiographic monitoring was performed during the patients’ hospital stay to detect NOAF. We assessed the predictive ability of the different scoring models using receiver operating characteristic (ROC) curves. In addition, we employed the area under the curve (AUC), integrated discrimination improvement (IDI), and net reclassification improvement (NRI) analyses to assess the incremental discriminative ability of uric acid when added to the CHA2DS2-VASc score.ResultsNinety-three patients (9.3%) developed NOAF during hospitalisation. In multivariate regression analyses, the adjusted odds ratio (OR) for NOAF was 1.439 per one standard deviation increase in uric acid level (95% confidence intervals (CI):1.182–1.753, p < 0.001). The ROC curve analysis revealed that the AUC for uric acid was 0.667 (95% CI:0.601–0.719), while the AUC for the CHA2DS2-VASc score was 0.678 (95% CI:0.623–0.734). After integrating the uric acid variable into the CHA2DS2-VASc score, the combined score yielded an improved AUC of 0.737 (95% CI:0.709–0.764, p = 0.009). Furthermore, there was a significant improvement in both IDI and NRI, indicating an incremental improvement in discriminative ability (IDI = 0.041, p < 0.001; NRI = 0.627, p < 0.001).ConclusionOur study suggests that uric acid level is an independent risk factor for the development of NOAF after AMI. Furthermore, the incorporation of uric acid into the CHA2DS2-VASc score significantly improves the discriminative ability of the score in identifying patients at high risk for NOAF.

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.

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. 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. 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). 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.

Does Atrial Fibrillation Deteriorate the Prognosis in Patients With Septic or Cardiogenic Shock?

Atrial fibrillation (AF) is associated with increased risk of mortality in various clinical conditions. However, the prognostic role of preexisting and new-onset AF in critically ill patients, such as patients with septic or cardiogenic shock remains unclear. This study investigates the prognostic impact of preexisting and new-onset AF on 30-day all-cause mortality in patients with septic or cardiogenic shock. Consecutive patients with sepsis, or septic or cardiogenic shock were enrolled in 2 prospective, monocentric registries from 2019 to 2021. Statistical analyses included Kaplan-Meier, multivariable logistic, and Cox proportional regression analyses. In total, 644 patients were included (cardiogenic shock: n=273; sepsis/septic shock: n=361). The prevalence of AF was 41% (29% with preexisting AF, 12% with new-onset AF). Within the entire study cohort, neither preexisting AF (log-rank p=0.542; hazard ratio [HR]1.075, 95% confidence interval [CI] 0.848 to 1.363, p=0.551) nor new-onset AF (log-rank p=0.782, HR=0.957, 95% CI 0.683 to 1.340, p=0.797) were associated with 30-day all-cause mortality compared with non-AF. In patients with AF, ventricular rates >120beats/min compared with ≤120beats/min were shown to increase the risk of reaching the primary end point in AF patients with cardiogenic shock (log-rank p=0.006, HR1.886, 95% CI 1.164 to 3.057, p=0.010). Furthermore, logistic regression analyses suggested increased age was the only predictor of new-onset AF (odds ratio1.042, 95% CI 1.018 to 1.066, p=0.001). In conclusion, neither the presence of preexisting AF nor the occurrence of new-onset AF was associated with the risk of 30-day all-cause mortality in consecutive patients admitted with cardiogenic shock.