Identifying risk patterns in older adults with atrial fibrillation by hierarchical cluster analysis: A retrospective approach based on the risk probability for clinical events

[Cluster Analysis and Ablation Success Rate in Atrial Fibrillation Patients Undergoing Catheter Ablation]

Objective

Atrial fibrillation (AF) is a disease of high heterogeneity, and the association between AF phenotypes and the outcome of different catheter ablation strategies remains unclear. Conventional classification of AF (e.g. according to duration, atrial size, and thromboembolism risk) fails to provide reference for the optimal stratification of the prognostic risks or to guide individualized treatment plan. In recent years, research on machine learning has found that cluster analysis, an unsupervised data-driven approach, can uncover the intrinsic structure of data and identify clusters of patients with pathophysiological similarity. It has been demonstrated that cluster analysis helps improve the characterization of AF phenotypes and provide valuable prognostic information. In our cohort of AF inpatients undergoing radiofrequency catheter ablation, we used unsupervised cluster analysis to identify patient subgroups, to compare them with previous studies, and to evaluate their association with different suitable ablation patterns and outcomes.

Methods

The participants were AF patients undergoing radiofrequency catheter ablation at West China Hospital between October 2015 and December 2017. All participants were aged 18 years or older. They underwent radiofrequency catheter ablation during their hospitalization. They completed the follow-up process under explicit informed consent. Patients with AF of a reversible cause, severe mitral stenosis or prosthetic heart valve, congenital heart disease, new-onset acute coronary syndrome within three months prior to the surgery, or a life expectancy less than 12 months were excluded according to the exclusion criteria. The cohort consisted of 1102 participants with paroxysmal or persistent/long-standing persistent AF. Data on 59 variables representing demographics, AF type, comorbidities, therapeutic history, vital signs, electrocardiographic and echocardiographic findings, and laboratory findings were collected. Overall, data for the variables were rarely missing (<5%), and multiple imputation was used for correction of missing data. Follow-up surveys were conducted through outpatient clinic visits or by telephone. Patients were scheduled for follow-up with 12-lead resting electrocardiography and 24-hours Holter monitoring at 3 months and 6 months after the ablation procedure. Early ablation success was defined as the absence of documented AF, atrial flutter, or atrial tachycardia >30 seconds at 6-month follow-up. Hierarchical clustering was performed on the 59 baseline variables. All characteristic variables were standardized to have a mean of zero and a standard deviation of one. Initially, each patient was regarded as a separate cluster, and the distance between these clusters was calculated. Then, the Ward minimum variance method of clustering was used to merge the pair of clusters with the minimum total variance. This process continued until all patients formed one whole cluster. The "NbClust" package in R software, capable of calculating various statistical indices, including pseudo t2 index, cubic clustering criterion, silhouette index etc, was applied to determine the optimal number of clusters. The most frequently chosen number of clusters by these indices was selected. A heatmap was generated to illustrate the clinical features of clusters, while a tree diagram was used to depict the clustering process and the heterogeneity among clusters. Ablation strategies were compared within each cluster regarding ablation efficacy.

Results

Five statistically driven clusters were identified: 1) the younger age cluster (n=404), characterized by the lowest prevalence of cardiovascular and cerebrovascular comorbidities but the highest prevalence of obstructive sleep apnea syndrome (14.4%); 2) a cluster of elderly adults with chronic diseases (n=438), the largest cluster, showing relatively higher rates of hypertension, diabetes, stroke, and chronic obstructive pulmonary disease; 3) a cluster with high prevalence of sinus node dysfunction (n=160), with patients showing the highest prevalence of sick sinus syndrome and pacemaker implantation; 4) the heart failure cluster (n=80), with the highest prevalence of heart failure (58.8%) and persistent/long-standing persistent AF (73.7%); 5) prior coronary artery revascularization cluster (n=20), with patients of the most advanced age (median: 69.0 years old) and predominantly male patients, all of whom had prior myocardial infarction and coronary artery revascularization. Patients in cluster 2 achieved higher early ablation success with pulmonary veins isolation alone compared to extensive ablation strategies (79.6% vs. 66.5%; odds ratio [OR]=1.97, 95% confidence interval [CI]: 1.28-3.03). Although extensive ablation strategies had a slightly higher success rate in the heart failure group, the difference was not statistically significant.

Conclusions

This study provided a unique classification of AF patients undergoing catheter ablation by cluster analysis. Age, chronic disease, sinus node dysfunction, heart failure and history of coronary artery revascularization contributed to the formation of the five clinically relevant subtypes. These subtypes showed differences in ablation success rates, highlighting the potential of cluster analysis in guiding individualized risk stratification and treatment decisions for AF patients.

Characteristics and outcomes in elderly patients with non-valvular atrial fibrillation and high bleeding risk: subanalysis of the J-RHYTHM Registry

Recently, a once-daily dose of edoxaban (15-mg) has been approved for stroke prevention in non-valvular atrial fibrillation (NVAF) patients aged ≥ 80 years, in whom standard oral anticoagulants are not recommended because of high bleeding risk (HBR), based on the ELDERCARE-AF trial. However, information regarding the characteristics and clinical outcomes among such patients is limited. Thus, this study aimed to clarify the characteristics and event rates in elderly patients with NVAF and HBR defined by the ELDERCARE-AF criteria. Of the 7406 NVAF outpatients included in the J-RHYTHM Registry, 60 patients with creatinine clearance (CrCl) < 15 mL/min were excluded. The remaining 7346 patients (age, 69.7 ± 9.9 years; men, 70.9%; warfarin use, 78.7%) were divided into three groups: Group 1, aged < 80 years (n = 6165); Group 2, aged ≥ 80 years without HBR (n = 584); and Group 3, aged ≥ 80 years with HBR (at least one of the followings; CrCl, 15-30 mL/min, history of bleeding, body weight ≤ 45 kg, and antiplatelet use) (n = 597, eligible for 15-mg edoxaban). Patients in Group 3 had a higher prevalence of comorbidities, and therefore, both higher thromboembolic and bleeding risk scores than in the other groups. During the 2-year follow-up period, the incidence rates (per 100 person-years) of thromboembolism in Groups 1, 2, and 3 were 0.7, 1.5, and 2.1 (P < 0.001), major hemorrhage, 0.8, 1.2, and 2.0 (P < 0.001), and all-cause death, 0.8, 2.6, and 4.6 (P < 0.001), respectively. Adjusted hazard ratios of Group 3 were 1.64 (95% confidence interval 0.89-3.04, P = 0.116) for thromboembolism, 1.53 (0.85-2.72, P = 0.154) for major hemorrhage, and 1.84 (1.19-2.85, P = 0.006) for all-cause death compared with Group 1. The NVAF Patients aged ≥ 80 years with HBR defined by the ELDERCARE-AF criteria were certainly at a higher adverse event risk, especially for all-cause death. Clinical trial registration: The J-RHYTHM Registry is registered in the University Hospital Medicine Information Network (UMIN) Clinical Trials Registry (unique identifier: UMIN000001569) http://www.umin.ac.jp/ctr/ .

A Comparison of the Impact of Pharmacological Treatments on Cardioversion, Rate Control, and Mortality in Data-Driven Atrial Fibrillation Phenotypes in Critical Care

Critical care physicians are commonly faced with patients exhibiting atrial fibrillation (AF), a cardiac arrhythmia with multifaceted origins. Recent investigations shed light on the heterogeneity among AF patients by uncovering unique AF phenotypes, characterized by differing treatment strategies and clinical outcomes. In this retrospective study encompassing 9401 AF patients in an intensive care cohort, we sought to identify differences in average treatment effects (ATEs) across different patient groups. We extract data from the MIMIC-III database, use hierarchical agglomerative clustering to identify patients' phenotypes, and assign them to treatment groups based on their initial drug administration during AF episodes. The treatment options examined included beta blockers (BBs), potassium channel blockers (PCBs), calcium channel blockers (CCBs), and magnesium sulfate (MgS). Utilizing multiple imputation and inverse probability of treatment weighting, we estimate ATEs related to rhythm control, rate control, and mortality, approximated as hourly and daily rates (%/h, %/d). Our analysis unveiled four distinctive AF phenotypes: (1) postoperative hypertensive, (2) non-cardiovascular mutlimorbid, (3) cardiovascular multimorbid, and (4) valvulopathy atrial dilation. PCBs showed the highest cardioversion rates across phenotypes, ranging from 11.6%/h (9.35-13.3) to 7.69%/h (5.80-9.22). While CCBs demonstrated the highest effectiveness in controlling ventricular rates within the overall patient cohort, PCBs and MgS outperformed them in specific phenotypes. PCBs exhibited the most favorable mortality outcomes overall, except for the non-cardiovascular multimorbid cluster, where BBs displayed a lower mortality rate of 1.33%/d [1.04-1.93] compared to PCBs' 1.68%/d [1.10-2.24]. The results of this study underscore the significant diversity in ATEs among individuals with AF and suggest that phenotype-based classification could be a valuable tool for physicians, providing personalized insights to inform clinical decision making.

Clinical phenotypes of older adults with non-valvular atrial fibrillation not treated with oral anticoagulants by hierarchical cluster analysis in the ANAFIE Registry

BACKGROUND

Although anticoagulants are indicated for many elderly patients with non-valvular atrial fibrillation (NVAF), some patients do not receive anticoagulant therapy, whose characteristics and outcomes are diverse.

METHODS AND RESULTS

In this sub-analysis of the All Nippon AF In the Elderly (ANAFIE) Registry, the phenotypes of patients who were not receiving anticoagulants at baseline were evaluated by cluster analysis using Ward's linkage hierarchical algorithm. Of 32,275 enrolled patients, 2445 (7.6%) were not receiving anticoagulants. Two clusters were identified: (1) elderly paroxysmal AF (PAF) patients with a high proportion of catheter ablation history (57%) and (2) very elderly patients with a high prevalence of previous major bleeding (43%). Respective mean ages were 80.9 and 84.2 years, mean CHA2DS2-VASc scores were 3.8 and 4.9, PAF prevalences were 100.0% and 31.4%, proportions of patients with catheter ablation history were 21.0% and 7.9%, and proportions of patients with a history of major bleeding were 4.0% and 10.8%. Annual incidence rates were 2.72% and 8.81% for all-cause death, 1.66% and 5.85% for major adverse cardiovascular or neurological events, 1.08% and 3.30% for stroke or systemic embolism, and 0.69% and 1.19% for major bleeding, respectively.

CONCLUSIONS

In this cohort of elderly NVAF patients from the ANAFIE Registry who were not receiving anticoagulants, over half had PAF with a high proportion of catheter ablation history and a low incidence of adverse outcomes; for them, non-prescription of anticoagulants may be partially understandable, but they should be carefully monitored regarding AF burden or atrial cardiomyopathy and be adequately anticoagulated when adverse findings are detected. The remaining were very elderly patients with a high prevalence of previous major bleeding and a high incidence of adverse outcomes; for them, non-prescription of anticoagulants is inappropriate because of the high thromboembolic risk.

TRIAL REGISTRATION

Registration: http://www.umin.ac.jp/; Unique identifier: UMIN000024006.

Network Pharmacology and Pharmacological Mechanism of CV-3 in Atrial Fibrillation

The high fatality and disability rate of atrial fibrillation (AF) strongly promote the development of pathogenesis and treatment of AF that is of great value. The present research attempted to clarify potential mechanisms of Mujiangzi oil (CV-3) in treating AF by constructing an AF cardiomyocytes model and using a network pharmacology approach. The experiment was divided into 4 groups: control, an AF model, AF + CV-3-treated, and the AF + verapamil group. Flow cytometry and the MTT assay were employed to detect cell apoptosis and cell viability, respectively. The main active components of CV-3 and predicted targets were obtained firstly, and molecular docking was performed. In the AF model, the cell apoptosis was aggravated, but inhibited in the CV-3-treated group. In addition, the cell viability was recovered after CV-3 treatment compared with the model group. Five potential active compounds of CV-3 were collected, including effective ingredients N-decanoic acid, spathulenol, copaene, β-panasinsene, and eucalyptol. Among them, N-decanoic acid and spathulenol was demonstrated to bind to PTGS2 with binding energy of −4.08 and −7.09 kcal/mol, respectively, and hydrogen bonds interaction were found. The present study indicated that CV-3 could alleviate AF cardiomyocytes apoptosis and improve cardiomyocytes viability, and N-decanoic acid and spathulenol may be the key components of CV-3 in treatment of AF by regulating PTGS2. This study provided the possible target PTGS2 and the understanding of molecular mechanisms of CV-3 in treating AF.