Identification of atrial fibrillation phenotypes at low risk of stroke in patients with CHA2DS2‐VASc ≥2: Insight from the China‐AF study.
Objective: Patients with atrial fibrillation (AF) are highly heterogeneous, and current risk stratification scores are only modestly good at predicting an individual's stroke risk. We aim to identify distinct AF clinical phenotypes with cluster analysis to optimize stroke prevention practices. Metho...
| Publicado en: | Pacing & Clinical Electrophysiology Vol. 46; no. 10; pp. 1203 - 1212 |
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| Autores principales: | , , , , , , , , , , , , , , , , |
| Formato: | research tables/charts Journal Article |
| Publicado: |
Wiley-Blackwell
Oct2023
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=172893921&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 172893921 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 01478389 4F8 jtl: Pacing & Clinical Electrophysiology issn: 01478389 maglogo: Y pubinfo: dt: Oct2023 vid: 46 iid: 10 pid: 480 pub: Wiley-Blackwell place: Malden, Massachusetts artinfo: ui: 172893921 172257922 172893921 172893921 10.1111/pace.14829 172893921 ppf: 1203 ppct: 9 formats: fmt: – @attributes: type: T – @attributes: type: C – @attributes: type: P tig: atl: Identification of atrial fibrillation phenotypes at low risk of stroke in patients with CHA2DS2‐VASc ≥2: Insight from the China‐AF study. aug: au: Jiang, Chao Li, Mingxiao Hu, Yiying Du, Xin Li, Xiang He, Liu Lai, Yiwei Chen, Tiange Li, Yingxue Guo, Xueyuan Jiang, Chenxi Tang, Ribo Sang, Caihua Long, Deyong Xie, Guotong Dong, Jianzeng Ma, Changsheng affil: Department of Cardiology, Beijing Anzhen Hospital, Capital Medical University, National Clinical Research Center for Cardiovascular Diseases, Beijing, China sug: subj: Atrial Fibrillation Complications Phenotype Stroke Risk Factors Cardiac Patients Risk Assessment Human Male Female Cluster Analysis Prospective Studies Funding Source Registries, Disease China Anticoagulants Therapeutic Use Ischemic Stroke Risk Factors Thromboembolism Epidemiology Heart Failure Diabetes Mellitus Age Factors Aged Incidence Predictive Value of Tests Stroke Prevention and Control Aged: 65+ years Male Female ab: Objective: Patients with atrial fibrillation (AF) are highly heterogeneous, and current risk stratification scores are only modestly good at predicting an individual's stroke risk. We aim to identify distinct AF clinical phenotypes with cluster analysis to optimize stroke prevention practices. Methods: From the prospective Chinese Atrial Fibrillation Registry cohort study, we included 4337 AF patients with CHA2DS2‐VASc≥2 for males and 3 for females who were not treated with oral anticoagulation. We randomly split the patients into derivation and validation sets by a ratio of 7:3. In the derivation set, we used outcome‐driven patient clustering with metric learning to group patients into clusters with different risk levels of ischemic stroke and systemic embolism, and identify clusters of patients with low risks. Then we tested the results in the validation set, using the clustering rules generated from the derivation set. Finally, the survival decision tree was applied as a sensitivity analysis to confirm the results. Results: Up to the follow‐up of 1 year, 140 thromboembolic events (ischemic stroke or systemic embolism) occurred. After supervised metric learning from six variables involved in CHA2DS2‐VASc scheme, we identified a cluster of patients (255/3035, 8.4%) at an annual thromboembolism risk of 0.8% in the derivation set. None of the patients in the low‐risk cluster had prior thromboembolism, heart failure, diabetes, or age older than 70 years. After applying the regularities from metric learning on the validation set, we also identified a cluster of patients (137/1302, 10.5%) with an incident thromboembolism rate of 0.7%. Sensitivity analysis based on the survival decision tree approach selected a subgroup of patients with the same phenotypes as the metric‐learning algorithm. Conclusions: Cluster analysis identified a distinct clinical phenotype at low risk of stroke among high‐risk [CHA2DS2‐VASc≥2 (3 for females)] patients with AF. The use of the novel analytic approach has the potential to prevent a subset of AF patients from unnecessary anticoagulation and avoid the associated risk of major bleeding. pubtype: Academic Journal doctype: research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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