Yang Chen , Bi Huang , Peter Calvert , Yang Liu , Ying Gue , Dhiraj Gupta , Garry McDowell , Jinbert Lordson Azariah , Narayanan Namboodiri , Govindan Unni , Jayagopal Pathiyil Balagopalan , Gregory Yoke Hong Lip , Bahuleyan Charantharayil Gopalan
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Outcomes were all-cause mortality, major adverse cardiovascular events (MACE), and composite bleeding events within one-year follow-up.</div></div><div><h3>Findings</h3><div>3348 patients were included (median age 65.0 [56.0–74.0] years; 48.8% male; median CHA<sub>2</sub>DS<sub>2</sub>-VASc 3.0 [2.0–4.0]). Five clusters were identified. Cluster 1: patients aged ≤65 years with rheumatic conditions; Cluster 2: patients aged >65 years with multi-comorbidities, suggestive of cardiovascular-kidney-metabolic syndrome; Cluster 3: patients aged ≤65 years with fewer comorbidities; Cluster 4: heart failure patients with multiple comorbidities; Cluster 5: male patients with lifestyle-related risk factors. Cluster 1, 2 and 4 had significantly higher MACE risk compared to Cluster 3 (Cluster 1: OR 1.36, 95% CI 1.08–1.71; Cluster 2: OR 1.79, 95% CI 1.42–2.25; Cluster 4: OR 1.76, 95% CI 1.31–2.36). The results for other outcomes were similar. Atrial fibrillation Better Care (ABC) pathway in the whole cohort was low (10.1%), especially in Cluster 4 (1.9%). Overall adherence to the ABC pathway was associated with reduced all-cause mortality (OR 0.26, 95% CI 0.15–0.46) and MACE (OR 0.45, 95% CI 0.31–0.46), similar trends were evident in different clusters.</div></div><div><h3>Interpretation</h3><div>Cluster analysis identified distinct phenotypes with implications for outcomes. There was poor ABC pathway adherence overall, but adherence to such integrated care was associated with improved outcomes.</div></div><div><h3>Funding</h3><div>Kerala Chapter of <span>Cardiological Society of India</span>.</div></div>","PeriodicalId":75136,"journal":{"name":"The Lancet regional health. 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Cluster analysis, a machine learning method for classifying patients with similar phenotypes, has not yet been used in South Asian AF patients.</div></div><div><h3>Methods</h3><div>The Kerala Atrial Fibrillation Registry is a prospective multicentre cohort study in Kerala, India, and the largest prospective AF registry in South Asia. Hierarchical clustering was used to identify different phenotypic clusters. Outcomes were all-cause mortality, major adverse cardiovascular events (MACE), and composite bleeding events within one-year follow-up.</div></div><div><h3>Findings</h3><div>3348 patients were included (median age 65.0 [56.0–74.0] years; 48.8% male; median CHA<sub>2</sub>DS<sub>2</sub>-VASc 3.0 [2.0–4.0]). Five clusters were identified. 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引用次数: 0
摘要
背景心房颤动(房颤)患者经常患有多种疾病。方法喀拉拉邦心房颤动登记是印度喀拉拉邦的一项前瞻性多中心队列研究,也是南亚最大的前瞻性心房颤动登记。该研究采用层次聚类方法来识别不同的表型集群。研究结果共纳入 3348 名患者(中位年龄 65.0 [56.0-74.0] 岁;48.8% 为男性;中位 CHA2DS2-VASc 3.0 [2.0-4.0])。确定了五个群组。群组1:年龄小于65岁、患有风湿病的患者;群组2:年龄大于65岁、患有多种合并症、提示心血管-肾脏-代谢综合征的患者;群组3:年龄小于65岁、合并症较少的患者;群组4:患有多种合并症的心衰患者;群组5:具有生活方式相关风险因素的男性患者。与组群3相比,组群1、2和4的MACE风险明显更高(组群1:OR 1.36,95% CI 1.08-1.71;组群2:OR 1.79,95% CI 1.42-2.25;组群4:OR 1.76,95% CI 1.31-2.36)。其他结果类似。心房颤动更好护理(ABC)路径在整个队列中的比例较低(10.1%),尤其是在群组 4 中(1.9%)。总体而言,坚持ABC路径与全因死亡率(OR 0.26,95% CI 0.15-0.46)和MACE(OR 0.45,95% CI 0.31-0.46)的降低有关,不同群组的趋势相似。总体而言,ABC路径的依从性较差,但这种综合护理的依从性与预后的改善相关。
Phenotypes of South Asian patients with atrial fibrillation and holistic integrated care management: cluster analysis of data from KERALA-AF Registry
Background
Patients with atrial fibrillation (AF) frequently experience multimorbidity. Cluster analysis, a machine learning method for classifying patients with similar phenotypes, has not yet been used in South Asian AF patients.
Methods
The Kerala Atrial Fibrillation Registry is a prospective multicentre cohort study in Kerala, India, and the largest prospective AF registry in South Asia. Hierarchical clustering was used to identify different phenotypic clusters. Outcomes were all-cause mortality, major adverse cardiovascular events (MACE), and composite bleeding events within one-year follow-up.
Findings
3348 patients were included (median age 65.0 [56.0–74.0] years; 48.8% male; median CHA2DS2-VASc 3.0 [2.0–4.0]). Five clusters were identified. Cluster 1: patients aged ≤65 years with rheumatic conditions; Cluster 2: patients aged >65 years with multi-comorbidities, suggestive of cardiovascular-kidney-metabolic syndrome; Cluster 3: patients aged ≤65 years with fewer comorbidities; Cluster 4: heart failure patients with multiple comorbidities; Cluster 5: male patients with lifestyle-related risk factors. Cluster 1, 2 and 4 had significantly higher MACE risk compared to Cluster 3 (Cluster 1: OR 1.36, 95% CI 1.08–1.71; Cluster 2: OR 1.79, 95% CI 1.42–2.25; Cluster 4: OR 1.76, 95% CI 1.31–2.36). The results for other outcomes were similar. Atrial fibrillation Better Care (ABC) pathway in the whole cohort was low (10.1%), especially in Cluster 4 (1.9%). Overall adherence to the ABC pathway was associated with reduced all-cause mortality (OR 0.26, 95% CI 0.15–0.46) and MACE (OR 0.45, 95% CI 0.31–0.46), similar trends were evident in different clusters.
Interpretation
Cluster analysis identified distinct phenotypes with implications for outcomes. There was poor ABC pathway adherence overall, but adherence to such integrated care was associated with improved outcomes.