Liverpool Centre for Cardiovascular Science, Institute of Ageing and Chronic Disease, University of Liverpool, William Henry Duncan Building, 6 West Derby Street, Liverpool, L7 8TX, UK.
Department of Translational and Precision Medicine, Sapienza - University of Rome, Rome, Italy.
BMC Med. 2024 Apr 8;22(1):151. doi: 10.1186/s12916-024-03373-4.
Clinical complexity, as the interaction between ageing, frailty, multimorbidity and polypharmacy, is an increasing concern in patients with AF. There remains uncertainty regarding how combinations of comorbidities influence management and prognosis of patients with atrial fibrillation (AF). We aimed to identify phenotypes of AF patients according to comorbidities and to assess associations between comorbidity patterns, drug use and risk of major outcomes.
From the prospective GLORIA-AF Registry, we performed a latent class analysis based on 18 diseases, encompassing cardiovascular, metabolic, respiratory and other conditions; we then analysed the association between phenotypes of patients and (i) treatments received and (ii) the risk of major outcomes. Primary outcome was the composite of all-cause death and major adverse cardiovascular events (MACE). Secondary exploratory outcomes were also analysed.
32,560 AF patients (mean age 70.0 ± 10.5 years, 45.4% females) were included. We identified 6 phenotypes: (i) low complexity (39.2% of patients); (ii) cardiovascular (CV) risk factors (28.2%); (iii) atherosclerotic (10.2%); (iv) thromboembolic (8.1%); (v) cardiometabolic (7.6%) and (vi) high complexity (6.6%). Higher use of oral anticoagulants was found in more complex groups, with highest magnitude observed for the cardiometabolic and high complexity phenotypes (odds ratio and 95% confidence interval CI): 1.76 [1.49-2.09] and 1.57 [1.35-1.81], respectively); similar results were observed for beta-blockers and verapamil or diltiazem. We found higher risk of the primary outcome in all phenotypes, except the CV risk factor one, with highest risk observed for the cardiometabolic and high complexity groups (hazard ratio and 95%CI: 1.37 [1.13-1.67] and 1.47 [1.24-1.75], respectively).
Comorbidities influence management and long-term prognosis of patients with AF. Patients with complex phenotypes may require comprehensive and holistic approaches to improve their prognosis.
临床复杂性是指衰老、虚弱、多种合并症和多种药物治疗之间的相互作用,在患有 AF 的患者中越来越受到关注。目前仍不确定合并症的组合如何影响心房颤动(AF)患者的管理和预后。我们旨在根据合并症确定 AF 患者的表型,并评估合并症模式、药物使用与主要结局风险之间的关联。
我们从前瞻性 GLORIA-AF 登记处中,基于 18 种疾病(包括心血管、代谢、呼吸和其他疾病)进行了潜在类别分析;然后分析了患者表型与(i)所接受的治疗和(ii)主要不良心血管事件(MACE)风险之间的关联。主要结局是全因死亡和主要不良心血管事件(MACE)的复合结局。还分析了次要探索性结局。
共纳入 32560 例 AF 患者(平均年龄 70.0±10.5 岁,45.4%为女性)。我们确定了 6 种表型:(i)低复杂性(39.2%的患者);(ii)心血管(CV)危险因素(28.2%);(iii)动脉粥样硬化(10.2%);(iv)血栓栓塞(8.1%);(v)心脏代谢(7.6%)和(vi)高复杂性(6.6%)。在更复杂的组中发现了更高的口服抗凝剂使用率,其中心脏代谢和高复杂性表型的幅度最大(比值比和 95%置信区间 CI):1.76[1.49-2.09]和 1.57[1.35-1.81]);β受体阻滞剂和维拉帕米或地尔硫卓也观察到类似的结果。我们发现所有表型的主要结局风险均升高,除了心血管危险因素表型外,其中心脏代谢和高复杂性组的风险最高(风险比和 95%CI:1.37[1.13-1.67]和 1.47[1.24-1.75])。
合并症会影响 AF 患者的管理和长期预后。复杂表型的患者可能需要全面的整体方法来改善其预后。