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全国范围内使用筛查算法的临床心房颤动发生率及相关并发症。

Incidence of clinical atrial fibrillation and related complications using a screening algorithm at a nationwide level.

机构信息

Department of Cardiology, Centre Hospitalier Universitaire Dijon Bourgogne, Dijon, France.

Department of Cardiology, Centre Hospitalier Universitaire Trousseau and University François Rabelais, Tours, France.

出版信息

Europace. 2023 May 19;25(5). doi: 10.1093/europace/euad063.

Abstract

AIMS

In a recent position paper, the European Heart Rhythm Association (EHRA) proposed an algorithm for the screening and management of arrhythmias using digital devices. In patients with prior stroke, a systematic screening approach for atrial fibrillation (AF) should always be implemented, preferably immediately after the event. Patients with increasing age and with specific cardiovascular or non-cardiovascular comorbidities are also deemed to be at higher risk. From a large nationwide database, the aim was to analyse AF incidence rates derived from this new EHRA algorithm.

METHODS AND RESULTS

Using the French administrative hospital discharge database, all patients hospitalized in 2012 without a history of AF, and with at least a 5-year follow-up (FU) (or if they died earlier), were included. The yearly incidence of AF was calculated in each subgroup defined by the algorithm proposed by EHRA based on a history of previous stroke, increasing age, and eight comorbidities identified via International Classification of Diseases 10th Revision codes. Out of the 4526 104 patients included (mean age 58.9 ± 18.9 years, 64.5% women), 1% had a history of stroke. Among those with no history of stroke, 18% were aged 65-74 years and 21% were ≥75 years. During FU, 327 012 patients had an incidence of AF (yearly incidence 1.86% in the overall population). Implementation of the EHRA algorithm divided the population into six risk groups: patients with a history of stroke (group 1); patients > 75 years (group 2); patients aged 65-74 years with or without comorbidity (groups 3a and 3b); and patients < 65 years with or without comorbidity (groups 4a and 4b). The yearly incidences of AF were 4.58% per year (group 2), 6.21% per year (group 2), 3.50% per year (group 3a), 2.01% per year (group 3b), 1.23% per year (group 4a), and 0.35% per year (group 4b). In patients aged < 65 years, the annual incidence of AF increased progressively according to the number of comorbidities from 0.35% (no comorbidities) to 9.08% (eight comorbidities). For those aged 65-75 years, the same trend was observed, i.e. increasing from 2.01% (no comorbidities) to 11.47% (eight comorbidities).

CONCLUSION

These findings at a nationwide scale confirm the relevance of the subgroups in the EHRA algorithm for identifying a higher risk of AF incidence, showing that older patients (>75 years, regardless of comorbidities) have a higher incidence of AF than those with prior ischaemic stroke. Further studies are needed to evaluate the usefulness of algorithm-based risk stratification strategies for AF screening and the impact of screening on major cardiovascular event rates.

摘要

目的

在最近的一份立场文件中,欧洲心律协会(EHRA)提出了一种使用数字设备筛查和管理心律失常的算法。在既往有卒中的患者中,应始终实施系统的房颤(AF)筛查方法,最好在事件发生后立即进行。年龄增长以及存在特定心血管或非心血管合并症的患者也被认为具有更高的风险。本研究旨在利用来自大型全国性数据库的数据,分析源自这一新 EHRA 算法的 AF 发生率。

方法和结果

利用法国医院行政出院数据库,纳入了所有 2012 年无 AF 病史且至少随访 5 年(或更早死亡)的住院患者。根据 EHRA 基于既往卒中史、年龄增长和通过国际疾病分类第 10 版代码确定的 8 种合并症提出的算法,计算各亚组的 AF 发生率。在纳入的 4526104 例患者中(平均年龄 58.9±18.9 岁,64.5%为女性),1%有卒中史。在无卒中史的患者中,18%年龄为 65-74 岁,21%年龄≥75 岁。在随访期间,有 327012 例患者发生了 AF(总体人群的年发生率为 1.86%)。EHRA 算法的实施将人群分为 6 个风险组:有卒中史的患者(第 1 组);年龄>75 岁的患者(第 2 组);年龄 65-74 岁且有或无合并症的患者(第 3a 和 3b 组);年龄<65 岁且有或无合并症的患者(第 4a 和 4b 组)。AF 的年发生率分别为 4.58%/年(第 2 组)、6.21%/年(第 2 组)、3.50%/年(第 3a 组)、2.01%/年(第 3b 组)、1.23%/年(第 4a 组)和 0.35%/年(第 4b 组)。在年龄<65 岁的患者中,AF 的年发生率根据合并症的数量从 0.35%(无合并症)逐渐增加至 9.08%(8 种合并症)。对于年龄为 65-75 岁的患者,也观察到了同样的趋势,即从 2.01%(无合并症)增加至 11.47%(8 种合并症)。

结论

这些全国范围内的研究结果证实了 EHRA 算法中各亚组对于识别更高 AF 发生率风险的相关性,表明年龄较大的患者(>75 岁,无论是否存在合并症)的 AF 发生率高于既往有缺血性卒中的患者。需要进一步研究来评估基于算法的风险分层策略对 AF 筛查的有效性以及筛查对主要心血管事件发生率的影响。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3a73/10227657/2e3487684b17/euad063_ga1.jpg

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