Li Yanguang, Li Qiaoyuan, Wang Lili, Zhang Tao, Gao Hai, Pastori Daniele, Liang Zhuo, Lip Gregory Y H, Wang Yunlong
Department of Cardiology, Beijing Anzhen Hospital, Capital Medical University, Beijing, China.
Department of Clinical Internal, Anesthesiological and Cardiovascular Sciences, Sapienza University of Rome, Rome, Italy.
JACC Adv. 2025 Jan 10;4(2):101521. doi: 10.1016/j.jacadv.2024.101521. eCollection 2025 Feb.
Assessing individuals' risk of developing incident atrial fibrillation (AF) is important for making preventive and screening strategies.
The performance of the mCHEST score for predicting incident AF has scarcely been evaluated, especially in a multi-ethnic population.
Participants from the MESA (Multi-Ethnic Study of Atherosclerosis were enrolled in the present study, which involved population of different ethnicities (Caucasian, African-American, Chinese-American, and Hispanic) aged between 45 and 84 from 6 communities in the United States. The discriminative and calibration performance of the mCHEST score was compared with other risk models.
A total of 4,524 subjects (mean age 60.2 ± 9.5 years; 53.0% female) were included; 565 (mean age 67.0 ± 7.9 years; 46.5% female) developed AF during 13.6 ± 2.5 years of follow-up, with an incidence of 0.93%/year. The mCHEST score had good prediction at 10 years (C-index, 0.72; 95% CI: 0.701 to 0.753), and 15 years (0.773, 95% CI: 0.749 to 0.798). The risk of incident AF increased with higher mCHEST score points and risk groups (log-rank < 0.001). The mCHEST score showed positive net reclassification indexes (0.057, 0.090, 0.128, and 0.143) and integrated discriminative improvement (3.2%, 3.9%, 5.7%, and 4.9%) compared with CHEST, HAVOC, HATCH, and CHADS-VASc scores, respectively. Optimal calibration was seen in the mCHEST score ( = 0.41).
The mCHEST score is a practical model for predicting individuals' risk of incident AF that may be used for guiding AF surveillance, resource allocation, and screening strategies.
评估个体发生房颤（AF）的风险对于制定预防和筛查策略至关重要。
mCHEST评分预测房颤发生的性能几乎未被评估，尤其是在多民族人群中。
本研究纳入了动脉粥样硬化多民族研究（MESA）的参与者，该研究涉及来自美国6个社区、年龄在45至84岁之间的不同种族人群（白种人、非裔美国人、华裔美国人及西班牙裔）。将mCHEST评分的鉴别和校准性能与其他风险模型进行比较。
共纳入4524名受试者（平均年龄60.2±9.5岁；53.0%为女性）；在13.6±2.5年的随访期间，565名（平均年龄67.0±7.9岁；46.5%为女性）发生了房颤，年发病率为0.93%。mCHEST评分在10年时（C指数，0.72；95%CI：0.701至0.753）及15年时（0.773，95%CI：0.749至0.798）具有良好的预测能力。房颤发生风险随mCHEST评分及风险组升高而增加（对数秩检验<0.001）。与CHEST、HAVOC、HATCH及CHADS-VASc评分相比，mCHEST评分的净重新分类指数为正值（分别为0.057、0.090、0.128及0.143），综合鉴别改善率分别为3.2%、3.9%、5.7%及4.9%。mCHEST评分具有最佳校准（χ²=0.41）。
mCHEST评分是预测个体房颤发生风险的实用模型，可用于指导房颤监测、资源分配及筛查策略。
