Zheng Xiaoqing, Wang Ya, Wang Hongxing, Guan Minfang, Chen Xiaosong, Li Shasha, Zhang Wanluan, Hu Jiamiao, Ye Qiaoling, Xu Qinhong
Cardiovascular Internal Medicine Ward, The First Affiliated Hospital of Ningbo University, 315000 Ningbo, Zhejiang, China.
Cardiovascular Internal Medicine Ward, The Yangming Hospital Affiliated to Ningbo University, 315400 Yuyao, Zhejiang, China.
Rev Cardiovasc Med. 2025 Aug 19;26(8):37270. doi: 10.31083/RCM37270. eCollection 2025 Aug.
To explore the potential categories of compliance development track of dual antiplatelet therapy (DAPT) after percutaneous coronary intervention (PCI) in patients with acute coronary syndrome (ACS) using growth mixture modeling (GMM) to analyze its predictive factors, providing evidence for dynamic adherence monitoring and tailored interventions.
A total of 150 patients with ACS after PCI were selected by convenience sampling. Patients were studied using Self-Efficacy for Appropriate Medication Use Scale (SEAMS), family APGAR index (APGAR), Generalized Anxiety Disorder-2 (GAD-2), and Patient Health Questionnaire-2 (PHQ-2) at baseline. The compliance of patients with DAPT was assessed using Morisky Medication Adherence Scales-8 (MMAS-8) at 1, 3, 6, 9, and 12 months after discharge. The mixed model of latent variable growth was used to identify the development track of compliance. Multiple logistic regression was used to analyze the predictive factors of different development track categories.
Two development track categories of DAPT compliance in patients with ACS after PCI were identified in the low compliance-decreased group (7.41%) and the persistent high compliance group (92.59%). Multivariate logistic regression analysis showed that age ≥60 years, body mass index (BMI), and the family APGAR index were the predictive factors of different development track categories of DAPT compliance in patients with ACS after PCI.
Significant population heterogeneity was observed in the development track of DAPT in ACS patients within 12 months after PCI. The compliance of most patients remained stable, and only a few remained at a low level and showed a significant downward trend. Based on these predictive factors, healthcare personnel can identify patients in the low compliance-decreased group early and implement targeted and specific interventions to improve DAPT compliance of ACS patients after PCI.
采用生长混合模型（GMM）探索急性冠状动脉综合征（ACS）患者经皮冠状动脉介入治疗（PCI）后双重抗血小板治疗（DAPT）依从性发展轨迹的潜在类别，分析其预测因素，为动态依从性监测和个性化干预提供依据。
采用方便抽样法选取150例PCI术后ACS患者。在基线时使用合理用药自我效能量表（SEAMS）、家庭APGAR指数（APGAR）、广泛性焦虑障碍-2（GAD-2）和患者健康问卷-2（PHQ-2）对患者进行研究。在出院后1、3、6、9和12个月，使用Morisky药物依从性量表-8（MMAS-8）评估患者DAPT的依从性。采用潜在变量增长混合模型确定依从性的发展轨迹。采用多因素logistic回归分析不同发展轨迹类别的预测因素。
在PCI术后ACS患者中，DAPT依从性分为低依从性下降组（7.41%）和持续高依从性组（92.59%）两个发展轨迹类别。多因素logistic回归分析显示，年龄≥60岁、体重指数（BMI）和家庭APGAR指数是PCI术后ACS患者DAPT依从性不同发展轨迹类别的预测因素。
PCI术后12个月内，ACS患者DAPT的发展轨迹存在显著的人群异质性。大多数患者的依从性保持稳定，只有少数患者依从性处于低水平且呈显著下降趋势。基于这些预测因素，医护人员可以早期识别低依从性下降组的患者，并实施有针对性的具体干预措施，以提高PCI术后ACS患者的DAPT依从性。
