2026 年第 7 期 第 21 卷

冠心病患者认知功能和睡眠质量与心理症状的潜在剖面分析及其影响因素研究

Latent profile analysis and its influencing factors research on cognitive function, sleep quality and psychological symptoms in patients with coronary atherosclerotic heart disease

作者：营晓张喜维崔永慧阚雅雯李晶刘瑀曾勇

英文作者：Ying Xiao Zhang Xiwei Cui Yonghui Kan Yawen Li Jing Liu Yu Zeng Yong

单位：首都医科大学附属北京安贞医院冠心病中心，北京100029

英文单位：Coronary Heart Disease Center Beijing Anzhen Hospital Capital Medical University Beijing 100029 China

关键词：冠心病（冠状动脉粥样硬化性心脏病）；认知功能；睡眠质量；情绪状态；潜在剖面分析

英文关键词：Coronaryatheroscleroticheartdisease;Cognitivefunction;Sleepquality;Emotionalstatus;Latentprofileanalysis

• 摘要：

• 目的 探讨冠心病（冠状动脉粥样硬化性心脏病）患者在认知功能、睡眠质量与情绪状态方面的潜在分类特征，并分析其影响因素。方法 选取2021年12月至2023年4月就诊于首都医科大学附属北京安贞医院的5 413例冠心病患者为研究对象。运用潜在剖面分析识别患者认知功能、睡眠质量与情绪状态的潜在类别。采用蒙特利尔认知评估量表、匹兹堡睡眠质量指数、焦虑自评量表及抑郁自评量表分别评估认知功能、睡眠质量、焦虑及抑郁状态。采用多元Logistic回归分析探讨各亚组的影响因素。结果 冠心病患者认知功能、睡眠质量与情绪状态可划分为3个潜在类别：稳态适应组2 800例（51.7%）、风险过渡组2 371例（43.8%）、高负荷症状群组242例（4.5%）。3组患者性别、文化程度分布、脑血管病史、吸烟史分布、饮酒史分布、体重指数分布比例和年龄水平比较，差异均有统计学意义（均P<0.05）。3组患者蒙特利尔认知评估量表总分、匹兹堡睡眠质量指数总分、焦虑自评量表总分、抑郁自评量表总分水平、轻度认知障碍、睡眠质量异常、焦虑、抑郁比例比较，差异均有统计学意义（均P<0.05）。多因素Logistic回归分析结果显示，年龄增加、女性、有脑血管病史以及低体重是患者归属高负荷症状群组的独立影响因素；年龄增加（比值比=1.014，95%置信区间：1.008~1.020，P<0.001）、女性（比值比=0.766，95%置信区间：0.662~0.886，P<0.001）以及不饮酒（比值比=1.267，95%置信区间：1.053~1.526，P=0.012）是患者归属风险过渡组的独立影响因素。结论 冠心病患者的认知功能、睡眠质量与情绪状态存在明显的异质性，临床护理应重点识别高龄、女性、低体重指数及合并脑血管病史的高危人群，并根据不同剖面特征实施个体化精准干预，以改善患者预后。

• Objective To explore latent classification characteristics of cognitive function, sleep quality and emotional status in patients with coronary atherosclerotic heart disease, and analyze relevant influencing factors. Methods A total of 5 413 patients with coronary atherosclerotic heart disease admitted to Beijing Anzhen Hospital, Capital Medical University from December 2021 to April 2023 were enrolled. Latent profile analysis was performed to identify latent subgroups based on cognitive function, sleep quality and emotional status. Montreal cognitive assessment, pittsburgh sleep quality index, self-rating anxiety scale and self-rating depression scale were applied to evaluate cognitive function, sleep quality, anxiety and depression respectively. Multinomial Logistic regression was used to analyze influencing factors of each subgroup. Results All subjects were divided into three latent subgroups: stable adaptation group (2 800 cases, 51.7%), transitional risk group (2 371 cases, 43.8%) and high-symptom-burden group (242 cases, 4.5%). There were statistically significant differences in gender, educational attainment, history of cerebrovascular disease, smoking status, drinking status, body mass index and age among the three groups (all P<0.05). There were significant differences in the total scores of the Montreal cognitive assessment, pittsburgh sleep quality index, self-rating anxiety scale and self-rating depression scale, as well as the proportions of mild cognitive impairment, abnormal sleep quality, anxiety and depression among the three groups (all P<0.05). Multivariate Logistic regression revealed that advanced age, female sex, cerebrovascular disease history and low body weight were independent predictors for classification into the high-symptom-burden group; increased age (odds ratio=1.014, 95%confidence interval:1.008-1.020, P<0.001), female gender (odds ratio=0.766, 95%confidence interval:0.662-0.886, P<0.001) and non-drinking habit (odds ratio=1.267, 95%confidence interval:1.053-1.526, P=0.012) were independent influencing factors for inclusion in the transitional risk group. Conclusion Obvious heterogeneity exists in cognitive function, sleep quality and emotional status among coronary atherosclerotic heart disease patients. Clinical nursing should screen high-risk populations including elderly, female, low body mass index and patients complicated with cerebrovascular diseases, and carry out individualized precise interventions corresponding to different profile characteristics so as to improve clinical prognosis.