吴苏, 王菁菁, 蔡桂兰, 甄勇. 基于潜变量混合增长模型预测颅内动脉瘤手术患者治疗依从性的影响因素[J]. 实用临床医药杂志, 2024, 28(8): 99-103, 108. DOI: 10.7619/jcmp.20233758
引用本文: 吴苏, 王菁菁, 蔡桂兰, 甄勇. 基于潜变量混合增长模型预测颅内动脉瘤手术患者治疗依从性的影响因素[J]. 实用临床医药杂志, 2024, 28(8): 99-103, 108. DOI: 10.7619/jcmp.20233758
WU Su, WANG Jingjing, CAI Guilan, ZHEN Yong. Influence factors of treatment compliance in patients undergoing intracranial aneurysm surgery based on latent growth mixture model[J]. Journal of Clinical Medicine in Practice, 2024, 28(8): 99-103, 108. DOI: 10.7619/jcmp.20233758
Citation: WU Su, WANG Jingjing, CAI Guilan, ZHEN Yong. Influence factors of treatment compliance in patients undergoing intracranial aneurysm surgery based on latent growth mixture model[J]. Journal of Clinical Medicine in Practice, 2024, 28(8): 99-103, 108. DOI: 10.7619/jcmp.20233758

基于潜变量混合增长模型预测颅内动脉瘤手术患者治疗依从性的影响因素

Influence factors of treatment compliance in patients undergoing intracranial aneurysm surgery based on latent growth mixture model

  • 摘要:
    目的 基于潜变量混合增长模型(LGMM)分析颅内动脉瘤(IA)手术患者治疗依从性的影响因素。
    方法 选取接受IA手术的150例患者为研究对象。收集患者一般资料, 采用治疗依从性量表评估患者依从性。应用LGMM预测IA术后患者治疗依从性的变化轨迹,并通过多因素Logistic回归分析法分析IA患者治疗依从性的影响因素。
    结果 本研究共回收有效问卷138份,有效问卷回收率为92.00%。IA术后患者治疗依从性得分为(5.18±1.59)分。经LGMM拟合后,选取3个潜在剖面。依从性好的患者为37例(26.81%), 依从性中等的患者为42例(30.43%), 依从性差的患者为59例(42.75%)。依从性好患者的潜在剖面类别归属概率矩阵为97.29%, 依从性中等患者为95.24%, 依从性差患者为98.31%。依从性差患者中年龄为30~50岁、初中及以下文化水平、合并2种及以上疾病、自费(医疗费用)和Hunt-Hess分级为Ⅲ级者占比高于依从性好患者和依从性中等患者,差异有统计学意义(P<0.05)。年龄30~50岁、Hunt-Hess分级为Ⅲ级、合并2种及以上疾病、文化程度为初中及以下、自费(医疗费用)是治疗依从性的影响因素(P<0.05)。
    结论 IA手术患者治疗依从性较低,且存在异质性。年龄为30~50岁、初中及以下文化水平、合并2种及以上疾病、医疗费用支付方式为自费以及Hunt-Hess分级为Ⅲ级均为IA手术患者依从性的影响因素。

     

    Abstract:
    Objective To analyze the influencing factors of treatment compliance in patients undergoing intracranial aneurysm (IA) surgery based on based on latent growth mixture model (LGMM).
    Methods A total of 150 patients who underwent IA surgery were selected as the study objects. The general data of patients were collected and the compliance scale was used to evaluate the compliance of patients. LGMM was used to predict the change track of treatment compliance of patients with IA after surgery, and the influencing factors of treatment compliance of patients with IA were analyzed by multivariate Logistic regression analysis.
    Results A total of 138 valid questionnaires were collected in this study, and the effective questionnaire recovery rate was 92.00%. The treatment compliance score of patients with IA was (5.18±1.59) points. After LGMM fitting, 3 potential profiles were selected. There were 37 patients with good compliance (26.81%), 42 patients with moderate compliance (30.43%), and 59 patients with poor compliance (42.75%). The potential profile category attribution probability matrix was 97.29% for patients with good compliance, 95.24% for patients with moderate compliance, and 98.31% for patients with poor compliance. The proportion of poor compliance patients with age of 30 to 50 years old, junior high school education level or below, combined with two or more diseases, out-of-pocket (medical expenses) and Hunt-Hess grade Ⅲ was significantly higher than those with good compliance and moderate compliance (P < 0.05). Age of 30 to 50 years old, Hunt-Hess grade Ⅲ, combined with two or more diseases, education level as junior high school or below and self-expense (medical expenses) were the influential factors of treatment compliance (P < 0.05).
    Conclusion Treatment compliance of patients undergoing IA surgery is low and heterogeneous. Age of 30 to 50 years old, junior high school education level or below, combination of more than two diseases, medical insurance payment method of self-payment and Hunt-Hess grade Ⅲ are all influencing factors for compliance of IA surgery patients.

     

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