应用多变量分析方法探索围绝经期的异质性。

Exploring heterogeneity of perimenopause with application of multivariable analysis approaches.

作者信息

Huang Zhongyu, You Huazhi, Li Lijuan, Wang Shuang, Lyu Zipan, Zeng Xiaoqin, Zhu Changyan, Li Minqing, Yan Han, He Yaojuan

机构信息

Institute of Clinical Medicine, Guangzhou First People's Hospital, Guangzhou Medical University, Guangzhou, 510000, China.

Spinal Orthopedics Department, Guangzhou First People's Hospital, Guangzhou Medical University, Guangzhou, 510000, China.

出版信息

BMC Womens Health. 2024 Dec 4;24(1):638. doi: 10.1186/s12905-024-03483-4.

DOI:10.1186/s12905-024-03483-4

PMID:39633406

原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11619569/

Abstract

OBJECTIVES

Heterogeneity of clinical appearance had made it a challenge to make individualized and comprehensive management of perimenopause. This study aimed to estimate the profiles over heterogenous appearances of perimenopause with application of latent variable analysis methods over an optimized multidimensional assessing framework.

METHODS

A two-phase clinical study was designed and advanced in the research center in Guangzhou, China. The assessing framework was developed over the initial item pool as integration of 4 scales including Insomnia severity index, Modified Kupperman index, Self-rating anxiety scale, and Self-rating depression scale. Validity and reliability of the instrument were evaluated and the psychometric properties of the items were estimated with multidimensional item response theory(MIRT). And then computer adaptive testing(CAT) was developed with the estimated model. We used latent profile analysis (LPA) to cluster patients into subgroups as patterns characterized by multidimensional latent trait scores. Finally, interpretability and efficiency were analyzed via comparison between the two assessing strategies.

RESULT

There were in total 336 patients diagnosed with perimenopause enrolled for the assessment. A conceptual framework was estimated consisting of 6 factors including sleep disturbance, mood swings, vasomotor symptoms, positive attitude towards life, multisystem abnormality, and fatigue. The construct validity was evaluated as optimized with CMIN/df = 1.814, GFI = 0.619, CFI = 0.721, TLI = 0.707 and RMSEA = 0.075. With scores in the simulated CAT, the 4 latent profiles model was estimated indicating the heterogeneity of perimenopause characterized by different severity of psychological and physical discomforts in the LPA.

CONCLUSION

The quantitative paradigm raised in this study revealed the potential patterns presenting heterogeneity of perimenopause offering better interpretation for clinical assessment.

摘要

目的

临床症状的异质性使得围绝经期的个体化综合管理成为一项挑战。本研究旨在通过在优化的多维评估框架上应用潜在变量分析方法，评估围绝经期异质症状的特征。

方法

在中国广州的研究中心设计并推进了一项两阶段临床研究。评估框架是在初始项目库的基础上开发的，整合了4个量表，包括失眠严重程度指数、改良库珀曼指数、自评焦虑量表和自评抑郁量表。评估了该工具的效度和信度，并用多维项目反应理论（MIRT）估计了项目的心理测量特性。然后根据估计模型开发了计算机自适应测试（CAT）。我们使用潜在剖面分析（LPA）将患者聚类为亚组，这些亚组以多维潜在特质分数为特征。最后，通过比较两种评估策略分析其可解释性和效率。

结果

共有336名被诊断为围绝经期的患者参与评估。估计了一个概念框架，包括6个因素，即睡眠障碍、情绪波动、血管舒缩症状、对生活的积极态度、多系统异常和疲劳。结构效度评估为优化，CMIN/df = 1.814，GFI = 0.619，CFI = 0.721，TLI = 0.707，RMSEA = 0.075。根据模拟CAT中的分数，估计了4个潜在剖面模型，表明围绝经期的异质性表现为LPA中心理和身体不适的不同严重程度。