Abstract:

Objective To conduct a scoping review of studies related to latent class trajectory analysis of glucose metabolism indicators in diabetes mellitus patients，so as to clarify the method of latent category trajectory analysis，evaluation indicators and the changing trajectories of different glucose metabolism indicators in diabetes mellitus patients，and to establish foundation for diabetes management and research. Methods Based on Arksey’s framework for scoping study，a literature search was performed in CNKI，Wanfang，CBM，Web of Science，PubMed，Embase，Cochrane Library，CINAHL database inception to January 28，2024. Totally 2 researchers independently screened the literature and extracted data. Results A total of 22 pieces of the literature were included. Latent class growth model was the most commonly used model in latent class trajectory analysis，and 4 softwares are available for implementation. The current evaluation indicators for trajectory results are various，with the Bayesian information criterion and average posterior probability as the most frequently utilized. Hemoglobin is the most commonly used glucose metabolism indicators for trajectory analysis，and the number of identified trajectories ranged from 2 to 5. Most studies showed that diabetic patients exhibited a “low-stable” pattern in glucose metabolism indicators. Conclusion Latent class trajectory analysis represents a novel longitudinal data analysis approach that can identify potential subgroups of diabetic patients with similar development trajectory. The models and evaluation indicators employed are diverse，and the stability test of the models can be enhanced in the future. Through trajectory identification，it is recommended that clinical staff pay greater attention to the longitudinal trend of the glucose metabolism indicators and incorporate it into the long-term blood glucose management goal of diabetic patients.

Key words: Diabetes Mellitus, Hemoglobin, Fasting Plasma Glucose, Latent Class Trajectory Analysis, Latent Class Growth Model, Scoping Review, Nursing Care

摘要：

目的 对糖尿病患者糖代谢指标潜类别轨迹分析的相关研究进行范围综述，明确糖尿病患者不同糖代谢指标的潜类别轨迹分析方法、评价指标及变化轨迹，为糖尿病管理和研究提供依据。 方法 基于Arksey等的范围综述框架，系统检索中国知网、万方数据库、中国生物医学文献数据库、Web of Science、PubMed、Embase、Cochrane Library、CINAHL等数据库，检索时限为建库至2024年1月28日。由2名研究者独立对文献进行筛选并提取资料。 结果 共纳入22篇文献，潜类别轨迹分析方法以潜类别增长模型运用最多，并有4个软件可供实现，目前对轨迹结果的评价指标多样，以贝叶斯信息准则和平均后验概率为主。糖化血红蛋白是最常用于轨迹分析的糖代谢指标，识别的轨迹数量为2~5条，大部分研究显示糖尿病患者的糖代谢指标处于“低水平-稳定”发展状态。结论 潜类别轨迹分析可识别糖尿病患者中具有相似发展轨迹的潜在类别，其采用的模型及评价指标具有多样性，未来可增加模型稳定性检验。通过轨迹识别，提示临床医护人员应多加关注糖代谢指标的纵向变化趋势，并将其纳入糖尿病患者长期血糖管理目标中。

关键词: 糖尿病, 糖化血红蛋白, 空腹血糖, 潜类别轨迹分析, 潜类别增长模型, 范围综述, 护理