Fanyu Meng, Wenwen Ou, Xiaotian Zhao, Mi Wang, Xiaowen Lu, Qiangli Dong, Liang Zhang, Jinrong Sun, Hua Guo, Futao Zhao, Mei Huang, Mohan Ma, Guanyi Lv, Yaqi Qin, Weihui Li, Zexuan Li, Mei Liao, Li Zhang, Jin Liu, Bangshan Liu, Yumeng Ju, Yan Zhang, Lingjiang Li
{"title":"识别重度抑郁障碍患者症状轨迹的潜在亚型及其预测因素。","authors":"Fanyu Meng, Wenwen Ou, Xiaotian Zhao, Mi Wang, Xiaowen Lu, Qiangli Dong, Liang Zhang, Jinrong Sun, Hua Guo, Futao Zhao, Mei Huang, Mohan Ma, Guanyi Lv, Yaqi Qin, Weihui Li, Zexuan Li, Mei Liao, Li Zhang, Jin Liu, Bangshan Liu, Yumeng Ju, Yan Zhang, Lingjiang Li","doi":"10.1007/s00406-024-01883-z","DOIUrl":null,"url":null,"abstract":"<p><p>This study aimed to identify different symptom trajectories based on the severity of depression symptoms within a 2-month follow-up, and to explore predictive factors for different symptom trajectories. Three hundred and ninety-two adults diagnosed with major depressive disorder (MDD) were recruited from two longitudinal cohorts. Patients received antidepressant treatment as usual, and the depression symptoms were evaluated by the 17-item Hamilton depression rating scale (HAMD-17) at baseline, two weeks, and eight weeks. Based on the HAMD-17 scores, different trajectories of symptom change were distinguished by applying Growth Mixture Modeling (GMM). Furthermore, the baseline sociodemographic, clinical, and cognitive characteristics were compared to identify potential predictors for different trajectories. Through GMM, three unique depressive symptom trajectories of MDD patients were identified: (1) mild-severity class with significant improvement (Mild, n = 255); (2) high-severity class with significant improvement (High, n = 39); (3) moderate-severity class with limited improvement (Limited, n = 98). Among the three trajectories, the Mild class had a relatively low level of anxiety symptoms at baseline, whereas the High class had the lowest education level and the worst cognitive performance. Additionally, participants in the Limited class exhibited an early age of onset and experienced a higher level of emotional abuse. MDD patients could be categorised into three distinct latent subtypes through different symptom trajectories in this study, and the characteristics of these subtype patients may inform identifications for trajectory-specific intervention targets.</p>","PeriodicalId":11822,"journal":{"name":"European Archives of Psychiatry and Clinical Neuroscience","volume":" ","pages":""},"PeriodicalIF":3.5000,"publicationDate":"2024-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Identifying latent subtypes of symptom trajectories in major depressive disorder patients and their predictors.\",\"authors\":\"Fanyu Meng, Wenwen Ou, Xiaotian Zhao, Mi Wang, Xiaowen Lu, Qiangli Dong, Liang Zhang, Jinrong Sun, Hua Guo, Futao Zhao, Mei Huang, Mohan Ma, Guanyi Lv, Yaqi Qin, Weihui Li, Zexuan Li, Mei Liao, Li Zhang, Jin Liu, Bangshan Liu, Yumeng Ju, Yan Zhang, Lingjiang Li\",\"doi\":\"10.1007/s00406-024-01883-z\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>This study aimed to identify different symptom trajectories based on the severity of depression symptoms within a 2-month follow-up, and to explore predictive factors for different symptom trajectories. Three hundred and ninety-two adults diagnosed with major depressive disorder (MDD) were recruited from two longitudinal cohorts. Patients received antidepressant treatment as usual, and the depression symptoms were evaluated by the 17-item Hamilton depression rating scale (HAMD-17) at baseline, two weeks, and eight weeks. Based on the HAMD-17 scores, different trajectories of symptom change were distinguished by applying Growth Mixture Modeling (GMM). Furthermore, the baseline sociodemographic, clinical, and cognitive characteristics were compared to identify potential predictors for different trajectories. Through GMM, three unique depressive symptom trajectories of MDD patients were identified: (1) mild-severity class with significant improvement (Mild, n = 255); (2) high-severity class with significant improvement (High, n = 39); (3) moderate-severity class with limited improvement (Limited, n = 98). Among the three trajectories, the Mild class had a relatively low level of anxiety symptoms at baseline, whereas the High class had the lowest education level and the worst cognitive performance. Additionally, participants in the Limited class exhibited an early age of onset and experienced a higher level of emotional abuse. MDD patients could be categorised into three distinct latent subtypes through different symptom trajectories in this study, and the characteristics of these subtype patients may inform identifications for trajectory-specific intervention targets.</p>\",\"PeriodicalId\":11822,\"journal\":{\"name\":\"European Archives of Psychiatry and Clinical Neuroscience\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":3.5000,\"publicationDate\":\"2024-09-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"European Archives of Psychiatry and Clinical Neuroscience\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1007/s00406-024-01883-z\",\"RegionNum\":3,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"CLINICAL NEUROLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"European Archives of Psychiatry and Clinical Neuroscience","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1007/s00406-024-01883-z","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CLINICAL NEUROLOGY","Score":null,"Total":0}
Identifying latent subtypes of symptom trajectories in major depressive disorder patients and their predictors.
This study aimed to identify different symptom trajectories based on the severity of depression symptoms within a 2-month follow-up, and to explore predictive factors for different symptom trajectories. Three hundred and ninety-two adults diagnosed with major depressive disorder (MDD) were recruited from two longitudinal cohorts. Patients received antidepressant treatment as usual, and the depression symptoms were evaluated by the 17-item Hamilton depression rating scale (HAMD-17) at baseline, two weeks, and eight weeks. Based on the HAMD-17 scores, different trajectories of symptom change were distinguished by applying Growth Mixture Modeling (GMM). Furthermore, the baseline sociodemographic, clinical, and cognitive characteristics were compared to identify potential predictors for different trajectories. Through GMM, three unique depressive symptom trajectories of MDD patients were identified: (1) mild-severity class with significant improvement (Mild, n = 255); (2) high-severity class with significant improvement (High, n = 39); (3) moderate-severity class with limited improvement (Limited, n = 98). Among the three trajectories, the Mild class had a relatively low level of anxiety symptoms at baseline, whereas the High class had the lowest education level and the worst cognitive performance. Additionally, participants in the Limited class exhibited an early age of onset and experienced a higher level of emotional abuse. MDD patients could be categorised into three distinct latent subtypes through different symptom trajectories in this study, and the characteristics of these subtype patients may inform identifications for trajectory-specific intervention targets.
期刊介绍:
The original papers published in the European Archives of Psychiatry and Clinical Neuroscience deal with all aspects of psychiatry and related clinical neuroscience.
Clinical psychiatry, psychopathology, epidemiology as well as brain imaging, neuropathological, neurophysiological, neurochemical and moleculargenetic studies of psychiatric disorders are among the topics covered.
Thus both the clinician and the neuroscientist are provided with a handy source of information on important scientific developments.