Yuwei Li, Dong Wang, Jiexin Fang, Si Zu, Le Xiao, Xuequan Zhu, Gang Wang, Yongdong Hu
{"title":"影响抑郁症患者残留症状倾向的因素:一项纵向研究。","authors":"Yuwei Li, Dong Wang, Jiexin Fang, Si Zu, Le Xiao, Xuequan Zhu, Gang Wang, Yongdong Hu","doi":"10.1186/s12888-024-05915-9","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Residual symptoms of depressive disorders are serious health problems. However, the progression process is hardly predictable due to high heterogeneity of the disease. This study aims to: (1) classify the patterns of changes in residual symptoms based on homogeneous data, and (2) identify potential predictors for these patterns.</p><p><strong>Methods: </strong>In this study, we conducted a data-driven Latent Class Growth Analysis (LCGA) to identify distinct tendencies of changes in residual symptoms, which were longitudinally quantified using the QIDS-SR16 at baseline and 1/3/6 months post-baseline for depressed patients. The association between baseline characteristics (e.g. clinical features and cognitive functions) and different progression tendencies were also identified.</p><p><strong>Results: </strong>The tendency of changes in residual symptoms was categorized into four classes: \"light residual symptom decline (15.4%)\", \"residual symptom disappears (39.3%)\", \"steady residual symptom (6.3%)\" and \"severe residual symptom decline (39.0%)\". We observed that the second class displayed more favorable recuperation outcomes than the rest of patients. The severity, recurrence, polypharmacy, and medication adherence of symptoms are intricately linked to the duration of residual symptoms' persistence. Additionally, clinical characteristics including sleep disturbances, depressive moods, alterations in appetite or weight, and difficulties with concentration have been identified as significant factors in the recovery process.</p><p><strong>Conclusions: </strong>Our research findings indicate that certain clinical characteristics in patients with depressive disorders are associated with poor recovery from residual symptoms following acute treatment. This revelation holds significant value in the targeted attention to specific patients and the development of early intervention strategies for residual symptoms accordingly.</p>","PeriodicalId":9029,"journal":{"name":"BMC Psychiatry","volume":null,"pages":null},"PeriodicalIF":3.4000,"publicationDate":"2024-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11323663/pdf/","citationCount":"0","resultStr":"{\"title\":\"Factors influencing the tendency of residual symptoms in patients with depressive disorders: a longitudinal study.\",\"authors\":\"Yuwei Li, Dong Wang, Jiexin Fang, Si Zu, Le Xiao, Xuequan Zhu, Gang Wang, Yongdong Hu\",\"doi\":\"10.1186/s12888-024-05915-9\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>Residual symptoms of depressive disorders are serious health problems. However, the progression process is hardly predictable due to high heterogeneity of the disease. This study aims to: (1) classify the patterns of changes in residual symptoms based on homogeneous data, and (2) identify potential predictors for these patterns.</p><p><strong>Methods: </strong>In this study, we conducted a data-driven Latent Class Growth Analysis (LCGA) to identify distinct tendencies of changes in residual symptoms, which were longitudinally quantified using the QIDS-SR16 at baseline and 1/3/6 months post-baseline for depressed patients. The association between baseline characteristics (e.g. clinical features and cognitive functions) and different progression tendencies were also identified.</p><p><strong>Results: </strong>The tendency of changes in residual symptoms was categorized into four classes: \\\"light residual symptom decline (15.4%)\\\", \\\"residual symptom disappears (39.3%)\\\", \\\"steady residual symptom (6.3%)\\\" and \\\"severe residual symptom decline (39.0%)\\\". We observed that the second class displayed more favorable recuperation outcomes than the rest of patients. The severity, recurrence, polypharmacy, and medication adherence of symptoms are intricately linked to the duration of residual symptoms' persistence. Additionally, clinical characteristics including sleep disturbances, depressive moods, alterations in appetite or weight, and difficulties with concentration have been identified as significant factors in the recovery process.</p><p><strong>Conclusions: </strong>Our research findings indicate that certain clinical characteristics in patients with depressive disorders are associated with poor recovery from residual symptoms following acute treatment. This revelation holds significant value in the targeted attention to specific patients and the development of early intervention strategies for residual symptoms accordingly.</p>\",\"PeriodicalId\":9029,\"journal\":{\"name\":\"BMC Psychiatry\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":3.4000,\"publicationDate\":\"2024-08-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11323663/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"BMC Psychiatry\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1186/s12888-024-05915-9\",\"RegionNum\":2,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"PSYCHIATRY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"BMC Psychiatry","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1186/s12888-024-05915-9","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"PSYCHIATRY","Score":null,"Total":0}
Factors influencing the tendency of residual symptoms in patients with depressive disorders: a longitudinal study.
Background: Residual symptoms of depressive disorders are serious health problems. However, the progression process is hardly predictable due to high heterogeneity of the disease. This study aims to: (1) classify the patterns of changes in residual symptoms based on homogeneous data, and (2) identify potential predictors for these patterns.
Methods: In this study, we conducted a data-driven Latent Class Growth Analysis (LCGA) to identify distinct tendencies of changes in residual symptoms, which were longitudinally quantified using the QIDS-SR16 at baseline and 1/3/6 months post-baseline for depressed patients. The association between baseline characteristics (e.g. clinical features and cognitive functions) and different progression tendencies were also identified.
Results: The tendency of changes in residual symptoms was categorized into four classes: "light residual symptom decline (15.4%)", "residual symptom disappears (39.3%)", "steady residual symptom (6.3%)" and "severe residual symptom decline (39.0%)". We observed that the second class displayed more favorable recuperation outcomes than the rest of patients. The severity, recurrence, polypharmacy, and medication adherence of symptoms are intricately linked to the duration of residual symptoms' persistence. Additionally, clinical characteristics including sleep disturbances, depressive moods, alterations in appetite or weight, and difficulties with concentration have been identified as significant factors in the recovery process.
Conclusions: Our research findings indicate that certain clinical characteristics in patients with depressive disorders are associated with poor recovery from residual symptoms following acute treatment. This revelation holds significant value in the targeted attention to specific patients and the development of early intervention strategies for residual symptoms accordingly.
期刊介绍:
BMC Psychiatry is an open access, peer-reviewed journal that considers articles on all aspects of the prevention, diagnosis and management of psychiatric disorders, as well as related molecular genetics, pathophysiology, and epidemiology.