{"title":"情绪调节能力对评估抑郁症认知改善的预测作用","authors":"","doi":"10.1016/j.jpsychires.2024.08.036","DOIUrl":null,"url":null,"abstract":"<div><h3>Objective</h3><p>To construct a predictive model for the improvement of cognitive function in patients with depressive disorder treated with SNRIs, based on emotional regulation abilities, and to provide personalized treatment for depressed patients.</p></div><div><h3>Methods</h3><p>Clinical data from 170 patients with depressive disorder treated with SNRIs at Tongji Hospital, Shanghai, from December 2017 to May 2023 were collected. Based on whether the MoCA-B total score at 3–6 months post-treatment was at least 2 points higher than at baseline, patients were divided into the cognitive function improved group (n = 80) and the cognitive function not improved group (n = 90). Stepwise logistic regression and LASSO regression were used to select predictive factors, and logistic regression analysis was applied to construct predictive models solely based on emotional regulation abilities, combined with executive functions and HAMD scores. The models were further validated through Bootstrap internal validation, calibration curve plotting, and C-index calculation, and a comparison between the two models was performed.</p></div><div><h3>Results</h3><p>An ER model with an area under the ROC curve of 0.817was established using four emotional regulation ability indicators: the valence of reappraised images, the arousal of negative images, the arousal of neutral images, and the success of reappraisal (arousal). Internal validation using Bootstrap showed a C index of 0.817, and clinical decision curves indicated that this model has a significant net benefit with a probability of improved cognitive function ranging from about 20 to 85%. Additionally, an EREH model including emotional regulation ability, executive function, and HAMD score as predictors was constructed using Lasso and logistic regression methods. This model reached an area under the ROC curve of 0.859and clinical decision curves showed high net benefits with probabilities of improved cognitive function ranging from 10 to 100%. The calibration curves of both models coincided well with the actual curves, with the latter having a higher AUC and significant statistical differences between the two models.</p></div><div><h3>Conclusion</h3><p>This study suggests that emotional regulation ability may serve as a predictor for the improvement of cognitive functions in patients with <del>depression</del> depressive disorder treated with SNRIs. However, it is important to note that there may be other factors not covered or included in this study.The predictive model that includes executive functions and HAMD scores offers better differentiation and consistency and is more feasible in clinical practice.</p></div>","PeriodicalId":16868,"journal":{"name":"Journal of psychiatric research","volume":null,"pages":null},"PeriodicalIF":3.7000,"publicationDate":"2024-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Predictive utility of emotional regulation abilities for assessing cognitive improvement in depression\",\"authors\":\"\",\"doi\":\"10.1016/j.jpsychires.2024.08.036\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><h3>Objective</h3><p>To construct a predictive model for the improvement of cognitive function in patients with depressive disorder treated with SNRIs, based on emotional regulation abilities, and to provide personalized treatment for depressed patients.</p></div><div><h3>Methods</h3><p>Clinical data from 170 patients with depressive disorder treated with SNRIs at Tongji Hospital, Shanghai, from December 2017 to May 2023 were collected. Based on whether the MoCA-B total score at 3–6 months post-treatment was at least 2 points higher than at baseline, patients were divided into the cognitive function improved group (n = 80) and the cognitive function not improved group (n = 90). Stepwise logistic regression and LASSO regression were used to select predictive factors, and logistic regression analysis was applied to construct predictive models solely based on emotional regulation abilities, combined with executive functions and HAMD scores. The models were further validated through Bootstrap internal validation, calibration curve plotting, and C-index calculation, and a comparison between the two models was performed.</p></div><div><h3>Results</h3><p>An ER model with an area under the ROC curve of 0.817was established using four emotional regulation ability indicators: the valence of reappraised images, the arousal of negative images, the arousal of neutral images, and the success of reappraisal (arousal). Internal validation using Bootstrap showed a C index of 0.817, and clinical decision curves indicated that this model has a significant net benefit with a probability of improved cognitive function ranging from about 20 to 85%. Additionally, an EREH model including emotional regulation ability, executive function, and HAMD score as predictors was constructed using Lasso and logistic regression methods. This model reached an area under the ROC curve of 0.859and clinical decision curves showed high net benefits with probabilities of improved cognitive function ranging from 10 to 100%. The calibration curves of both models coincided well with the actual curves, with the latter having a higher AUC and significant statistical differences between the two models.</p></div><div><h3>Conclusion</h3><p>This study suggests that emotional regulation ability may serve as a predictor for the improvement of cognitive functions in patients with <del>depression</del> depressive disorder treated with SNRIs. However, it is important to note that there may be other factors not covered or included in this study.The predictive model that includes executive functions and HAMD scores offers better differentiation and consistency and is more feasible in clinical practice.</p></div>\",\"PeriodicalId\":16868,\"journal\":{\"name\":\"Journal of psychiatric research\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":3.7000,\"publicationDate\":\"2024-08-27\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of psychiatric research\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0022395624004928\",\"RegionNum\":2,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"PSYCHIATRY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of psychiatric research","FirstCategoryId":"3","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0022395624004928","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"PSYCHIATRY","Score":null,"Total":0}
Predictive utility of emotional regulation abilities for assessing cognitive improvement in depression
Objective
To construct a predictive model for the improvement of cognitive function in patients with depressive disorder treated with SNRIs, based on emotional regulation abilities, and to provide personalized treatment for depressed patients.
Methods
Clinical data from 170 patients with depressive disorder treated with SNRIs at Tongji Hospital, Shanghai, from December 2017 to May 2023 were collected. Based on whether the MoCA-B total score at 3–6 months post-treatment was at least 2 points higher than at baseline, patients were divided into the cognitive function improved group (n = 80) and the cognitive function not improved group (n = 90). Stepwise logistic regression and LASSO regression were used to select predictive factors, and logistic regression analysis was applied to construct predictive models solely based on emotional regulation abilities, combined with executive functions and HAMD scores. The models were further validated through Bootstrap internal validation, calibration curve plotting, and C-index calculation, and a comparison between the two models was performed.
Results
An ER model with an area under the ROC curve of 0.817was established using four emotional regulation ability indicators: the valence of reappraised images, the arousal of negative images, the arousal of neutral images, and the success of reappraisal (arousal). Internal validation using Bootstrap showed a C index of 0.817, and clinical decision curves indicated that this model has a significant net benefit with a probability of improved cognitive function ranging from about 20 to 85%. Additionally, an EREH model including emotional regulation ability, executive function, and HAMD score as predictors was constructed using Lasso and logistic regression methods. This model reached an area under the ROC curve of 0.859and clinical decision curves showed high net benefits with probabilities of improved cognitive function ranging from 10 to 100%. The calibration curves of both models coincided well with the actual curves, with the latter having a higher AUC and significant statistical differences between the two models.
Conclusion
This study suggests that emotional regulation ability may serve as a predictor for the improvement of cognitive functions in patients with depression depressive disorder treated with SNRIs. However, it is important to note that there may be other factors not covered or included in this study.The predictive model that includes executive functions and HAMD scores offers better differentiation and consistency and is more feasible in clinical practice.
期刊介绍:
Founded in 1961 to report on the latest work in psychiatry and cognate disciplines, the Journal of Psychiatric Research is dedicated to innovative and timely studies of four important areas of research:
(1) clinical studies of all disciplines relating to psychiatric illness, as well as normal human behaviour, including biochemical, physiological, genetic, environmental, social, psychological and epidemiological factors;
(2) basic studies pertaining to psychiatry in such fields as neuropsychopharmacology, neuroendocrinology, electrophysiology, genetics, experimental psychology and epidemiology;
(3) the growing application of clinical laboratory techniques in psychiatry, including imagery and spectroscopy of the brain, molecular biology and computer sciences;