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Explore the influencing factors and construct random forest models of post-stroke depression at 3 months in males and females
BACKGROUND: Post-stroke depression (PSD) is one of the most common neuropsychiatric complications after stroke. The occurrence, development and prognosis of PSD have long been different between males and females. The main purpose of this study was to explore the influencing factors of PSD at 3 month...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9764471/ https://www.ncbi.nlm.nih.gov/pubmed/36539755 http://dx.doi.org/10.1186/s12888-022-04467-0 |
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author | Qiu, Xiuli Wang, He Lan, Yan Miao, Jinfeng Pan, Chensheng Sun, Wenzhe Li, Guo Wang, Yanyan Zhao, Xin Zhu, Zhou Zhu, Suiqiang |
author_facet | Qiu, Xiuli Wang, He Lan, Yan Miao, Jinfeng Pan, Chensheng Sun, Wenzhe Li, Guo Wang, Yanyan Zhao, Xin Zhu, Zhou Zhu, Suiqiang |
author_sort | Qiu, Xiuli |
collection | PubMed |
description | BACKGROUND: Post-stroke depression (PSD) is one of the most common neuropsychiatric complications after stroke. The occurrence, development and prognosis of PSD have long been different between males and females. The main purpose of this study was to explore the influencing factors of PSD at 3 months in males and females, and construct random forest (RF) models to rank the influencing factors. METHODS: This is a prospective multicenter cohort study (Registration number: ChiCTR-ROC-17013993). Stroke patients hospitalized in the department of Neurology of three hospitals in Wuhan were enrolled from May 2018 to August 2019. Scale assessments were performed 24 hours after admission and 3 months after stroke onset. Binary logistic regression analysis was used for univariate and multivariate (stepwise backward method) analysis, when p was less than 0.05, the difference between groups was considered statistically significant. Lastly, the RF models were constructed according to the results of multivariate regression analysis. RESULTS: This study found that several baseline variables were associated with PSD at 3 months in males and females. RF model ranked them as stroke severity (OR [odds ratio] =1.17, p < 0.001, 95%CI [confidence interval]:1.11–1.24), neuroticism dimension (OR = 1.06, p = 0.002, 95%CI:1.02–1.10), physical exercise (OR = 0.62, p = 0.007, 95%CI:0.44–0.88), sleeping time < 5 h (OR = 1.91, p = 0.006, 95% CI:1.20–3.04) and atrial fibrillation (OR = 4.18, p = 0.012, 95%CI:1.38–12.68) in males. In females, RF model ranked them as psychological resilience (OR = 0.98, p = 0.015, 95%CI:0.96–1.00), ability of daily living (OR = 0.98, p = 0.001, 95%CI:0.97–0.99), neuroticism dimension (OR = 1.11, p = 0.002, 95%CI:1.04–1.18) and subjective support (OR = 1.11, p < 0.001, 95%CI:1.05–1.78). CONCLUSION: The study found influencing factors of PSD at 3 months were different in males and females, and construct RF models to rank them according to their importance. This suggests that clinicians should focus their interventions on sex-specific influencing factors in order to improve the prognosis of PSD patients. TRIAL REGISTRATION: ChiCTR-ROC-17013993. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12888-022-04467-0. |
format | Online Article Text |
id | pubmed-9764471 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-97644712022-12-21 Explore the influencing factors and construct random forest models of post-stroke depression at 3 months in males and females Qiu, Xiuli Wang, He Lan, Yan Miao, Jinfeng Pan, Chensheng Sun, Wenzhe Li, Guo Wang, Yanyan Zhao, Xin Zhu, Zhou Zhu, Suiqiang BMC Psychiatry Research BACKGROUND: Post-stroke depression (PSD) is one of the most common neuropsychiatric complications after stroke. The occurrence, development and prognosis of PSD have long been different between males and females. The main purpose of this study was to explore the influencing factors of PSD at 3 months in males and females, and construct random forest (RF) models to rank the influencing factors. METHODS: This is a prospective multicenter cohort study (Registration number: ChiCTR-ROC-17013993). Stroke patients hospitalized in the department of Neurology of three hospitals in Wuhan were enrolled from May 2018 to August 2019. Scale assessments were performed 24 hours after admission and 3 months after stroke onset. Binary logistic regression analysis was used for univariate and multivariate (stepwise backward method) analysis, when p was less than 0.05, the difference between groups was considered statistically significant. Lastly, the RF models were constructed according to the results of multivariate regression analysis. RESULTS: This study found that several baseline variables were associated with PSD at 3 months in males and females. RF model ranked them as stroke severity (OR [odds ratio] =1.17, p < 0.001, 95%CI [confidence interval]:1.11–1.24), neuroticism dimension (OR = 1.06, p = 0.002, 95%CI:1.02–1.10), physical exercise (OR = 0.62, p = 0.007, 95%CI:0.44–0.88), sleeping time < 5 h (OR = 1.91, p = 0.006, 95% CI:1.20–3.04) and atrial fibrillation (OR = 4.18, p = 0.012, 95%CI:1.38–12.68) in males. In females, RF model ranked them as psychological resilience (OR = 0.98, p = 0.015, 95%CI:0.96–1.00), ability of daily living (OR = 0.98, p = 0.001, 95%CI:0.97–0.99), neuroticism dimension (OR = 1.11, p = 0.002, 95%CI:1.04–1.18) and subjective support (OR = 1.11, p < 0.001, 95%CI:1.05–1.78). CONCLUSION: The study found influencing factors of PSD at 3 months were different in males and females, and construct RF models to rank them according to their importance. This suggests that clinicians should focus their interventions on sex-specific influencing factors in order to improve the prognosis of PSD patients. TRIAL REGISTRATION: ChiCTR-ROC-17013993. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12888-022-04467-0. BioMed Central 2022-12-20 /pmc/articles/PMC9764471/ /pubmed/36539755 http://dx.doi.org/10.1186/s12888-022-04467-0 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Qiu, Xiuli Wang, He Lan, Yan Miao, Jinfeng Pan, Chensheng Sun, Wenzhe Li, Guo Wang, Yanyan Zhao, Xin Zhu, Zhou Zhu, Suiqiang Explore the influencing factors and construct random forest models of post-stroke depression at 3 months in males and females |
title | Explore the influencing factors and construct random forest models of post-stroke depression at 3 months in males and females |
title_full | Explore the influencing factors and construct random forest models of post-stroke depression at 3 months in males and females |
title_fullStr | Explore the influencing factors and construct random forest models of post-stroke depression at 3 months in males and females |
title_full_unstemmed | Explore the influencing factors and construct random forest models of post-stroke depression at 3 months in males and females |
title_short | Explore the influencing factors and construct random forest models of post-stroke depression at 3 months in males and females |
title_sort | explore the influencing factors and construct random forest models of post-stroke depression at 3 months in males and females |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9764471/ https://www.ncbi.nlm.nih.gov/pubmed/36539755 http://dx.doi.org/10.1186/s12888-022-04467-0 |
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