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Development and validation of a prediction model for depression in adolescents with polycystic ovary syndrome: A study protocol

INTRODUCTION: The high prevalence and severity of depression in adolescents with polycystic ovary syndrome (PCOS) is a critical health threat that must be taken seriously. The identification of high-risk groups for depression in adolescents with PCOS is essential to preventing its development and im...

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Autores principales: Ding, Rui, Zhou, Heng, Yan, Xin, Liu, Ying, Guo, Yunmei, Tan, Huiwen, Wang, Xueting, Wang, Yousha, Wang, Lianhong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9486103/
https://www.ncbi.nlm.nih.gov/pubmed/36147974
http://dx.doi.org/10.3389/fpsyt.2022.984653
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author Ding, Rui
Zhou, Heng
Yan, Xin
Liu, Ying
Guo, Yunmei
Tan, Huiwen
Wang, Xueting
Wang, Yousha
Wang, Lianhong
author_facet Ding, Rui
Zhou, Heng
Yan, Xin
Liu, Ying
Guo, Yunmei
Tan, Huiwen
Wang, Xueting
Wang, Yousha
Wang, Lianhong
author_sort Ding, Rui
collection PubMed
description INTRODUCTION: The high prevalence and severity of depression in adolescents with polycystic ovary syndrome (PCOS) is a critical health threat that must be taken seriously. The identification of high-risk groups for depression in adolescents with PCOS is essential to preventing its development and improving its prognosis. At present, the routine screening of depression in adolescents with PCOS is mainly performed using scales, and there is no early identification method for high-risk groups of PCOS depression in adolescents. It is necessary to use a warning model to identify high-risk groups for depression with PCOS in adolescents. METHODS AND ANALYSIS: Model development and validation will be conducted using a retrospective study. The study will involve normal adolescent girls as the control group and adolescent PCOS patients as the experimental group. We will collect not only general factors such as individual susceptibility factors, biological factors, and psychosocial environmental factors of depression in adolescence, but will also examine the pathological factors, illness perception factors, diagnosis and treatment factors, and symptom-related factors of PCOS, as well as the outcome of depression. LASSO will be used to fit a multivariate warning model of depression risk. Data collected between January 2022 and August 2022 will be used to develop and validate the model internally, and data collected between September 2022 and December 2022 will be used for external validation. We will use the C-statistic to measure the model's discrimination, the calibration plot to measure the model's risk prediction ability for depression, and the nomogram to visualize the model. DISCUSSION: The ability to calculate the absolute risk of depression outcomes in adolescents with PCOS would enable early and accurate predictions of depression risk among adolescents with PCOS, and provide the basis for the formulation of depression prevention and control strategies, which have important theoretical and practical implications. TRIAL REGISTRATION NUMBER: [ChiCTR2100050123]; Pre-results.
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spelling pubmed-94861032022-09-21 Development and validation of a prediction model for depression in adolescents with polycystic ovary syndrome: A study protocol Ding, Rui Zhou, Heng Yan, Xin Liu, Ying Guo, Yunmei Tan, Huiwen Wang, Xueting Wang, Yousha Wang, Lianhong Front Psychiatry Psychiatry INTRODUCTION: The high prevalence and severity of depression in adolescents with polycystic ovary syndrome (PCOS) is a critical health threat that must be taken seriously. The identification of high-risk groups for depression in adolescents with PCOS is essential to preventing its development and improving its prognosis. At present, the routine screening of depression in adolescents with PCOS is mainly performed using scales, and there is no early identification method for high-risk groups of PCOS depression in adolescents. It is necessary to use a warning model to identify high-risk groups for depression with PCOS in adolescents. METHODS AND ANALYSIS: Model development and validation will be conducted using a retrospective study. The study will involve normal adolescent girls as the control group and adolescent PCOS patients as the experimental group. We will collect not only general factors such as individual susceptibility factors, biological factors, and psychosocial environmental factors of depression in adolescence, but will also examine the pathological factors, illness perception factors, diagnosis and treatment factors, and symptom-related factors of PCOS, as well as the outcome of depression. LASSO will be used to fit a multivariate warning model of depression risk. Data collected between January 2022 and August 2022 will be used to develop and validate the model internally, and data collected between September 2022 and December 2022 will be used for external validation. We will use the C-statistic to measure the model's discrimination, the calibration plot to measure the model's risk prediction ability for depression, and the nomogram to visualize the model. DISCUSSION: The ability to calculate the absolute risk of depression outcomes in adolescents with PCOS would enable early and accurate predictions of depression risk among adolescents with PCOS, and provide the basis for the formulation of depression prevention and control strategies, which have important theoretical and practical implications. TRIAL REGISTRATION NUMBER: [ChiCTR2100050123]; Pre-results. Frontiers Media S.A. 2022-09-06 /pmc/articles/PMC9486103/ /pubmed/36147974 http://dx.doi.org/10.3389/fpsyt.2022.984653 Text en Copyright © 2022 Ding, Zhou, Yan, Liu, Guo, Tan, Wang, Wang and Wang. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Psychiatry
Ding, Rui
Zhou, Heng
Yan, Xin
Liu, Ying
Guo, Yunmei
Tan, Huiwen
Wang, Xueting
Wang, Yousha
Wang, Lianhong
Development and validation of a prediction model for depression in adolescents with polycystic ovary syndrome: A study protocol
title Development and validation of a prediction model for depression in adolescents with polycystic ovary syndrome: A study protocol
title_full Development and validation of a prediction model for depression in adolescents with polycystic ovary syndrome: A study protocol
title_fullStr Development and validation of a prediction model for depression in adolescents with polycystic ovary syndrome: A study protocol
title_full_unstemmed Development and validation of a prediction model for depression in adolescents with polycystic ovary syndrome: A study protocol
title_short Development and validation of a prediction model for depression in adolescents with polycystic ovary syndrome: A study protocol
title_sort development and validation of a prediction model for depression in adolescents with polycystic ovary syndrome: a study protocol
topic Psychiatry
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9486103/
https://www.ncbi.nlm.nih.gov/pubmed/36147974
http://dx.doi.org/10.3389/fpsyt.2022.984653
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