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

被引:4
作者
Ding, Rui [1 ,2 ]
Zhou, Heng [3 ]
Yan, Xin [1 ,2 ]
Liu, Ying [1 ,2 ]
Guo, Yunmei [1 ,2 ]
Tan, Huiwen [1 ,2 ]
Wang, Xueting [1 ,2 ]
Wang, Yousha [1 ,2 ]
Wang, Lianhong [1 ,2 ]
机构
[1] Zunyi Med Univ, Nursing Dept, Affiliated Hosp, Zunyi, Peoples R China
[2] Zunyi Med Univ, Nursing Coll, Zunyi, Peoples R China
[3] Zunyi Med Univ, Reprod Med Dept, Affiliated Hosp, Zunyi, Peoples R China
关键词
polycystic ovary syndrome; adolescents; depression; prediction model; LASSO regression; DISORDERS; WOMEN; PERCEPTION; CHILDREN; RISK;
D O I
10.3389/fpsyt.2022.984653
中图分类号
R749 [精神病学];
学科分类号
100205 ;
摘要
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.
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页数:11
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