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Development of a nomogram prediction model for depression in patients with systemic lupus erythematosus

Systemic lupus erythematosus (SLE) is an inflammatory autoimmune disease with depression as one of its most common symptoms. The aim of this study is to establish a nomogram prediction model to assess the occurrence of depression in patients with SLE. Based on the Hospital Anxiety and Depression Sca...

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Autores principales: Chen, Haoyang, Cui, Hengmei, Geng, Yaqin, Jin, Tiantian, Shi, Songsong, Li, Yunyun, Chen, Xin, Shen, Biyu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9518674/
https://www.ncbi.nlm.nih.gov/pubmed/36186364
http://dx.doi.org/10.3389/fpsyg.2022.951431
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author Chen, Haoyang
Cui, Hengmei
Geng, Yaqin
Jin, Tiantian
Shi, Songsong
Li, Yunyun
Chen, Xin
Shen, Biyu
author_facet Chen, Haoyang
Cui, Hengmei
Geng, Yaqin
Jin, Tiantian
Shi, Songsong
Li, Yunyun
Chen, Xin
Shen, Biyu
author_sort Chen, Haoyang
collection PubMed
description Systemic lupus erythematosus (SLE) is an inflammatory autoimmune disease with depression as one of its most common symptoms. The aim of this study is to establish a nomogram prediction model to assess the occurrence of depression in patients with SLE. Based on the Hospital Anxiety and Depression Scale cutoff of 8, 341 patients with SLE, recruited between June 2017 and December 2019, were divided into depressive and non-depressive groups. Data on socio-demographic characteristics, medical history, sociopsychological factors, and other risk factors were collected. Between-group differences in clinical characteristics were assessed with depression as the dependent variable and the variables selected by logistic multiple regression as predictors. The model was established using R language. Marital status, education, social support, coping, and anxiety predicted depression (p < 0.05). The nomogram prediction model showed that the risk rate was from 0.01 to 0.80, and the receiver operating characteristic curve analysis showed that the area under the curve was 0.891 (p < 0.001). The calibration curve can intuitively show that the probability of depression predicted by the nomogram model is consistent with the actual comparison. The designed nomogram provides a highly predictive assessment of depression in patients with SLE, facilitating more comprehensive depression evaluation in usual clinical care.
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spelling pubmed-95186742022-09-29 Development of a nomogram prediction model for depression in patients with systemic lupus erythematosus Chen, Haoyang Cui, Hengmei Geng, Yaqin Jin, Tiantian Shi, Songsong Li, Yunyun Chen, Xin Shen, Biyu Front Psychol Psychology Systemic lupus erythematosus (SLE) is an inflammatory autoimmune disease with depression as one of its most common symptoms. The aim of this study is to establish a nomogram prediction model to assess the occurrence of depression in patients with SLE. Based on the Hospital Anxiety and Depression Scale cutoff of 8, 341 patients with SLE, recruited between June 2017 and December 2019, were divided into depressive and non-depressive groups. Data on socio-demographic characteristics, medical history, sociopsychological factors, and other risk factors were collected. Between-group differences in clinical characteristics were assessed with depression as the dependent variable and the variables selected by logistic multiple regression as predictors. The model was established using R language. Marital status, education, social support, coping, and anxiety predicted depression (p < 0.05). The nomogram prediction model showed that the risk rate was from 0.01 to 0.80, and the receiver operating characteristic curve analysis showed that the area under the curve was 0.891 (p < 0.001). The calibration curve can intuitively show that the probability of depression predicted by the nomogram model is consistent with the actual comparison. The designed nomogram provides a highly predictive assessment of depression in patients with SLE, facilitating more comprehensive depression evaluation in usual clinical care. Frontiers Media S.A. 2022-09-14 /pmc/articles/PMC9518674/ /pubmed/36186364 http://dx.doi.org/10.3389/fpsyg.2022.951431 Text en Copyright © 2022 Chen, Cui, Geng, Jin, Shi, Li, Chen and Shen. 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 Psychology
Chen, Haoyang
Cui, Hengmei
Geng, Yaqin
Jin, Tiantian
Shi, Songsong
Li, Yunyun
Chen, Xin
Shen, Biyu
Development of a nomogram prediction model for depression in patients with systemic lupus erythematosus
title Development of a nomogram prediction model for depression in patients with systemic lupus erythematosus
title_full Development of a nomogram prediction model for depression in patients with systemic lupus erythematosus
title_fullStr Development of a nomogram prediction model for depression in patients with systemic lupus erythematosus
title_full_unstemmed Development of a nomogram prediction model for depression in patients with systemic lupus erythematosus
title_short Development of a nomogram prediction model for depression in patients with systemic lupus erythematosus
title_sort development of a nomogram prediction model for depression in patients with systemic lupus erythematosus
topic Psychology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9518674/
https://www.ncbi.nlm.nih.gov/pubmed/36186364
http://dx.doi.org/10.3389/fpsyg.2022.951431
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