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Factors associated with suicidal attempts in female patients with mood disorder
AIM: This study aims to establish a nomogram model to predict the relevance of SA in Chinese female patients with mood disorder (MD). METHOD: The study included 396 female participants who were diagnosed with MD Diagnostic Group (F30–F39) according to the 10th Edition of Disease and Related Health P...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10560740/ https://www.ncbi.nlm.nih.gov/pubmed/37818303 http://dx.doi.org/10.3389/fpubh.2023.1157606 |
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author | Zhang, Jinhe Liang, Sixiang Liu, Xinyu Li, Dan Zhou, Fuchun Xiao, Le Liu, Jun Sha, Sha |
author_facet | Zhang, Jinhe Liang, Sixiang Liu, Xinyu Li, Dan Zhou, Fuchun Xiao, Le Liu, Jun Sha, Sha |
author_sort | Zhang, Jinhe |
collection | PubMed |
description | AIM: This study aims to establish a nomogram model to predict the relevance of SA in Chinese female patients with mood disorder (MD). METHOD: The study included 396 female participants who were diagnosed with MD Diagnostic Group (F30–F39) according to the 10th Edition of Disease and Related Health Problems (ICD-10). Assessing the differences of demographic information and clinical characteristics between the two groups. LASSO Logistic Regression Analyses was used to identify the risk factors of SA. A nomogram was further used to construct a prediction model. Bootstrap re-sampling was used to internally validate the final model. The Receiver Operating Characteristic (ROC) curve and C-index was also used to evaluate the accuracy of the prediction model. RESULT: LASSO regression analysis showed that five factors led to the occurrence of suicidality, including BMI (β = −0.02, SE = 0.02), social dysfunction (β = 1.72, SE = 0.24), time interval between first onset and first dose (β = 0.03, SE = 0.01), polarity at onset (β = −1.13, SE = 0.25), and times of hospitalization (β = −0.11, SE = 0.06). We assessed the ability of the nomogram model to recognize suicidality, with good results (AUC = 0.76, 95% CI: 0.71–0.80). Indicating that the nomogram had a good consistency (C-index: 0.756, 95% CI: 0.750–0.758). The C-index of bootstrap resampling with 100 replicates for internal validation was 0.740, which further demonstrated the excellent calibration of predicted and observed risks. CONCLUSION: Five factors, namely BMI, social dysfunction, time interval between first onset and first dose, polarity at onset, and times of hospitalization, were found to be significantly associated with the development of suicidality in patients with MD. By incorporating these factors into a nomogram model, we can accurately predict the risk of suicide in MD patients. It is crucial to closely monitor clinical factors from the beginning and throughout the course of MD in order to prevent suicide attempts. |
format | Online Article Text |
id | pubmed-10560740 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-105607402023-10-10 Factors associated with suicidal attempts in female patients with mood disorder Zhang, Jinhe Liang, Sixiang Liu, Xinyu Li, Dan Zhou, Fuchun Xiao, Le Liu, Jun Sha, Sha Front Public Health Public Health AIM: This study aims to establish a nomogram model to predict the relevance of SA in Chinese female patients with mood disorder (MD). METHOD: The study included 396 female participants who were diagnosed with MD Diagnostic Group (F30–F39) according to the 10th Edition of Disease and Related Health Problems (ICD-10). Assessing the differences of demographic information and clinical characteristics between the two groups. LASSO Logistic Regression Analyses was used to identify the risk factors of SA. A nomogram was further used to construct a prediction model. Bootstrap re-sampling was used to internally validate the final model. The Receiver Operating Characteristic (ROC) curve and C-index was also used to evaluate the accuracy of the prediction model. RESULT: LASSO regression analysis showed that five factors led to the occurrence of suicidality, including BMI (β = −0.02, SE = 0.02), social dysfunction (β = 1.72, SE = 0.24), time interval between first onset and first dose (β = 0.03, SE = 0.01), polarity at onset (β = −1.13, SE = 0.25), and times of hospitalization (β = −0.11, SE = 0.06). We assessed the ability of the nomogram model to recognize suicidality, with good results (AUC = 0.76, 95% CI: 0.71–0.80). Indicating that the nomogram had a good consistency (C-index: 0.756, 95% CI: 0.750–0.758). The C-index of bootstrap resampling with 100 replicates for internal validation was 0.740, which further demonstrated the excellent calibration of predicted and observed risks. CONCLUSION: Five factors, namely BMI, social dysfunction, time interval between first onset and first dose, polarity at onset, and times of hospitalization, were found to be significantly associated with the development of suicidality in patients with MD. By incorporating these factors into a nomogram model, we can accurately predict the risk of suicide in MD patients. It is crucial to closely monitor clinical factors from the beginning and throughout the course of MD in order to prevent suicide attempts. Frontiers Media S.A. 2023-09-25 /pmc/articles/PMC10560740/ /pubmed/37818303 http://dx.doi.org/10.3389/fpubh.2023.1157606 Text en Copyright © 2023 Zhang, Liang, Liu, Li, Zhou, Xiao, Liu and Sha. 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 | Public Health Zhang, Jinhe Liang, Sixiang Liu, Xinyu Li, Dan Zhou, Fuchun Xiao, Le Liu, Jun Sha, Sha Factors associated with suicidal attempts in female patients with mood disorder |
title | Factors associated with suicidal attempts in female patients with mood disorder |
title_full | Factors associated with suicidal attempts in female patients with mood disorder |
title_fullStr | Factors associated with suicidal attempts in female patients with mood disorder |
title_full_unstemmed | Factors associated with suicidal attempts in female patients with mood disorder |
title_short | Factors associated with suicidal attempts in female patients with mood disorder |
title_sort | factors associated with suicidal attempts in female patients with mood disorder |
topic | Public Health |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10560740/ https://www.ncbi.nlm.nih.gov/pubmed/37818303 http://dx.doi.org/10.3389/fpubh.2023.1157606 |
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