Factors associated with suicidal attempts in female patients with mood disorder.
Chinese population
LASSO Logistic Regression
mood disorder
prediction model
suicidal attempt
Journal
Frontiers in public health
ISSN: 2296-2565
Titre abrégé: Front Public Health
Pays: Switzerland
ID NLM: 101616579
Informations de publication
Date de publication:
2023
2023
Historique:
received:
02
02
2023
accepted:
08
09
2023
medline:
12
10
2023
pubmed:
11
10
2023
entrez:
11
10
2023
Statut:
epublish
Résumé
This study aims to establish a nomogram model to predict the relevance of SA in Chinese female patients with mood disorder (MD). 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. LASSO regression analysis showed that five factors led to the occurrence of suicidality, including BMI ( 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.
Identifiants
pubmed: 37818303
doi: 10.3389/fpubh.2023.1157606
pmc: PMC10560740
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
1157606Informations de copyright
Copyright © 2023 Zhang, Liang, Liu, Li, Zhou, Xiao, Liu and Sha.
Déclaration de conflit d'intérêts
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
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