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<p>Bipolar disorder (BD) is a psychiatric disorder with a high prevalence of suicidal ideation (SI). While the relationship between BD and the endocrine system is well established, the influence of neuroendocrine hormones on SI during depressive episodes remains poorly understood. This cross-sectional study aimed to identify high-risk neuroendocrine factors for SI and evaluate their predictive efficacy using machine learning techniques. Data were obtained from the electronic medical records of patients hospitalized for BD depressive episodes at The First Affiliated Hospital of Jinan University in Guangzhou, Guangdong Province, China between January 1, 2017, and October 31, 2022. Of 635 eligible patients, 380 exhibited SI. In the multivariate analysis, lower levels of FT4 (OR = 0.925; 95% CI = 0.869–0.986; <i>P</i> = 0.017) and testosterone (OR = 0.799; 95% CI = 0.642–0.993; <i>P</i> = 0.043) were significantly associated with an increased risk of SI. Additionally, an earlier age of onset (OR = 0.936; 95% CI = 0.897–0.977; <i>P</i> = 0.002) and the presence of psychotic symptoms contributed to a higher risk of SI. Furthermore, we developed a supervised learning model—Naive Bayes classifier. The model identified age of onset as a key predictor of SI during depressive episodes of BD, highlighting its importance as the most relevant predictive variable for distinguishing patients at risk of SI. These findings could help clinicians more accurately identify BD patients with higher suicide risk, thereby improving diagnostic sensitivity for this disorder.</p>

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Neuroendocrine abnormalities as predictors of suicidal ideation in bipolar disorder patients during depressive episodes: a cross-sectional study

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年10月28日

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  • Xiaoxuan Fan,
  • Xian Shi,
  • Fangyi Deng,
  • Yixian Cai,
  • Yaxi Liu,
  • Yang Zhao,
  • Heng Wang,
  • Jiwu Liao,
  • Jiyang Pan

摘要

Bipolar disorder (BD) is a psychiatric disorder with a high prevalence of suicidal ideation (SI). While the relationship between BD and the endocrine system is well established, the influence of neuroendocrine hormones on SI during depressive episodes remains poorly understood. This cross-sectional study aimed to identify high-risk neuroendocrine factors for SI and evaluate their predictive efficacy using machine learning techniques. Data were obtained from the electronic medical records of patients hospitalized for BD depressive episodes at The First Affiliated Hospital of Jinan University in Guangzhou, Guangdong Province, China between January 1, 2017, and October 31, 2022. Of 635 eligible patients, 380 exhibited SI. In the multivariate analysis, lower levels of FT4 (OR = 0.925; 95% CI = 0.869–0.986; P = 0.017) and testosterone (OR = 0.799; 95% CI = 0.642–0.993; P = 0.043) were significantly associated with an increased risk of SI. Additionally, an earlier age of onset (OR = 0.936; 95% CI = 0.897–0.977; P = 0.002) and the presence of psychotic symptoms contributed to a higher risk of SI. Furthermore, we developed a supervised learning model—Naive Bayes classifier. The model identified age of onset as a key predictor of SI during depressive episodes of BD, highlighting its importance as the most relevant predictive variable for distinguishing patients at risk of SI. These findings could help clinicians more accurately identify BD patients with higher suicide risk, thereby improving diagnostic sensitivity for this disorder.