Li Chao, Yang Lei, Zhang Qiuyu, Zhang Ying, Li Ranli, Jia Feng, Wang Lina, Ma Xiaoyan, Yao Kaifang, Tian Hongjun, Liu Zengxun, Zhuo Chuanjun
Computational Biology and Animal Imaging Center (CBAC), Tianjin Anding Hospital, Nankai University Affiliated Tianjin Anding Hospital, Tianjin Medical University Affiliated Tianjin Anding Hospital, Tianjin Medical University Affiliated Tianjin Mental Health Center, Tianjin, 300222, People's Republic of China.
Laboratory of Psychiatric-Neuroimaging-Genetic and Co-morbidity (PNGC_Lab), Tianjin Anding Hospital, Tianjin Mental Health Center of Tianjin Medical University, Tianjin, 300222, People's Republic of China.
Neuropsychiatr Dis Treat. 2025 Jan 29;21:157-166. doi: 10.2147/NDT.S496172. eCollection 2025.
Distinguishing bipolar depression (BD) from unipolar depression (UD) remains a major clinical challenge, especially in drug-naïve patients. The present study aimed to investigate whether demographic, clinical, and biochemical parameters can help differentiate drug-naïve BD from UD.
Drug-naïve patients with UD and BD were recruited from Shandong Mental Health Center. Ninety-four inpatients (61 UD and 33 BD) were assessed using the 17-item Hamilton Depression Rating Scale (HAMD-17) and P300 latency. Fasting serum levels of free triiodothyronine (FT3), free thyroxine (FT4), thyroid-stimulating hormone (TSH), as well as fasting plasma glucose (FPG), lipid, C-reactive protein (CRP), and uric acid (UA) indicators were measured.
Patients with BD had longer illness duration and P300 latency and lower FT3 levels, but higher levels of TSH and FPG than patients with UD (all <0.05). Binary logistic regression analysis indicated illness duration, TSH, FPG, and P300 latency were significantly associated with BD. Illness duration, TSH, FPG, and P300 latency achieved an area under the ROC curve of 0.777, 0.699, 0.646, and 0.635, respectively, in discriminating unipolar and bipolar depression.
Increased illness duration, serum TSH and FPG levels, and P300 latency were independent risk factors for BD. Demographic, clinical, biochemical, and electrophysiological markers identified may have the potential to distinguish BD from UD.
区分双相抑郁症（BD）和单相抑郁症（UD）仍然是一项重大的临床挑战，尤其是在未接受过药物治疗的患者中。本研究旨在调查人口统计学、临床和生化参数是否有助于区分未接受过药物治疗的BD和UD。
从山东精神卫生中心招募未接受过药物治疗的UD和BD患者。使用17项汉密尔顿抑郁量表（HAMD-17）和P300潜伏期对94名住院患者（61名UD和33名BD）进行评估。测量空腹血清游离三碘甲状腺原氨酸（FT3）、游离甲状腺素（FT4）、促甲状腺激素（TSH）水平，以及空腹血糖（FPG）、血脂、C反应蛋白（CRP）和尿酸（UA）指标。
与UD患者相比，BD患者的病程更长、P300潜伏期更长、FT3水平更低，但TSH和FPG水平更高（均P<0.05）。二元逻辑回归分析表明，病程、TSH、FPG和P300潜伏期与BD显著相关。在区分单相和双相抑郁症方面，病程、TSH水平、FPG水平和P300潜伏期的ROC曲线下面积分别为0.777、0.699、0.646和0.635。
病程延长、血清TSH和FPG水平升高以及P300潜伏期延长是BD的独立危险因素。所确定的人口统计学、临床、生化和电生理标志物可能具有区分BD和UD的潜力。
