Zhu Yuncheng, Ji Haifeng, Niu Zhiang, Liu Hongmei, Wu Xiaohui, Yang Lu, Wang Zuowei, Chen Jun, Fang Yiru
Division of Mood Disorders, Shanghai Hongkou Mental Health Center, Shanghai, China.
Clinical Research Center and Division of Mood Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Front Psychiatry. 2022 Jun 20;13:875141. doi: 10.3389/fpsyt.2022.875141. eCollection 2022.
Conventional biochemical indexes may have predictive values in clinical identification between bipolar disorder (BD) and major depressive disorder (MDD).
This study included 2,470 (BD/MDD = 1,333/1,137) hospitalized patients in Shanghai as training sets and 2,143 (BD/MDD = 955/1,188) in Hangzhou as test sets. A total of 35 clinical biochemical indexes were tested, including blood cells, immuno-inflammatory factors, liver enzymes, glycemic and lipid parameters, and thyroid and gonadal hormones. A stepwise analysis of a multivariable logistic regression was performed to build a predictive model to identify BD and MDD.
Most of these biochemical indexes showed significant differences between BD and MDD groups, such as white blood cell (WBC) in the hematopoietic system, uric acid (UA) in immuno-inflammatory factors, direct bilirubin (DBIL) in liver function, lactic dehydrogenase (LDH) in enzymes, and fasting blood glucose (FBG) and low-density lipoprotein (LDL) in glucolipid metabolism (-values < 0.05). With these predictors for discrimination, we observed the area under the curve (AUC) of the predictive model to distinguish between BD and MDD to be 0.772 among men and 0.793 among women, with the largest AUC of 0.848 in the luteal phase of women. The χ values of internal and external validation for male and female datasets were 2.651/10.264 and 10.873/6.822 (-values < 0.05), respectively. The AUCs of the test sets were 0.696 for males and 0.707 for females.
Discrimination and calibration were satisfactory, with fair-to-good diagnostic accuracy and external calibration capability in the final prediction models. Female patients may have a higher differentiability with a conventional biochemical index than male patients.
ICTRP NCT03949218. Registered on 20 November 2018. Retrospectively registered. https://www.clinicaltrials.gov/ct2/show/NCT03949218?id=NCT03949218&rank=1.
传统生化指标在双相情感障碍(BD)和重度抑郁症(MDD)的临床鉴别中可能具有预测价值。
本研究纳入上海的2470例住院患者(BD/MDD = 1333/1137)作为训练集,杭州的2143例患者(BD/MDD = 955/1188)作为测试集。共检测了35项临床生化指标,包括血细胞、免疫炎症因子、肝酶、血糖和血脂参数以及甲状腺和性腺激素。进行多变量逻辑回归的逐步分析以建立鉴别BD和MDD的预测模型。
这些生化指标中的大多数在BD组和MDD组之间显示出显著差异,例如造血系统中的白细胞(WBC)、免疫炎症因子中的尿酸(UA)、肝功能中的直接胆红素(DBIL)、酶中的乳酸脱氢酶(LDH)以及糖脂代谢中的空腹血糖(FBG)和低密度脂蛋白(LDL)(P值<0.05)。利用这些鉴别预测指标,我们观察到鉴别BD和MDD的预测模型在男性中的曲线下面积(AUC)为0.772,在女性中为0.793,女性黄体期的AUC最大为0.848。男性和女性数据集的内部和外部验证的χ²值分别为2.651/10.264和10.873/6.822(P值<0.05)。测试集的AUC男性为0.696,女性为0.707。
最终预测模型的鉴别和校准效果良好,诊断准确性和外部校准能力中等至良好。女性患者使用传统生化指标可能比男性患者具有更高的可区分性。
ICTRP NCT03949218。于2018年11月20日注册。回顾性注册。https://www.clinicaltrials.gov/ct2/show/NCT03949218?id=NCT03949218&rank=1。