外周血免疫炎症指标在疾病早期区分单双相抑郁的价值
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国家自然科学基金(82101600);北京市医院管理中心培育计划项目(PX2022076)


The value of peripheral immunoinflammatory markers to distinguish bipolar depression from unipolar depression in the early stage
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    摘要:

    目的 探索可在疾病早期区分双相抑郁与单相抑郁的外周血免疫炎症指标并构建预测 模型,为双相抑郁与单相抑郁的早期鉴别、早期治疗提供依据。方法 选取 2013 年 1 月至 2019 年 12 月 在首都医科大学附属北京安定医院住院≥ 2 次,且首次入院时诊断为抑郁障碍的患者 487 例,根据此后 住院记录中的诊断分为单相抑郁组 357 例和双相抑郁组 130 例。通过倾向性评分匹配法,两组各纳入 102 例患者。比较两组患者首次住院时的一般资料及中性粒细胞 / 淋巴细胞比值(NLR)、单核细胞 / 淋巴 细胞比值(MLR)、血小板 / 淋巴细胞比值(PLR)、C 反应蛋白(CRP)、补体 3(C3)、补体 4(C4)、免疫球蛋白 A (IgA)、免疫球蛋白 G(IgG)、免疫球蛋白 M(IgM)。采用二项 Logistic 回归分析控制混杂因素,探索双相抑 郁的早期预测因子。采用受试者工作特征(ROC)曲线分析免疫炎症因子对双相抑郁的早期预测价值。 结果 单相抑郁组与双相抑郁组的 NLR、MLR、C3、CRP 比较差异有统计学意义(Z=2.004、3.062、2.333、 2.233;P< 0.05)。二项 Logistic 回归分析显示,MLR(OR=1.631,95%CI=1.206~2.194)和 C3(OR=1.195, 95%CI=1.033~1.383)是双相抑郁的影响因素(P< 0.05)。ROC 曲线分析结果显示,Logistic 回归模型 预测双相抑郁的 AUC 为 0.669,敏感度为 78.4%,特异度为 53.9%。结论 MLR 及 C3 水平升高可能是双 相抑郁的早期预测指标。

    Abstract:

    Objective To explore the peripheral blood immunoinflammatory indicators that can distinguish bipolar depression from unipolar depression in the early stage of the disease, and build a prediction model to provide evidence for the early identification and early treatment of bipolar depression. Methods Patients who have been hospitalized at least 2 times in Beijing Anding Hospital, Capital Medical University between January 2013 and December 2019 were recruited as research subjects. A total of 487 patients diagnosed with major depressive disorder at the first admission were included, who were divided into unipolar depression group (357 cases) and bipolar depression group (130 cases) according to whether they were diagnosed with bipolar disorder in the subsequent admission records. 102 patients were included in each of the two groups by the propensity score matching method. The demographic data and immunoinflammatory factors of the first hospitalization were compared between the two groups. The selected immunoinflammatory factors include neutrophil count to lymphocyte count ratio (NLR), monocyte count to lymphocyte count ratio (MLR),platelet count to lymphocyte count ratio (PLR), C-reactive protein (CRP), complement 3 (C3), complement 4 (C4), immunoglobulin A (IgA), immunoglobulin G (IgG) and immunoglobulin M (IgM). Binomial Logistic regression analysis was used to control confounding factors to explore the early predictors for bipolar disorder. Receiver operating characteristic (ROC) curve was used to analyze the early predictive value of the selected immunoinflammatory factors for bipolar disorder. Results There were statistical differences in NLR, MLR, C3 and CRP between unipolar depression group and bipolar depression group (Z=2.004,3.062,2.333,2.233; P < 0.05). Binomial Logistic regression analysis showed that MLR (OR=1.63, 95%CI=1.206-2.194) and C3 (OR=1.195, 95%CI=1.033-1.383) were early predictors of bipolar depression. ROC analysis showed that the AUC of Logistic regression model for predicting bipolar depression was 0.669, with a sensitivity of 78.4% and a specificity of 53.9%. Conclusions Elevated MLR and C3 levels may be an early predictor of bipolar depression

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吕楠,李金红,付冰冰,王瀚,黄娟,张蒙,赵茜.外周血免疫炎症指标在疾病早期区分单双相抑郁的价值[J].神经疾病与精神卫生,2023,23(4).
DOI :10.3969/j. issn.1009-6574.2023.04.002.

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  • 在线发布日期: 2023-05-30