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血清和尿液联合检测免疫球蛋白结合蛋白1在狼疮性肾炎中的预测价值

Predictive value of combined testing for immunoglobulin binding protein 1 in serum and urine in lupus nephritis

    摘要
  • 摘要:
    目的 探讨血清和尿液联合检测免疫球蛋白结合蛋白1(IGBP1)在狼疮性肾炎(LN)中的预测价值。
    方法 选取2021年1月—2022年12月LN患者60例为LN组，选取同期诊治的系统性红斑狼疮(SLE)患者60例作为SLE组，比较2组血清IGBP1、尿IGBP1水平，并分析血清IGBP1、尿IGBP1单独及二者联合检测对LN的预测价值。
    结果 LN组血清IGBP1、尿IGBP1水平高于SLE组，差异有统计学意义(P＜0.05)。二元Logistic回归分析结果显示，血清IGBP1、尿IGBP1是LN的影响因素(P＜0.05)。受试者工作特征(ROC)曲线分析显示，血清IGBP1、尿IGBP1、联合检测LN的曲线下面积(AUC)分别为0.856、0.834、0.902, 约登指数分别为0.533、0.533、0.666, 血清IGBP1的敏感度、特异度分别为85.0%、68.3%, 尿IGBP1的敏感度、特异度分别为53.3%、100.0%, 联合检测的敏感度、特异度分别78.3%、88.3%。
    结论 血清IGBP1、尿IGBP1在LN患者中呈高表达，二者联合对LN具有较高的预测价值。

     

    Abstract:
    Objective To explore the predictive value of combined detection of immunoglobulin binding protein 1 (IGBP 1) in serum and urine in lupus nephritis (LN).
    Methods A total of 60 LN patients were selected as LN group, and 60 SLE erythematosus (SLE) patients in the same period were selected as SLE group, the serum IGBP 1 and urinary IGBP 1 levels between the two groups were compared, and the value of serum IGBP 1, urinary IGBP 1 and their combination in predicting LN was analyzed.
    Results Serum IGBP 1 and urinary IGBP 1 in the LN group were significantly higher than those in the SLE group (P < 0.05). Binary Logistic regression analysis showed that serum IGBP 1 and urinary IGBP 1 were risk factors for LN (P < 0.05). Receiver Operating Characteristic (ROC) curve revealed that the area under the curve (AUC) for serum IGBP1, urinary IGBP1, and their combined detection for LN was 0.856, 0.834, and 0.902, respectively. The Youden index was 0.533, 0.533, and 0.666, respectively. The sensitivity and specificity of serum IGBP1 were 85.0% and 68.3%, respectively. The sensitivity and specificity of urinary IGBP1 were 53.3% and 100.0%, respectively. The sensitivity and specificity of the combined detection were 78.3% and 88.3%, respectively.
    Conclusion Serum IGBP 1 and urinary IGBP 1 are highly expressed in LN patients, and their combination has a high predictive value for LN.

     

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