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脑脊液/血清游离轻链指数驱动神经梅毒高效诊断模型构建与效能评估

Construction and Efficacy Evaluation of a Highly Efficient Diagnostic Model for Neurosyphilis Driven by the Cerebrospinal Fluid/Serum Free Light Chain Index

  • 摘要:
    目的 通过测定脑脊液(cerebrospinal fluid, CSF)和血清游离轻链(free light chains, FLC),计算FLC指数并建立模型,探讨该模型在神经梅毒诊断中的应用价值。
    方法 本研究纳入87例梅毒患者,其中包括48例神经梅毒患者(NS组)和39例非神经梅毒患者(n-NS组)。收集所有纳入患者的CSF和血清样本对,检测kappa游离轻链(FLC-κ)和lambda游离轻链(FLC-λ)含量,计算FLC指数、FLC-κ指数和FLC-λ指数。运用受试者工作特征(receiver operating characteristic, ROC)曲线对三个指数进行评价。建立以FLC指数为核心的神经梅毒诊断模型,并实现对其可视化验证。
    结果 两组患者在血清梅毒初筛结果、CSF有核细胞计数、CSF微量蛋白、CSF IgG、IgG合成率、IgG指数水平及白蛋白商等指标上差异有统计学意义(P<0.05)。FLC-κ指数、FLC-λ指数、白蛋白商的ROC曲线下面积(area under the curve, AUC)分别为0.998〔95%置信区间(confidence interval, CI):0.990~1.000)、0.988(95%CI:0.961~1.000)、0.635(95%CI:0.496~0.751〕。在FLC-κ指数的模型中FLC-κ指数(P<0.05)对神经梅毒诊断有显著影响,在FLC-λ指数的模型中仅FLC-λ指数(P<0.05)有显著影响。围绕FLC-κ指数建立的诊断模型其训练ROC曲线的AUC大于0.950,其校准曲线在预测概率接近80%时预测效能较好,在预测概率为40%~60%时预测效能较弱。围绕FLC-λ指数建立的诊断模型的AUC为0.926,其校准曲线在预测概率接近85%时预测效能较好,在预测概率为40%~70%时预测效能较弱。
    结论 FLC-κ和FLC-λ对神经梅毒均具有较高诊断性能,FLC指数在神经梅毒的诊断中有一定的应用价值。

     

    Abstract:
    Objective To determine free light chains (FLC) in cerebrospinal fluid (CSF) and serum, calculate the FLC index, and establish a model to evaluate its application value in diagnosing neurosyphilis.
    Methods This study included 87 syphilis patients, comprising 48 neurosyphilis patients (NS group) and 39 non-neurosyphilis patients (n-NS group). CSF and serum samples were collected from all patients to measure kappa free light chains (FLC-κ) and lambda free light chains (FLC-λ). The FLC index, FLC-κ index, and FLC-λ index were calculated. Receiver operating characteristic (ROC) curves were used to evaluate these indices. A neurosyphilis diagnostic model based on the FLC index was established and its visualization was verified.
    Results Statistically significant differences were observed between the two groups in serological syphilis screening, CSF nucleated cell count, CSF microprotein, CSF IgG, IgG synthesis rate, IgG index, and albumin quotient (P < 0.05). The areas under the ROC curves (AUC) for the FLC-κ index, FLC-λ index, and albumin quotient were 0.998 (95% CI: 0.990-1.000), 0.988 (95% CI: 0.961-1.000), and 0.635 (95% CI: 0.496-0.751), respectively. In the FLC-κ index model, the FLC-κ index (P < 0.05) significantly affected the diagnosis of neurosyphilis, while in the FLC-λ index model, only the FLC-λ index (P < 0.05) had a significant effect. The training ROC curve AUC for the diagnosis model based on the FLC-κ index was greater than 0.950. Its calibration curve showed good predictive performance when the predicted probability was close to 80%, but poor performance when the predicted probability was 40%-60%. The AUC for the diagnosis model based on the FLC-λ index was 0.926, with good predictive performance when the predicted probability was close to 85%, and poor performance when the predicted probability was 40%-70%.
    Conclusion FLC-κ and FLC-λ have high diagnostic performance for neurosyphilis, and the FLC index has certain application value in the diagnosis of neurosyphilis.

     

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