Correlation analysis of the inflammatory burden index with the severity of Guillain-Barré syndrome
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摘要:
目的 探讨新型炎症标志物炎症负荷指数(IBI)与吉兰-巴雷综合征(GBS)患者病情严重程度的关系及其预测价值。 方法 回顾性选取徐州医科大学附属医院2014年1月—2022年9月首诊为GBS的患者160例，根据Hughes功能分级量表(HFGS)评分将其分为轻型组(52例)和重型组(108例)，收集2组患者一般资料、IBI及传统炎症指标，并进行统计学分析。采用ROC曲线评估IBI对重型GBS的预测价值；采用多因素logistic回归分析探讨重型GBS的影响因素。 结果 重型组患者入院时的IBI为13.15(4.06，56.78)，明显高于轻型组[3.32(1.93，8.87)]，差异有统计学意义(P＜0.001)；ROC分析结果显示，IBI预测重型组的ROC曲线下面积最大，为0.737(95% CI：0.660~0.815)；2组中性粒细胞与淋巴细胞比值(NLR)、血小板与淋巴细胞比值(PLR)、单核细胞与淋巴细胞比值(MLR)、IBI、全身免疫炎症指数(SII)、全身炎症反应指数(SIRI)比较差异均有统计学意义(P＜0.05)；多因素logistic分析结果显示，IBI≥11.00(OR=3.803，95% CI：1.631~8.868)和MLR≥0.42(OR=5.697，95% CI：1.109~29.272)是发生重型GBS的独立危险因素。 结论 IBI作为一种新兴的炎症指标，其水平升高与GBS患者病情严重程度有关，且与传统炎症指标相比，IBI对于重型GBS患者具有更高的预测价值。 Abstract:Objective To explore the relationship and predictive value of the novel inflammatory biomarker, inflammatory burden index (IBI) with the severity of Guillain-Barré syndrome (GBS). Methods Retrospective analysis was used to select 160 patients with GBS who were first diagnosed at the Affiliated Hospital of Xuzhou Medical University from January 2014 to September 2022. They were divided into the mild group (n=52) and the severe group (n=108) according to the Hughes functional grading scale (HFGS) score. Clinical data and inflammatory indicators, including IBI, were collected, and statistical analysis was conducted. Receiver operating characteristic (ROC) curve was used to evaluate the predictive value of IBI for severe GBS, while multivariate logistic regression analysis was employed to explore the factors influencing the severity of GBS. Results The IBI of patients in the severe group at admission was 13.15 (4.06, 56.78), which was significantly higher than that of patients in the mild group at 3.32 (1.93, 8.87), P < 0.001. The ROC analysis results show that the maximum area under the ROC curve predicted by IBI for the severe group was 0.737 (95% CI: 0.660-0.815). There were statistically significant differences in neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), monocyte-lymphocyte ratio (MLR), IBI, systemic immune inflammatory index (SII) and systemic inflammatory response index (SIRI) between the two groups (P < 0.05). The results of multivariate logistic analysis showed that IBI≥11.00 (OR=3.803, 95% CI: 1.631-8.868) and MLR≥0.42 (OR=5.697, 95% CI: 1.109-29.272) were independent risk factors for the occurrence of severe GBS. Conclusion The elevated level of IBI is correlated with the severity of GBS patients and possesses a high predictive value for identifying severe GBS cases. -
图 1 IBI、NLR、PLR、MLR、SII和SIRI预测GBS患者疾病严重程度的ROC曲线
Figure 1. ROC curves for IBI, NLR, PLR, MLR, SII, and SIRI in predicting the severity of GBS patients
表 1 本研究评估的6种常见的全身炎症性标志物计算公式
Table 1. The formulas for calculating six common systemic inflammatory markers assessed in this study
炎症标志物 计算公式 IBI C反应蛋白×中性粒细胞计数/淋巴细胞计数 NLR 中性粒细胞计数/淋巴细胞计数 PLR 血小板/淋巴细胞计数 MLR 单核细胞计数/淋巴细胞计数 SII 血小板×中性粒细胞计数/淋巴细胞计数 SIRI 单核细胞计数×中性粒细胞计数/淋巴细胞计数 
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表 2 2组GBS患者入院时的IBI、NLR、PLR、MLR、SII和SIRI比较[M(P25, P75)]
Table 2. The comparison of IBI, NLR, PLR, MLR, SII, and SIRI at admission between the two groups of GBS patients[M(P25, P75)]
组别 例数 IBI NLR PLR MLR SII(×109) SIRI(×109) 轻型组 52 3.32(1.93，8.87) 2.27(1.82，3.12) 134.52(103.78，172.34) 0.24(0.19，0.32) 603.33(413.35，820.37) 1.02(0.72，1.55) 重型组 108 13.15(4.06，56.78) 3.36(2.25，5.12) 168.17(122.45，220.83) 0.28(0.19，0.48) 726.67(496.41，1219.92) 1.31(0.75，2.77) Z值 -4.856 -3.789 -2.772 -2.370 -2.412 -2.080 P值 ＜0.001 ＜0.001 0.006 0.018 0.016 0.038
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表 3 NLR、PLR、MLR、IBI、SII和SIRI预测GBS患者疾病严重程度的ROC曲线下面积
Table 3. The area under the ROC curves for NLR, PLR, MLR, IBI, SII, and SIRI in predicting the severity of GBS patients
项目 AUC 95% CI SE P值 cut-off IBI 0.737 0.660~0.815 0.039 ＜0.001 11.00 NLR 0.685 0.602~0.769 0.043 ＜0.001 3.06 PLR 0.636 0.548~0.723 0.045 0.006 188.45 MLR 0.616 0.528~0.704 0.045 0.018 0.42 SII 0.618 0.530~0.705 0.045 0.016 989.84 SIRI 0.602 0.514~0.690 0.045 0.038 1.12
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表 4 影响GBS患者疾病严重程度的单因素分析[例(%)]
Table 4. Univariate analysis of factors influencing the severity of GBS patients [cases (%)]
项目 轻型组 重型组 χ2值 P值 性别 0.038 0.845 男性 29(55.8) 62(57.4) 女性 23(44.2) 46(42.6) 年龄 2.462 0.117 ≥60岁 15(28.8) 45(41.7) ＜60岁 37(71.2) 63(68.3) 前驱事件 前驱感染 27(100.0) 41(87.2) 2.799 0.094 外伤或手术 0 6(12.8) 3.001 0.083 高血压史 1.292 0.256 是 8(15.4) 25(23.1) 否 44(84.6) 83(76.9) 糖尿病史 0.052 0.820 是 2(3.8) 5(4.6) 否 50(96.2) 103(95.4) 吸烟史 0.620 0.431 是 4(7.7) 5(4.6) 否 48(92.3) 103(95.4) 饮酒史 0.358 0.550 是 3(5.8) 4(3.7) 否 49(94.2) 104(96.3) 脑脊液蛋白细胞分离 0.033 0.855 是 44(86.3) 92(85.2) 否 7(13.7) 16(14.8) IBI≥11.00 20.669 ＜0.001 是 10(19.2) 62(57.4) 否 42(80.8) 46(42.6) NLR≥3.06 15.639 ＜0.001 是 13(25.0) 63(58.3) 否 39(75.0) 45(41.7) PLR≥188.45 12.728 ＜0.001 是 7(13.5) 45(41.7) 否 45(86.5) 63(58.3) MLR≥0.42 16.853 ＜0.001 是 2(3.8) 36(33.3) 否 50(96.2) 72(66.7) SII≥989.84(×109) 14.498 ＜0.001 是 5(9.6) 42(38.9) 否 47(90.4) 66(61.1) SIRI≥1.12(×109) 7.258 0.007 是 19(36.5) 64(59.3) 否 33(63.5) 44(40.7)
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表 5 重型GBS发生的多因素logistic回归分析
Table 5. Multivariable logistic regression analysis of factors influencing severe GBS
变量 B SE Waldχ2 P值 OR值 95% CI IBI≥11.00 1.336 0.432 9.563 0.002 3.803 1.631~8.868 MLR≥0.42 1.740 0.835 4.342 0.037 5.697 1.109~29.272
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