The role of albumin-bilirubin index in Nomogram prediction of acute pancreatitis complicated with multiple organ dysfunction syndrome
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摘要: 目的 探索白蛋白-胆红素指数(ALBI)在急性胰腺炎(AP)并发多器官功能障碍综合征(MODS)Nomogram风险预测中的作用。方法 回顾性分析华中科技大学同济医学院附属同济医院重症医学科收治的229例AP患者的临床资料，根据是否并发MODS分成MODS组和非MODS组。通过多因素logistic回归分析确定AP并发MODS的高危预测因素并通过R语言建立Nomogram图预测模型。使用受试者工作特征曲线(ROC)评价Nomogram图的预测能力，同时，使用Bootstrap自抽样内部验证法和一致性指数(C-index)验证Nomogram图风险预测效果的准确性。结果 多因素logistic回归分析结果提示ALBI指数、急性生理与慢性健康状况评分Ⅱ(APACHEⅡ)和氧合指数(PF)是AP并发MODS的高危因素。其中，ALBI指数的AUC值(0.967)、灵敏度(91.72%)和特异度(98.33%)均显著高于APACHEⅡ评分和PF。基于ALBI指数(回归系数=10.080)构建的Nomogram图风险预测模型预测AP并发MODS的C-index及AUC值均为0.997(95%CI：0.9924~1.000，P< 0.05)。模型校准曲线显示预测概率与实际发生概率趋于一致。结论 以ALBI指数为核心，联合APACHEⅡ评分和PF构建的Nomogram图风险预测模型可以有效预测AP并发MODS。
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关键词:
- 急性胰腺炎 /
- 多器官功能障碍综合征 /
- 白蛋白-胆红素指数 /
- Nomogram图
Abstract: Objective To explore the role of albumin-bilirubin index(ALBI) in Nomogram prediction of acute pancreatitis(AP) complicated with multiple organ dysfunction syndrome(MODS)Methods Clinical data of 229 patients with AP admitted to Tongji Hospital in Wuhan were retrospectively collected. The patients were divided into MODS groups and non-MODS groups based on whether MODS were concurrent or not. Multivariate logistic regression analysis was used to determine the high-risk predictors of AP complicated with MODS, and a Nomogram was drawn combined with R language. Receiver operating characteristic curve(ROC) was used to evaluate the prediction ability of the Nomogram. Meanwhile, Bootstrap self-sampling internal validation method and consistency index(C-index) were used to verify the accuracy of the prediction effect of the Nomogram.Results Multivariate logistic regression analysis indicated that ALBI, acute physiology and chronic health status score Ⅱ(APACHE Ⅱ) and oxygenation index(PF) ALBI were risk factors for AP complicated with MODS. Among them, the AUC value(0.967), sensitivity(91.72%) and specificity(98.33%) of ALBI index were significantly higher than those of the APACHE Ⅱ score and PF. The C index and AUC value of Nomogram prediction model based on ALBI index(regression coefficient=10.080) was 0.997 in predicting AP complicated with MODS(95%CI: 0.9924~1.000,P< 0.05). The calibration curve showed a good fit between the predicted probability and actual probability.Conclusion The Nomogram prediction model based on ALBI index, accompanied with APACHE Ⅱ score and PF can effectively predict AP complicated with MODS. -
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表 1 非MODS组和MODS组患者临床数据比较
X±S 项目 非MODS组(60例) MODS组(169例) χ2/Z /t P 年龄/岁 51.217±2.255 55.130±1.284 -1.541 0.125 APACHE Ⅱ评分 10.533±0.749 17.775±0.668 -7.216 < 0.001 SOFA评分 2.367±0.213 7.521±0.194 -17.911 < 0.001 GCS评分 14.567±0.165 13.006±0.198 6.051 < 0.001 D-Dimer/(mg·L-1) 2.954±0.427 6.618±0.925 -3.599 < 0.001 PT/s 15.223±0.330 17.735±0.512 -4.124 < 0.001 PF/mmHg 352.347±15.655 225.876±9.450 6.873 < 0.001 体温/℃ 37.023±0.113 36.924±0.057 0.855 0.394 MAP/mmHg 96.799±1.828 89.193±1.712 3.038 0.003 BNP/(pg·mL-1) 1579.605±922.767 4771.122±915.622 -2.455 0.015 AMY/(U·L-1) 889.900±216.968 956.964±84.797 -0.349 0.727 LIP/(U·L-1) 1018.933±142.179 1479.414±161.152 -1.623 0.106 WBC/(×10 9·L-1) 14.461±0.816 15.041±0.626 -0.500 0.617 RBC/(×10 9·L-1) 4.132±0.105 4.089±0.082 0.319 0.750 Hb/(g·L-1) 128.442±3.682 124.216±2.606 0.863 0.389 Hct/% 36.803±0.949 35.221±0.842 1.247 0.214 PLT/(×10 9·L-1) 194.317±9.448 138.858±6.323 4.616 < 0.001 ALT/(U·L-1) 30.550±4.970 139.994±24.382 -4.398 < 0.001 AST/(U·L-1) 47.333±7.365 261.456±50.141 -4.225 < 0.001 ALB/(g·L-1) 32.372±0.357 27.182±0.427 9.332 < 0.001 ALBI/分 -2.545±0.041 -1.290±0.043 -21.015 < 0.001 TBIL/(μmol·L-1) 11.585±0.815 36.795±3.715 -6.629 < 0.001 Cr/(μmol·L-1) 126.387±22.184 279.157±21.695 -4.923 < 0.001 注：1 mmHg=0.133kPa; BNP：B型钠利尿肽; AMY：血清淀粉酶; LIP：血清脂肪酶; WBC：白细胞计数; RBC：红细胞计数; Hb：血红蛋白含量; Hct：血细胞比容。 
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表 2 AP并发MODS的logistics回归分析结果
相关因素 B 标准误 Wald P APACHE Ⅱ评分 0.463 0.213 4.713 0.0299 PF -0.018 0.009 4.056 0.0440 ALBI指数 10.080 3.235 9.707 0.0018
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表 3 各高危因素对并发MODS的预测作用
相关因素 截断值 AUC 灵敏度/% 特异度/% 约登指数 多因素联合 0.997 96.72 99.40 APACHE Ⅱ评分 12 0.775 72.19 75.00 0.4719 PF 280 0.787 72.78 81.67 0.5445 ALBI指数 2.091 0.967 91.72 98.33 0.9005
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