重症急性胰腺炎继发胰腺坏死组织感染早期预警指标研究

A study on early prediction of infected pancreatic necrosis in patients with severe acute pancreatitis

目的 探究重症急性胰腺炎(SAP)继发胰腺坏死组织感染(IPN)的早期预警指标。方法 回顾性分析湖南省人民医院2012—2019年SAP病人临床资料,收集人口学特征、病因、发病后48 h内的临床数据和发病72 h后的急性胰腺炎严重指数(CTSI)评分,采用多因素Logistic回归分析IPN的影响因素,用ROC曲线比较Logistic回归模型、CTSI、急性胰腺炎严重程度床边指数(BISAP)、急性生理与慢性健康状况评分系统Ⅱ(APACHEⅡ)、序贯器官衰竭评估(SOFA)评分的预测效能,并分析各评分预测IPN的cutoff值。结果 SAP病人共277例,IPN组74例,对照组203例。Logistic回归分析示:谵妄(OR=4.049,95%CI 1.058~15.500,P=0.041)是IPN的危险因素,血细胞比容(Hct)(OR=0.939,95%CI 0.897~0.983,P=0.007)是IPN的保护性因素。Logistic回归模型、CTSI、BISAP、APACHEⅡ、SOFA预测IPN的ROC曲线下面积依次为0.719、0.702、0.622、0.593和0.561;各评分预测IPN的cutoff值:CTSI≥7分、BISAP≥3分、APACHEⅡ≥14分,SOFA≥5分。结论 早期谵妄和Hct下降可预警SAP后期继发IPN,建议及时转诊IPN高危病人。

Objective To explore the early warning signs of infected pancreatic necrosis(IPN)secondary to severe acute pancreatitis(SAP).Methods Clinical data of SAP in Hunan Provincial People’s Hospital from 2012 to 2019 were retrospectively analyzed.The demographic characteristics,past medical history,etiology,organ failure,library data in 48 h,and CTSI score at 72 hours after onset were collected.The risk factors of IPN were analyzed by multivariate binary Logistic regression analysis,the ROC curve was used to compare the predictive power of the Logistic regression model,CTSI,BISAP,APACHEⅡ,and SOFA scores,and the cutoff value of each score for predicting IPN was analyzed.Results There were 277 SAP patients,74 in the IPN group and 203 in the control group.Logistic regression analysis showed that delirium(OR=4.049,95%CI 1.058~15.500,P=0.041)was a risk factor for IPN,but hematocrit(Hct)(OR=0.939,95%CI 0.897~0.983,P=0.007)was a protective factor for IPN.The areas under the ROC curve of the Logistic regression model,CTSI,BISAP,APACHEⅡ,and SOFA were 0.719,0.702,0.622,0.593,and 0.561 respectively.The cutoff values of IPN predicted were CTSI≥7 points,BISAP≥3 points,APACHEⅡ≥14 points,and SOFA≥5 points respectively.Conclusion Early delirium and decreased Hct can predict IPN in the later stage of SAP,and it is recommended to transfer high-risk patients with IPN in time.