3种免疫营养评分工具对重症卒中并发肺部感染风险的预测价值比较  

Comparison of predictive value among three kinds of immuno-nutrition scoring tools for risk of severe stroke complicating lung infection

作　　者：周姝宏 阳佳家 李君卓 刘光维[1,2] ZHOU Shuhong;YANG Jiajia;LI Junzhuo;LIU Guangwei(Department of Nursing,First Affiliated Hospital of Chongqing Medical University,Chongqing 400016,China;Department of Neurology,First Affiliated Hospital of Chongqing Medical University,Chongqing 400016,China)

机构地区：[1]重庆医科大学附属第一医院护理部,重庆400016 [2]重庆医科大学附属第一医院神经内科,重庆400016

出　　处：《重庆医学》2024年第17期2608-2613,共6页Chongqing Medical Journal

基　　金：重庆市重点专科建设《临床护理》精品建设项目(0203[2023]47号202336)。

摘　　要：目的比较控制营养状况评分(CONUT)、预后营养指数(PNI)、预后炎症和营养指数(PINI)对重症卒中并发肺部感染(SCLI)的预测价值,分析重症SCLI发生的危险因素。方法回顾性分析2022年8月至2023年8月于该院神经重症监护病房(NICU)首次就诊的98例重症卒中患者临床资料,根据住院期间是否发生SCLI分为SCLI组和非SCLI组。采用logistic回归分析影响重症SCLI的独立危险因素,计算3种工具预测重症SCLI的灵敏度、特异度、Youden指数、Kappa值并绘制受试者工作特征(ROC)曲线及曲线下面积(AUC)。结果98例患者住院期间发生SCLI的有35例(35.71%)。多因素logistic回归分析,结果显示,使用机械通气(OR=1.33,95%CI:1.06~2.76)、使用鼻胃管(OR=1.42,95%CI:1.25~2.68)、高CONUT(OR=2.74,95%CI:2.02~3.69)、低PNI(OR=0.70,95%CI:0.51~0.96)与低PINI(OR=2.51,95%CI:1.78~3.62)是重症SCLI的独立危险因素(P<0.05)。CONUT、PNI、PINI预测SCLI的ROC曲线的AUC分别为0.729、0.723、0.697,灵敏度分别为0.707、0.685、0.631,特异度分别为0.872、0.764、0.712,Youden指数分别为0.579、0.449、0.343,Kappa值分别为0.621、0.534、0.432(P<0.05)。结论CONUT、PNI、PINI均与SCLI风险相关,CONUT对重症SCLI预测价值最高。Objective To compare the predictive value of controlling nutritional status score(CONUT),prognostic nutritional index(PNI)and prognostic inflammation and nutritional index(PINI)for severe stroke complicating lung infection(SCLI),and to analyze the risk factors for severe SCLI occurrence.Methods A retrospective analysis on the clinical data of 98 cases of severe stroke firstly visited and treated in the nervous intensive care unit(NICU)of this hospital from August 2022 to August 2023 was performed.The patients were divided into the SCLI group and non-SCLI group according to whether or not SCLI occurring during the hospitalization.Logistic regression was used to analyze the independent risk factors influencing severe SCLI.The sensitivity,specificity,Youden index and Kappa value of the three tools in predicting severe SCLI were calculated,and the area under the receiver operating characteristic(ROC)curve(AUC)was plotted.Results Among 98 cases,there were 35 cases(35.71%)of SCLI occurrence during hospitalization.The multivariate logistic regression analysis results showed that the mechanical ventilation use(OR=1.33,95%CI:1.06-2.76),nasogastric tube use(OR=1.42,95%CI:1.25-2.68),high CONUT(OR=2.74),95%CI:2.02-3.69),low PNI(OR=0.70,95%CI:0.51-0.96)and low PINI(OR=2.51,95%CI:1.78-3.62)were the independent risk factors for severe SCLI(P<0.05).AUC of the ROC curve of CONUT,PNI and PINI for predicting SCLI was 0.729,0.723 and 0.697 respectively.The sensitivity was 0.707,0.685 and 0.631,and the specificity was 0.872,0.764 and 0.712,respectively.The Youden index was 0.579,0.449 and 0.343 respectively,and the Kappa value was 0.621,0.534 and 0.432 respectively.Conclusion CONUT,PNI and PINI all are correlated with the SCLI risk.CONUT has the highest predictive value for SCLI.

关 键 词：重症卒中 卒中并发肺部感染 控制营养状况评分 预后炎症和营养指数 预后营养指数 

分 类 号：R743.3[医药卫生—神经病学与精神病学]