炎症标志物对急性缺血性脑卒中患者发生卒中后肺炎的预测价值OACSTPCD
Predictive value of inflammatory markers on the risk of stroke-associated pneumonia in acute ischemic stroke patients
目的 基于列线图模型探讨炎症标志物对急性缺血性脑卒中(AIS)患者发生卒中后肺炎(SAP)的预测价值.方法 根据是否发生肺炎将259 例AIS患者分为SAP组81 例与非SAP组178 例,比较两组患者的临床资料.根据公式计算出全身炎症反应指数(SIRI)、全身免疫炎症指数(SII)、中性粒细胞和淋巴细胞比值(NLR),将差异有统计学意义的变量纳入多因素二分类Logistic回归模型,筛选出AIS患者发生SAP的独立危险因素.将独立危险因素构建预测模型,进一步从区分度、校准度、临床实用性及等方面比较仅纳入传统因素和同时纳入炎症指标两个模型的预测能力.采用重分类分析评价列线图模型对AIS患者发生SAP风险预测价值的改善程度.结果 与非SAP组比较,SAP组吸烟、糖尿病、吞咽困难比率及白细胞、中性粒细胞、淋巴细胞、三酰甘油水平、入院时NIHSS评分、SIRI、SII、NLR显著升高,高血压比率显著降低(均P＜0.05).糖尿病(OR =2.505,95%CI:1.070～5.850,P =0.034)、吞咽困难(OR =3.492,95%CI:1.501～8.119,P =0.004)、入院NIHSS评分(OR =1.310,95%CI:1.188～1.446,P＜0.001)、SIRI(OR =2.417,95%CI:1.327～4.401,P =0.008)、NLR(OR =1.434,95%CI:1.101～1.860,P =0.007)是AIS患者发生SAP的独立危险因素.纳入独立危险因素构建列线图预测模型,不含炎症因子的预测模型与纳入炎症因子的列线图模型的曲线下面积分别为 0.788(95%CI:0.725～0.852,P＜0.001)和 0.884(95%CI:0.838～0.930,P＜0.001).校正曲线显示预测风险与观察结果之间具有良好的一致性.决策曲线显示该模型对预测SAP具有显著的净收益.此外,通过计算净重新分类指数和综合判别改善指数发现列线图模型预测AIS患者发生SAP风险方面有显著改善.内部验证也证明了列线图模型的可靠性.结论 入院时SIRI、NLR是AIS患者发生SAP的独立预测因素.在传统模型中加入SIRI及NLR可显著提高对AIS患者SAP发生风险的识别能力.
Objective To explore the predictive value of inflammatory markers for stroke-associated pneumonia(SAP)in patients with acute ischemic stroke(AIS)based on the nomogram model.Methods According to whether pneumonia occurred,259 AIS patients were divided into SAP group(81 cases)and non-SAP group(178 cases).The clinical data of the two groups were compared.The systemic inflammatory response index(SIRI),systemic immunoinflammatory index(SII)and neutrophil to lymphocyte ratio(NLR)were calculated according to the formula.The variables with statistically significant differences were included in the multivariate binary Logistic regression model to screen out the independent risk factors for SAP in AIS patients.The independent risk factors were used to construct a predictive model,and the predictive ability of the two models,which only included traditional factors and included inflammatory indicators at the same time,was further compared from the aspects of discrimination,calibration,clinical practicability and so on.Reclassification analysis was used to evaluate the extent to which the nomogram model improved the predictive value of SAP risk in AIS patients.Results Compared with those in the non-SAP group,the rates of smoking,diabetes,dysphagia,leukocytes,neutrophils,lymphocytes,triglyceride level,NIHSS score on admission,SIRI,SII and NLR were significantly increased in the SAP group,and the rate of hypertension was decreased(all P＜0.05).Diabetes mellitus(OR =2.505,95%CI:1.070-5.850,P =0.034),dysphagia(OR =3.492,95%CI:1.501-8.119,P =0.004),NIHSS score on admission(OR = 1.310,95%CI:1.188-1.446,P＜0.001),SIRI(OR =2.417,95%CI:1.327-4.401,P =0.008),NLR(OR =1.434,95%CI:1.101-1.860,P =0.007)were independent risk factors for SAP in AIS patients.The area under the curve was 0.788(95%CI:0.725-0.852,P＜0.001)for the prediction model without inflammatory factors and 0.884(95%CI:0.838-0.930,P＜0.001)for the prediction model with independent risk factors.The calibration curve showed a good consistency between the predicted risk and the observed results.The decision curve showed that the model had a significant net benefit for predicting SAP.In addition,by calculating the net reclassification index(NRI)and the comprehensive discriminant improvement index(IDI),it was found that the nomogram model had a significant improvement in predicting the risk of SAP in AIS patients.Internal verification also proves the reliability of the nomogram model.Conclusions SIRI and NLR are independent predictors of SAP in AIS patients on admission.Adding SIRI and NLR to the traditional model can significantly improve the ability to identify the risk of SAP occurrence in AIS patients.
刘海梅;符慧颖;白扬;刘颖;降建新
116000 大连医科大学研究生院延安大学咸阳医院神经内科南京医科大学附属泰州人民医院神经内科南京医科大学附属泰州人民医院神经外科
临床医学
全身炎症反应指数中性粒细胞和淋巴细胞比值缺血性脑卒中卒中后肺炎列线图
systemic inflammatory response indexneutrophil to lymphocyte ratioischemic strokestroke-associated pneumonianomogram
《临床神经病学杂志》 2024 (001)
9-14 / 6
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