摘要
目的:探讨平均血小板体积/血小板计数比值(MPV/PLT)对重症急性胰腺炎(SAP)肾损伤病人的病情评估作用.方法:60例SAP病人根据入院28 d存活情况分为存活组(42例)及死亡组(18例),根据是否满足急性肾损伤(AKI)诊断标准又分为AKI组(23例)和非AKI组(37例).入院后收集病人的基线资料和临床数据,包括年龄、性别、基础病(高血压、糖尿病)、APACHE Ⅱ评分、序贯器官衰竭评估(SOFA)评分、平均血小板体积(MPV)、血小板计数(PLT)、C反应蛋白(CRP)、血清肌酐(Scr)和尿素氮(BUN).采用Pearson相关性分析入院时病人MPV/PLT与APACHE Ⅱ评分、SOFA评分及CRP的相关性;利用受试者工作特征曲线(ROC)分析MPV/PLT对SAP合并AKI病情的预测价值;采用多因素logistic回归分析SAP合并AKI的独立危险因素.结果:在性别、年龄、基础病(高血压、糖尿病)方面,非AKI组和AKI组差异均无统计学意义(P>0.05);AKI组病人的CRP、Scr、BUN、MPV、SOFA评分及APACHE Ⅱ评分均明显高于非AKI组(P<0.05～P<0.01);AKI组病人的PLT水平明显低于非AKI组(P<0.01).预后结果显示,在性别方面存活组与死亡组的差异无统计学意义(P>0.05);死亡组病人的年龄、CRP、Scr、BUN、MPV、SOFA评分及APACHE Ⅱ评分均明显高于存活组(P<0.05～P<0.01);死亡组病人的PLT水平明显低于存活组(P<0.01);Pearson相关分析表明:SAP病人MPV/PLT与APACHE Ⅱ评分、SOFA评分与CRP均呈正相关(r=0.725、0.818、0.747,P<0.01);ROC曲线分析表明,MPV/PLT对预测SAP合并AKI和28 d死亡的ROC曲线下面积分别为0.616和0.816,敏感度分别为91.30％和94.40％,特异度分别为70.30％和57.10％;对SAP合并AKI多因素logistic回归分析表明,MPV/PLT、BUN及Scr可以作为判断SAP合并AKI的独立危险因素(P<0.05),而APACHE Ⅱ评分、SOFA评分及CRP不能作为SAP合并AKI的独立危险因素(P>0.05).结论:MPV/PLT升高可以早期预测SAP合并AKI的发生,并且在评估病人预后方面发挥重要价值,MPV/PLT升高可以作为判断SAP合并AKI的独立危险因素.
Abstract
Objective:To evaluate the role of mean platelet volume/platelet count ratio (MPV/PLT) in the evaluation of renal injury in severe acute pancreatitis (SAP).Methods:A total of 60 patients with SAP were divided into survival group (n=42) and death group (n=18) based on their 28 days survival after admission.SAP patients were divided into acute kidney injury (AKI) group (n=23) and non-AKI group (n=37) according to whether they fulfilled the diagnostic criteria of AKI.The baseline data and clinical data of the patients,including age,gender,underlying diseases (hypertension,diabetes mellitus),APACHE Ⅱ score,SOFA score,mean platelet volume (MPV),platelet count (PLT),C reaction protein (CRP),creatinine (Scr) and blood urea nitrogen (BUN),were collected after admission.The correlation between MPV/PLT and APACHE Ⅱscore,SOFA score and CRP of patients at admission was analyzed using Pearson correlation.The predictive value of MPV/PLT for AKI condition combined with SAP was analyzed using receiver operating characteristic (ROC) curve.Multivariate logistic regression was used to analyze the independent risk factors of SAP combined with AKI.Results:In terms of gender,age and underlying diseases (hypertension,diabetes mellitus),there were no significant differences between non-AKI group and AKI group (P>0.05).The CRP,SCR,BUN,MPV,SOFA scores and APACHE Ⅱ scores of patients in the AKI group were significantly higher than those in the non-AKI group (P<0.05 to P<0.01).The PLT levels of patients in the AKI group were significantly lower than those in the non-AKI group (P<0.01).In terms of gender,there was no significant difference between survival group and death group (P>0.05).The age,CRP,SCR,BUN,MPV,SOFA score and APACHE Ⅱscore of patients in the death group were significantly higher than those in the survival group (P<0.05 to P<0.01).The PLT levels of patients in the death group were significantly lower than those in the survival group (P<0.05).Pearson correlation analysis showed that MPV/PLT was significantly correlated with APACHE Ⅱ score,SOFA score and CRP in SAP patients (r=0.725,0.818,0.747,P<0.01).ROC curve analysis showed that MPV/PLT had a sensitivity of 91.30％ and 94.40％ and specificity of 70.30％ and 57.10％,respectively,with an area under the ROC curve of 0.616 and 0.816,respectively,for predicting SAP combined with AKI and 28-d death.Multivariate logistic regression analysis of SAP combined with AKI showed that MPV/PLT,BUN and Scr could be used as independent risk factors for determining SAP combined AKI (P<0.05),while APACHE Ⅱ score,SOFA score and CRP could not be used as independent risk factors for SAP combined AKI (P>0.05).Conclusions:Elevated MPV/PLT can early predict the occurrence of SAP combined with AKI and plays an important value in evaluating the prognosis of patients,especially elevated MPV/PLT can be used as an independent risk factor for judging SAP combined with AKI.
基金项目
安徽省高等学校自然科学研究重点项目(2022AH051437)
安徽省高等学校自然科学研究重点项目(KJ2021A0813)
安徽省高等学校自然科学研究重点项目(KJ2021A0767)
维普
万方数据