Predictive Value Of Preoperative SⅡ For AKI After Heart Valve Replacement And Construction Of Predictive Model

Objective:The systemic immune inflammatory index(SII)is a novel immune inflammatory index based on peripheral lymphocyte,neutrophil and platelet counts.It has been proved that it has a high predictive value for the prognosis of cancer and acute pancreatitis,but the predictive value of SII in cardiovascular system diseases is still controversial,and there are few related research reports.A report on the prediction of complications.This study intends to investigate the predictive value of preoperative SII for acute kidney injury(AKI)after heart valve replacement through retrospective analysis,and to construct a predictive model for AKI.Methods:By consulting the hospital’s electronic medical record system,the clinical data of 235 patients who underwent heart valve replacement surgery from January 2020 to September 2021 in the Cardiac and Great Vascular Surgery Department of the Affiliated Hospital of North Sichuan Medical College were collected in strict accordance with the inclusion and exclusion criteria.The data were collected,and the data of 199 patients who met the requirements were finally included for research.According to whether AKI occurred after surgery,they were divided into AKI group(91 cases)and non-AKI group(108 cases).The diagnostic criteria of AKI were based on the KDIGO diagnostic criteria.Statistical analysis was performed using SPSS21.0 software,with P=0.05 as the test level for comparison between groups.For descriptive statistics,the measurement data were tested for normality by the Kolmogorov-Smirnov method,and it was found that each measurement data did not conform to the normal distribution,so the measurement data were represented by the median(25th quantile,75th quantile).Number of cases and percentage(%)representation.Measurement data were compared between groups using the Mann-Whitney U nonparametric rank-sum test.For comparison of count data between groups,chi-square test or Fisher’s exact test were used.Rank data were compared between groups using the Mann-Whitney U nonparametric rank-sum test.Multivariate Logistic regression analysis was used for correlation analysis.The independent variables were meaningful indicators in univariate analysis.The results were adjusted by odds ratios(OR)and corresponding 95%confidence intervals(CI).Express.The β regression coefficient of each independent risk factor was obtained by multivariate Logistic regression analysis,the regression equation was obtained and the prediction model was constructed.The receiver operating characteristic curve(ROC)was used to evaluate the predictive value.Results:In this study,91 cases of AKI occurred after valve replacement,the incidence rate was 45.7%.The results of univariate analysis showed that compared with the non-AKI group,the AKI group was older,had higher preoperative cardiac function classification,higher proportion of hypertension,higher proportion of renal organic abnormality,greater ventricular septal thickness,SII,creatinine(Cr),cystatin C(CysC)values were higher,hemoglobin(Hb),estimated glomerular filtration rate(eGFR)lower;intraoperative cardiopulmonary bypass time,longer aortic occlusion time,intraoperative red blood cell unit number,intraoperative plasma infusion volume,and intraoperative urine volume less;postoperative pulmonary infection rate,low cardiac output syndrome rate,secondary The proportion of tracheal intubation and mortality were higher,and the stay time in the intensive care unit,postoperative intubation time,and postoperative hospitalization days were longer,and the differences were statistically significant(all P<0.05).In order to further explore the correlation between the 17 preoperative and intraoperative indicators with P<0.05 in univariate analysis and postoperative AKI,we performed multivariate Logistic regression analysis and obtained SII(OR=1.001,95%CI:1.000-1.002,P=0.008),age(OR=1.064,95%CI:1.026-1.104,P=0.001),preoperative Cr(OR=1.027,95%CI:1.006-1.048,P=0.010),aortic resistance Disconnection time(OR=1.013,95%CI:1.004-1.023,P=0.006)was an independent risk factor for AKI after valve replacement(OR>1).From the multivariate Logistic regression results,we obtained the regression equation:Y=0.062*age+0.001*SII+0.026*Crr+0.013*aortic occlusion time-8.113(Y represents the probability of postoperative AKI),and constructed the postoperative occurrence of AKI For the prediction model of AKI,in order to further evaluate the predictive value of SII and the prediction model,we used the ROC curve.The results of ROC curve analysis showed that the area under the curve(AUC)of preoperative SII for predicting AKI after valve replacement was 0.705(95%CI=0.633-0.777),and the optimal cut-off value was 428.381×10^9/L,its sensitivity was 72.5%,and its specificity was 63.0%.The AUC of the prediction model to predict AKI after valve replacement was 0.800(95%CI=0.738-0.861),the optimal cut-off value was 7.605,the sensitivity was 73.6%,and the specificity was 77.8%.Conclusion:(1)Preoperative SII is an independent risk factor for AKI after heart valve replacement,and it has a good predictive value for the occurrence of AKI after heart valve replacement.(2)This study also found that age,preoperative creatinine value,and intraoperative aortic occlusion time were also independent risk factors for AKI after heart valve replacement,and had certain predictive value for the occurrence of AKI after heart valve replacement.(3)The predictive model constructed by combining preoperative SII,age,preoperative creatinine value,and intraoperative aortic occlusion time has greater predictive value for AKI after heart valve replacement than the individual indicators,and has important clinical value.