Establishment Of A Risk Warning Model For Acute Kidney Injury In Patients With Type Aacute Aortic Dissection After Sugery

Objective:To analyze the perioperative risk factors and inflammatory factors for postoperative Acute Kidney Injury(AKI)in patients with Acute Type A Aortic Dissection(ATAAD)and to establish a risk warning model.Methods: A total of 111 patients who underwent ATAAD emergency surgery in Yijishan Hospital Affiliated to Wannan Medical College from January 2019 to July 2022 were selected.And the general clinical data of the patients were collected: age,gender(male/female),body mass index(BMI),history of hypertension,history of diabetes,chronic kidney disease,history of preoperative medication,pericardial effusion,preoperative systolic and diastolic blood pressure,history of medication,cardiac function classification,anemia,preoperative creatinine(Scr),preoperative lactic acid(Lac);intraoperative data included: anesthesia-related factors(anesthetic medication,intraoperative transfusion of suspended red blood cells,plasma,whether to use autologous platelet,the use of vasoactive drugs,whether to use furosemide and hormones etc.);surgery-related factors(anesthesia time,operation time,myocardial cross-clamping time,cardiopulmonary bypass(CPB)time,conventional ultrafiltration(CUF),hypothermia time,temperature the lowest degree,hematocrit(HCT)etc.and other data were collected.2ml peripheral venous blood was collected before and 24 hours after operation and then the levels of interleukin-6(IL-6),interleukin-10(IL-10),interleukin-11(IL-11),neutrophil gelatinase-associated liposome protein(NGAL)and insulin-like growth factor binding protein-7(IGFBP-7)were detected.AKI was diagnosed and grouped according to the international Kidney Disease: Improving Global Outcomes(KDIGO)criteria.The patients were divided into the non-AKI group(KDIGO criteria < 1)and the AKI group(KDIGO criteria ≥1).Binary Logistic regression analysis was used to determine the independent risk factors,and based on the results,selected indicators to establish a nomogram model for predicting the risk of postoperative AKI.The consistency and accuracy of the model were verified by the calibration curve and the receiver operating characteristic curve(ROC),and the clinical practicability of the model was determined by decision curve analysis(DCA).Results: A total of 85 patients met the inclusion criteria,and 49 patients developed AKI after surgery,with an incidence of 57.65%.Univariate analysis showed that preoperative factors: history of hypertension,history of diabetes,BMI,chronic kidney disease,use of angiotensin-converting enzyme inhibitors(ACEI)or angiotensin receptor blockers(ARB),cardiac function classification,pericardial effusion,preoperative Scr,preoperative anemia were statistically significant between the two groups(p<0.05).Intraoperative factors:duration of hypothermia,intraoperative use of vasoactive drugs,intraoperative use of furosemide and hormones,HCT,intraoperative use of sevoflurane and intraoperative use of electrical defibrillation were statistically significant between the two groups(p<0.05).Compared with the non-AKI group,the AKI group had significantly longer ICU stay time,postoperative mechanical ventilation time,and hospitalization time(p<0.05).However,there were no significant differences in inflammatory factors and new biomarkers(IL-6,IL-10,IL-11,NGAL,IGFBP-7)between the two groups(p>0.05).Multivariate binary Logistic regression analysis was used to analyze the factors with difference in univariate analysis.The statistical results showed that the history of hypertension,preoperative Scr and preoperative Lac were independent risk factors for postoperative AKI.Based on the results of binary Logistic regression analysis,the selected indicators were used to construct a nomogram model.After internal verification,the calibration curve showed that the average absolute error between the predicted risk of postoperative AKI and the actual risk of postoperative AKI was 0.017.ROC curve showed that the area under the curve of the model for predicting the risk of postoperative AKI was 0.902(95%CI 0.835-0.967),the sensitivity was 79.60%,and the specificity was 88.90%.DCA analysis showed that the model had good clinical practicability.Conclusion:The incidence of AKI after ATAAD is 57.65%.History of hypertension,preoperative Scr level and preoperative Lac level are independent risk factors for predicting AKI after ATAAD.The nomogram model based on history of hypertension,preoperative Scr level and preoperative Lac level can predict the occurrence of AKI after ATAAD to a certain extent.It has important clinical value in the prevention of AKI after ATAAD.