Risk Factors Analysis And Prediction Model Construction For Acute Kidney Injury After Acute Ischemic Stroke

Objective: Acute kidney injury(AKI)is a common clinical disease in hospitalized patients and is closely related to poor prognosis in patients with acute ischemic stroke(AIS).Currently,there is no consensus on the risk factors for AKI in AIS patients,and there is a lack of reliable prediction tools in clinical practice.Therefore,this study aimed to analyze the risk factors for AKI in AIS patients and construct an individualized risk prediction model to identify and intervene high-risk patients early and improve patient prognosis.Methods: A total of 1633 AIS patients hospitalized in our center from January 2020 to June 2021 were retrospectively included in this study.Univariate logistic regression and multivariate logistic regression were used to explore the relationship between AKI and allcause in-hospital mortality in AIS patients,and the receiver operating characteristic(ROC)curve was used to explore the predictive value of AKI for in-hospital mortality in AIS patients.Furthermore,to explore the risk factors for AKI in AIS patients,AIS patients were divided into AKI and non-AKI groups according to whether they developed AKI,and the clinical data of the two groups of patients were analyzed.The potential risk factors for AKI were analyzed by inter-group comparison and univariate logistic regression analysis.Risk factors for AKI in AIS patients were screened using lasso regression and multivariate logistic regression,incorporated into a nomogram prediction model,and an online dynamic nomogram was generated.Internal validation was performed by bootstrapping technique.ROC curve,concordance index(C-Index),calibration curve and decision curve analysis(DCA)were used to evaluate the discriminative ability,calibration,and clinical utility of the model.Results: A total of 1633 AIS patients were included in this study,and the incidence of AKI was 14.57%(238/1633),with AKI stages 1,2,and 3 accounting for 77.73%(185/238),13.03%(31/238),and 9.24%(22/238),respectively.The all-cause in-hospital mortality rate of AIS patients in this study was 4.84%(79/1633),and the incidence of AKI in deceased patients was significantly higher than that in surviving patients(56.96% vs.12.42%,P < 0.001).The univariate logistic regression analysis results showed that AKI was a risk factor for in-hospital mortality in AIS patients(OR 9.333,95% CI 5.832~14.936,P < 0.001),and the area under the curve(AUC)of the ROC curve for the single AKI index in predicting in-hospital mortality in AIS patients was 0.723(95% CI 0.656~0.790,P < 0.001).After adjusting for common risk factors for poor prognosis in AIS such as age,gender,smoking,drinking,hypertension,diabetes,coronary heart disease,and atrial fibrillation,the occurrence of AKI was independently associated with increased in-hospital mortality in AIS patients(OR 9.842,95% CI 6.089~16.071,P < 0.001),and the AUC of the joint index predicting in-hospital mortality in AIS patients after adjusting for covariates was 0.789(95% CI 0.734~0.844,P < 0.001).These results indicated that AKI was an independent risk factor for poor prognosis in hospitalized AIS patients.Therefore,it is important to identify AKI early and intervene as soon as possible to improve the prognosis.Further exploration of its related risk factors is necessary.Clinical data comparison and univariate logistic regression analysis results suggested that factors such as red blood cell count,white blood cell count,hemoglobin,platelets,prothrombin time,fasting blood glucose,comorbid atrial fibrillation and chronic kidney disease,and the use of antibiotics and diuretics were related to the occurrence of AKI in AIS patients.Multivariate logistic regression analysis results showed that increased neutrophil count,prolonged prothrombin time,elevated lactate dehydrogenase,reduced estimated glomerular filtration rate,with history of transfusion,comorbid chronic kidney disease,use of antibiotics,dipyridamole,diuretics and β-block(all P < 0.05)were independent risk factors for AKI in AIS patients.The AUC of the prediction model was 0.797(95% CI 0.769~0.866,P < 0.01),and the C-Index of the internal validation group was 0.762(95% CI 0.761~0.762,P < 0.01).In addition,the calibration curve showed good consistency between the predicted values and the actual observed values,and the DCA indicated that the model had a high clinical net benefit and was clinically useful.Conclusions: 1.AKI was associated with an increased risk of in-hospital mortality in AIS patients and was an independent predictor of death in hospitalized AIS patients.2.Increased neutrophil count,prolonged prothrombin time,elevated lactate dehydrogenase,reduced estimated glomerular filtration rate,with history of transfusion,comorbid chronic kidney disease,use of antibiotics,dipyridamole,diuretics and β-block could increase the risk of AKI in AIS patients.3.The nomogram risk prediction model constructed based on Lasso-Logistic regression in this study had good predictive ability,and the online dynamic nomogram provided clinicians with a convenient,objective,and efficient assessment tool,which could help early recognition and prevention of AKI and improve patient prognosis.