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Standardized Colon Ascendens Stent Peritonitis in Rats - a Simple, Feasible Animal Model to Induce Septic Acute Kidney Injury
Published on: February 15, 2022
DEVELOPMENT AND VALIDATION OF A PREDICTION MODEL FOR SEPTIC SHOCK-ASSOCIATED ACUTE KIDNEY INJURY: A MULTICENTER STUDY
Zhizhao Jiang1, Sibai Hong1, Yongqiang Chen1
1Department of Intensive Care Unit, The Second Affiliated Hospital of Fujian Medical University, Quanzhou, People's Republic of China.
Abstract:
Background: Septic shock-associated acute kidney injury (SS-AKI) is a severe complication with high mortality. This study aimed to investigate the risk factors associated with AKI in patients with septic shock and establish a nomogram to predict its occurrence. Methods: Patients with septic shock were categorized based on the development of AKI. A binary logistic regression was used to identify significant risk factors, which were then incorporated into a nomogram. The performance of the nomogram was evaluated using receiver operating characteristic curve analysis, calibration curve, and decision curve analysis. A validation set was used to assess the model's generalizability. Results: Of the 507 septic shock patients enrolled in this study, 174 (34.3%) developed AKI. The dataset was randomly partitioned into a training set (n = 355) and a validation set (n = 152) at a ratio of 7:3. The predictive factors incorporated into the nomogram included chronic kidney disease, diuretic administration, deresuscitation during vasopressor administration, mechanical ventilation, source control failure, restrictive fluid resuscitation, and Sequential Organ Failure Assessment scores. The developed nomogram demonstrated excellent performance in predicting the risk of AKI in patients with septic shock. The model achieved an area under the receiver operating characteristic curve of 0.788 (95% confidence interval, 0.737-0.839) in the training set and 0.770 (95% confidence interval, 0.693-0.846) in the validation set, indicating strong discriminatory ability. The calibration curve analysis, using the Hosmer-Lemeshow test, indicated good agreement between the predicted and observed probabilities of AKI in both the training set ( P = 0.468) and the validation set ( P = 0.396). The decision curve analysis further indicated that the nomogram demonstrated substantial clinical utility in both the training set (0.09-0.87) and the validation set (0.11-0.64). Conclusions: The nomogram serves as an invaluable tool for clinicians to assess the risk of AKI in patients experiencing septic shock and facilitates timely intervention.
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