Postoperative Acute Kidney Injury Risk Calculator
Development and Validation of a Web-based Prediction Model for Acute Kidney Injury after surgery
https://kidney360.asnjournals.org/content/early/2020/12/29/KID.0004732020
Background
AKI after surgery is associated with high mortality and morbidity. The purpose of this study is to develop and validate a risk prediction tool for the occurrence of postoperative AKI requiring RRT (AKI-dialysis).
Methods
This retrospective cohort study had 2,299,502 surgical patients over 2015–2017 from the American College of Surgeons National Surgical Quality Improvement Program Database (ACS NSQIP). Eleven predictors were selected for the predictive model: age, history of congestive heart failure, diabetes, ascites, emergency surgery, hypertension requiring medication, preoperative serum creatinine, hematocrit, sodium, preoperative sepsis, and surgery type. The predictive model was trained using 2015–2016 data (n=1,487,724) and further tested using 2017 data (n=811,778). A risk model was developed using multivariable logistic regression.
Results
AKI-dialysis occurred in 0.3% (n=6853) of patients. The unadjusted 30-day postoperative mortality rate associated with AKI-dialysis was 37.5%. The AKI risk prediction model had high area under the receiver operating characteristic curve (AUC; training cohort: 0.89, test cohort: 0.90) for postoperative AKI-dialysis.
Conclusions
This model provides a clinically useful bedside predictive tool for postoperative AKI requiring dialysis.
Principal Investigator: Sang H. Woo, MD
Research team:
Jillian Zavodnick, MD (Division of Hospital Medicine)
Lily Ackermann, MD (Division of Hospital Medicine)
Omar Maarouf, MD (Division of Nephrology)
Jingjing Zhang, MD (Division of Nephrology)
Scott W. Cowan, MD (Department of Surgery)