Na Young Kim (1)+, Dongwoo Chae (2,3)+, Kyungsoo Park (2,3)*, and So Yeon Kim (1)*
(1) Department of Anesthesiology and Pain Medicine, Anesthesia and Pain Research Institute (2) Department of Pharmacology (3) Brain Korea 21 Plus Project for Medical Science, Yonsei University, Seoul, Korea, +Both authors contributed equally to this work, *Co-corresponding authors
Objectives:
The incidence of renal cell carcinoma is increasing in worldwide and surgical excision via partial nephrectomy or radical nephrectomy is considered as the first-line treatment for localized renal cell carcinoma. Minimally invasive laparoscopic or robotic nephrectomy has shown similar oncologic outcomes with lower complication compared to open nephrectomy even for a locally advanced renal cell carcinoma, thus minimally invasive nephrectomy is now considered as a valuable alternative to open nephrectomy. However, postoperative acute kidney injury was reported in 20–24% of patients undergone minimally invasive partial nephrectomy, although the minimally invasive nephrectomy is known to reduce acute kidney injury incidence compared with open nephrectomy. The data for incidence of acute kidney injury after minimally invasive radical nephrectomy is limited, but it may be higher compared to minimally invasive partial nephrectomy. Postoperative acute kidney injury is a major factor for chronic kidney disease and both acute kidney injury and chronic kidney disease are significantly associated with adverse postoperative outcome and death after nephrectomy. Thus, acute kidney injury is still a matter of concern even with the development of the minimally invasive technique, and identification of patients at risk before surgery is important.
Therefore, the objectives of this study were: (1) to develop a predictive model of postoperative acute kidney injury and identify its risk factors; and (2) to develop a scoring system for postoperative acute kidney injury that facilitates the use of the predictive model.
Methods:
A total of 1,025 patients who underwent laparoscopic or robot-assisted laparoscopic partial nephrectomy were identified from the electronic medical records of a single institution. The dataset was randomly split into training and test sets in a ratio of 8:2. A stepwise logistic regression was performed on the training dataset to select the most significant covariates. This process was repeated 100 times with different random seeds, whereupon the frequency of each covariate inclusion was calculated. Using only those covariates that were selected in more than 95% of the resampled datasets, a multivariate logistic regression model predicting the incidence of acute kidney injury within 48 postoperative hours was built. A scoring system was developed based on the final model using RShiny.
Results:
Parenchymal mass removed, warm ischemia time, female gender, history of hypertension, intraoperative bleeding, neutrophil-lymphocyte ratio at postoperative day 1, and platelet count at immediately after operation were identified as significant risk factors. The prediction value in validation was area under the curve (AUC) = 82.26%. A scoring system was developed with a weighted score in each parameter.
Conclusions:
A scoring system would help clinicians to identify the patients at risk before surgery and guide clinicians to reduce modifiable risk factors. Prophylactic management to reduce intraoperative bleeding and inflammation should be considered to reduce acute kidney injury after minimally invasive partial nephrectomy.
References:
[1] Schmid M, Abd-El-Barr AE, Gandaglia G, et al. Predictors of 30-day acute kidney injury following radical and partial nephrectomy for renal cell carcinoma. Urol Oncol 2014; 32: 1259-66
[2] Cho A, Lee JE, Kwon GY, et al. Post-operative acute kidney injury in patients with renal cell carcinoma is a potent risk factor for new-onset chronic kidney disease after radical nephrectomy. Nephrol Dial Transplant 2011; 26: 3496-501
Reference: PAGE 28 (2019) Abstr 8953 [www.page-meeting.org/?abstract=8953]
Poster: Drug/Disease Modelling - Other Topics