Back

Acute Kidney Injury and Perioperative complications based on modality of nephrectomy for the treatment of kidney cancer

Patel, M. N.; Shah, D. M.; Patel, H. G.; Jaimes, E. A.

2024-09-26 nephrology
10.1101/2024.09.24.24314317 medRxiv
Show abstract

BackgroundNephrectomy, either partial or radical, is a key treatment for kidney cancer. The surgical approach--open, laparoscopic, or robot-assisted--can influence perioperative outcomes. This study evaluates acute kidney injury (AKI) and perioperative complications across these modalities. MethodsWe conducted a retrospective analysis using the National Inpatient Sample (NIS) of 2020-2021 to examine 12,676 kidney cancer patients who underwent nephrectomy. Patients were stratified by surgical approach: open, laparoscopic, and robot-assisted. Primary outcomes included AKI incidence, length of stay, and intra- and post-operative complications. Multivariable regression models adjusted for confounding variables, including age, sex, race, Charlson Comorbidity Index (CCI), hospital region, and teaching status. ResultsPatients undergoing open nephrectomy had the highest AKI rates, particularly for radical nephrectomy (22.13% vs. 16.52% for robotic, p < 0.001). Similarly, patients treated with open surgery had longer hospital stays and higher rates of complications, including pulmonary (7.71% vs. 4.17%, p < 0.001) and vascular (12.11% vs. 4.01%, p < 0.001) in radical nephrectomy. Multivariate analysis confirmed the increased risk of AKI and complications in open nephrectomy, with robotic-assisted surgery demonstrating the best perioperative outcomes. ConclusionOpen nephrectomy, whether partial or radical, is associated with higher AKI rates and perioperative complications compared to laparoscopic and robot-assisted surgeries. Robot-assisted nephrectomy, with its lower complication rates and shorter hospital stays, may be the preferred approach when feasible. Further efforts to expand access to minimally invasive techniques could improve outcomes for kidney cancer patients.

Matching journals

The top 4 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.