Geriatric Nutritional Risk Index Predicts Postoperative Complications in Elderly Patients Undergoing Robot‐Assisted Radical Cystectomy
Year: 2025
Type: article
Study design: Observational Study
Abstract: OBJECTIVE: Malnutrition is a common condition among elderly cancer patients. The Geriatric Nutritional Risk Index (GNRI) is a simple screening tool used to predict the risk of postoperative complications in patients undergoing radical cystectomy. This study aimed to evaluate the effectiveness of preoperative GNRI as a marker for predicting 90-day postoperative complications in elderly patients undergoing robot-assisted radical cystectomy (RARC). METHODS: We retrospectively evaluated 385 patients who underwent RARC at four affiliated institutes of Tokushima University between 2014 and 2023. Patient background characteristics, pathological findings, and 90-day postoperative complications were analyzed. Preoperative GNRI was calculated using serum albumin and body mass index, with an abnormal nutritional status defined as GNRI < 92. RESULTS: A total of 166 patients aged ≥ 75 years who underwent RARC were included in the study. Among these, 26 patients (15.7%) had an abnormal GNRI. Eighty-four patients (50.6%) experienced complications within 90 days postoperatively, including 29 patients (17.5%) with major complications (Clavien-Dindo classification ≥ 3). The 90-day postoperative mortality rate was 3.0% (five patients). Patients with an abnormal GNRI had a significantly higher rate of 90-day postoperative complications (p < 0.001). Multivariable logistic regression analysis identified abnormal GNRI as a significant predictor of 90-day postoperative complications (odds ratio: 9.963; 95% confidence interval: 2.125-46.718; p = 0.004). CONCLUSIONS: Poor nutritional status is associated with a higher rate of 90-day postoperative complications in elderly patients undergoing RARC. Preoperative GNRI may be a useful tool for assessing the risk of complications in this patient population.
Source: International Journal of Urology
DOI: 10.1111/iju.70070
Language: English
Subfield: Physiology (medical)
Field: Medicine
Domain: Health Sciences
Open Access status: bronze
OpenAlex ID: W4409750797