The influence of frailty on perioperative outcomes in patients undergoing surgical resection of liver metastases: a nationwide readmissions database study

Authors Shane Shahrestani, Madeleine Silverstein, Tania Nasrollahi, Marissa Maas, Chaiss Ugarte, Sujit Kulkarni, Heinz-Josef Lenz, Yuri Genyk, Tania Nasrollahi.


Background Liver metastases arise frequently from primary colorectal, pancreatic, and breast cancers. Research has highlighted the patient’s frailty status as an important predictor of outcomes, but the literature evaluating the role of frailty in patients with secondary metastatic disease of the liver remains limited. Using predictive analytics, we evaluated the role of frailty in patients who underwent hepatectomy for liver metastases.

Methods We used the Nationwide Readmissions Database from 2016-2017 to identify patients who underwent resection of a secondary malignant neoplasm of the liver. Patient frailty was evaluated using the Johns Hopkins Adjusted Clinical Groups (JHACG) frailty-defining diagnosis indicator. Propensity score matching was performed and Mann-Whitney U testing was used to analyze complication rates. Receiver operating characteristic (ROC) curves were created following creation of logistic regression models for predicting discharge disposition.

Results Frail patients reported significantly higher rates of nonroutine discharges, longer inpatient stays, greater costs, higher rates of acute infection, posthemorrhagic anemia, urinary tract infection (UTI), deep vein thrombosis (DVT), wound dehiscence and readmission, and greater mortality (P<0.05). Predictive models for patient discharge disposition, DVT and UTI demonstrated that the use of frailty status and age improved the area under the ROC curves significantly compared to models using age alone.

Conclusions Frailty was found to be significantly correlated with higher rates of medical complications during inpatient stay following hepatectomy in patients with liver metastasis. The inclusion of patient frailty status in predictive models improved their predictive capacity compared to those using age alone.

Keywords Liver, metastasis, frailty, oncology, hepatobiliary

Ann Gastroenterol 2023; 36 (3): 333-339

Original Articles