Hospital frailty risk score in predicting outcomes after simultaneous colon and liver resection for colorectal cancer liver metastasis in older adults: Evidence from the Nationwide Inpatient Sample 2015-2018

医院衰弱风险评分在预测老年结直肠癌肝转移患者同期行结肠和肝脏切除术后预后中的作用:来自2015-2018年全国住院样本的证据

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Abstract

OBJECTIVES: This study investigated the impact of clinical frailty on short-term outcomes of simultaneous colorectal cancer (CRC) and colorectal cancer liver metastasis (CRLM) resections. SETTING AND PARTICIPANTS: Data of older patients ≥ 60 years old undergoing simultaneous CRC/CRLM resections between 2005 and 2018 were identified in the United States (US) Nationwide Inpatient Sample (NIS) database. METHODS: Frailty was determined using the Hospital Frailty Risk Score (HFRS) according to the International Classification of Diseases Ninth and Tenth (ICD-9 and ICD-10) codes. Study outcomes included mortality, prolonged hospital stay (LOS), non-routine discharge, and complications. RESULTS: Data of 4514 patients were analyzed. Frailty was significantly associated with increased risks of in-hospital mortality (adjusted odds ratio [aOR] = 3.65, 95% confidence interval [CI]: 2.52, 5.28), non-routine discharge (aOR = 2.44, 95% CI: 2.08, 2.87), prolonged LOS (aOR = 3.07, 95% CI: 2.60, 3.61), overall complications (aOR = 3.47, 95% CI: 3.03, 3.97), sepsis (aOR = 13.73, 95% CI: 9.76, 19.31), respiratory failure (aOR = 4.99, 95% CI: 3.80, 6.57), acute kidney injury (AKI) (aOR = 6.42, 95% CI: 4.83, 8.52), and acute liver failure (aOR = 2.10, 95% CI: 1.38, 3.21), as well as 32.69 thousand USD higher total hospital costs (95% CI: 28.41, 36.97) than no frailty. Incorporating frailty with traditional demographic and clinical risk factors improved in-hospital mortality prediction (area under ROC curve [AUC]: 0.765 to 0.799). CONCLUSIONS: In older patients aged ≥ 60 years undergoing simultaneous CRC and CRLM resection, HFRS-defined frailty is a significant predictor of adverse in-hospital outcomes. The addition of HFRS-defined frailty to demographic and clinical variables in predictive models improved the AUC for mortality prediction. Incorporating frailty assessment into the preoperative risk stratification and decision-making process for these patients may support surgeons in delivering more personalized and effective care.

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