Introduction Frailty is recognized as an important predictor of adverse outcomes in older surgical patients. However, evidence regarding preoperative frailty among older patients with colorectal cancer (CRC) admitted to the ICU after surgery remains limited. This study aimed to investigate the prevalence, associated factors, and impact of preoperative frailty risk on in-hospital outcomes in this high-risk population. Materials and methods This single-center retrospective cohort study included 308 older CRC patients who underwent radical surgery and were admitted to the ICU postoperatively between June 2023 and March 2026. Preoperative frailty risk was assessed using the five-item modified Frailty Index (mFI-5). Multivariable logistic regression was used to identify factors associated with frailty risk and evaluate the association between preoperative frailty risk and postoperative complications. Generalized linear models were applied to assess the associations of frailty risk with total hospital stay, ICU stay, and hospitalization costs. Results The prevalence of preoperative frailty risk was 55.52% in this study. Higher albumin levels were a protective factor, whereas higher blood glucose levels, elevated NLR, BMI ≥ 26.9 kg/m², polypharmacy, pain, and high fall risk were significantly associated with increased frailty risk. After adjustment for confounders, frailty risk remained an independent predictor of overall complications and severe complications and was significantly associated with prolonged total hospital stay, longer ICU stay, and increased hospitalization costs. Discussion Preoperative frailty risk is highly prevalent among older CRC patients admitted to the ICU after surgery and is independently associated with adverse in-hospital outcomes. These findings highlight the importance of incorporating frailty assessment into perioperative management. The mFI-5 is a simple and feasible tool for preoperative risk stratification in this high-risk population and may help guide prehabilitation strategies to ultimately optimize postoperative recovery.
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Wang et al. (2026) studied this question.
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