Is a body composition analysis using bioelectrical impedance useful for predicting postoperative complications in elderly colorectal cancer patients?
Year: 2025
Type: article
Abstract: Introduction: Elderly patients are generally vulnerable to postoperative complications due to decreased organ function, lessened immunity, and several comorbidities. Body composition analysis with BIA has been reported to be useful in predicting postoperative complications. We conducted the present retrospective study to determine whether preoperative sarcopenia and other body‐composition parameters revealed by a bioelectrical impedance analysis are associated with the occurrence of postoperative complications in elderly patients with colorectal cancer. Methods: The study subjects were 60 elderly individuals aged ≥ 65 years who underwent curative surgery for colorectal cancer at our hospital. We divided the patients into two groups based on the presence (n＝16) or absence (n＝44) of postoperative complications that were grade II or higher in the Clavien‐Dindo classification. We compared the two groups' preoperative sarcopenia, body composition analysis results by BIA, surgical factors (surgical approach, operation time, and blood loss) and blood data. Results: The TBW/FFM ratio and phase angle were significantly higher in the group with complications, and the operation time was also significantly longer (all p < 0.05). In the logistic regression analysis with the presence or absence of complications as the dependent variable, sex (odds ratio [OR] 3.6, 95％ confidence interval [CI]: 1.00–12.90) and phase angle (OR 2.43, 95％CI: 1.06–5.54) were identified as significant factors in the univariate analysis (p < 0.05), but the multivariate analysis revealed no significant factors. Conclusions: Our study did not identify preoperative sarcopenia as a predictor of postoperative complications. However, phase angle might be a possible predictor of postoperative complications.
Authors: Yoshihisa Yaguchi, Kohei Sato, Mami Yoshida, Yuichi Nishihara, Hirofumi Sugita, Kenichiro Omoto, Shunsuke Takeuchi, Toshikazu Shioiri, Takafumi Suzuki
Institution: Mthatha General Hospital
Language: English
Subfield: Physiology
Field: Medicine
Domain: Health Sciences
Open Access status: diamond
OpenAlex ID: W7081980809