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| A model combined with sarcopenia to predict the risk of intra-abdominal infection after colorectal cancer surgery |
| YE Guoqing1.XU Jingxuan2, ZENG Yunpeng2, ZHU Ce2, WANG Xiang2, SUN Jing2, YANG Xinxin2,SHEN Xian2. |
| 1.Department of Surgery, Pingyang County Hospital of Traditional Chinese Medicine, Wenzhou 325000, China; 2.Department of Gastrointestinal Surgery, the Second Affiliated Hospital of Wenzhou Medical University, Wenzhou 325027, China |
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| Cite this article: |
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YE Guoqing,XU Jingxuan,ZENG Yunpeng, et al. A model combined with sarcopenia to predict the risk of intra-abdominal infection after colorectal cancer surgery[J]. JOURNAL OF WEZHOU MEDICAL UNIVERSITY, 2020, 50(12): 984-989.
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Abstract Objective: To determine the relationship between postoperative intraperitoneal infection and sarcopenia in colorectal cancer and to establish a prediction model with high accuracy to discriminate patients with high risk of intraperitoneal infection. Methods: A prospective study was conducted of 383 colorectal cancer patients undergoing radical resection. The lumbar skeletal muscle index, preoperative grip strength and walking speed were preoperatively measured for sarcopenia diagnosis. Univariate and multivariate analyses were used to identify the potential factors for intraperitoneal infection. A prediction model consisting of independent risk factors
was constructed to quantify the individual risk of intraperitoneal infection after colorectal resection. Results: Out of 383 patients, 93 were diagnosed with sarcopenia in the present study, andintraperitoneal infectionoccurred in 44 patients. Multivariate logistic analysis showed that sarcopenia, tumor size and patient’s age were independent factors for intraperitoneal infection predication. The combined prediction model can accurately quantify the individual risk of intraperitoneal infection after colorectal cancer surgery (C-index 0.710). Conclusion: Sarcopenia is an independent risk factor for intraperitoneal infection after colorectal cancer surgery. Our prediction model is a simple and practical tool which can accurately quantify the individual risk of intraperitoneal infection and identify patients with high risk.
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Received: 12 March 2020
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