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Analysis of influencing factors of postoperative infection in patients with colon cancer and construction of nomogram model / 中国医师进修杂志
Article em Zh | WPRIM | ID: wpr-1023042
Biblioteca responsável: WPRO
ABSTRACT
Objective:To analyze the risk factors of postoperative infection in patients with colon cancer, and construct a nomogram model.Methods:The clinical data of 220 patients with colon cancer in Anhui Cancer Hospital from May 2019 to June 2022 were retrospectively analyzed. Among them, 55 patients developed postoperative infection (infection group), and 165 patients did not develop postoperative infection (non-infection group). The receiver operating characteristic (ROC) curve was used to analyze the efficacy of each index in predicting postoperative infection in patients with colon cancer. Multivariate Logistic regression analysis was used to analyze the independent risk factors of postoperative infection in patients with colon cancer. R language 3.5.2 software was used to construct a nomogram model for predicting postoperative infection in patients with colon cancer, and it was verified and evaluated.Results:There were no significant differences in gender composition, body mass index, tumor stage, intraoperative blood transfusion, hypertension, smoking history, alcohol consumption history, tumor diameter and hemoglobin between the two groups ( P>0.05); the age, diabetes mellitus ratio, operation time and exhaust time in the infection group were significantly higher than those in the non-infection group: (49.60 ± 4.40) years old vs. (47.20 ± 4.12) years old, 63.64% (35/55) vs. 30.30% (50/165), (197.80 ± 12.55) min vs. (192.23 ± 12.05) min and (3.42 ± 1.18) d vs. (2.60 ± 0.80) d, the albumin was significantly lower than that in the non-infected group: (28.29 ± 3.02) g/L vs. (32.80 ± 3.21) g/L, and there were statistical differences ( P<0.01). ROC curve analysis result showed that the area under the curve of age, operation time, exhaust time and albumin for predicting postoperative infection in patients with colon cancer were 0.672, 0.610, 0.706 and 0.846, and the optimal cut-off values were 49 years old, 184 min, 3 d and 30 g/L, respectively. Multivariate Logistic regression analysis result showed that age (>49 years old), diabetes mellitus, operation time (>184 min), exhaust time (>3 d) and albumin (≤30 g/L) were independent risk factors of postoperative infection in patients with colon cancer ( OR = 2.131, 1.758, 1.449, 1.841 and 2.325; 95% CI 1.269 to 2.696, 1.354 to 3.059, 1.201 to 1.965, 1.018 to 2.365 and 1.582 to 3.051; P<0.01). A nomogram model was constructed with age, diabetes mellitus, operation time, exhaust time, and albumin as predictors for predicting postoperative infection in patients with colon cancer. The correction curve of the nomogram model for predicting postoperative infection in patients with colon cancer was close to the ideal curve (C-index = 0.764, 95% CI 0.657 to 0.834); decision curve analysis result showed that the nomogram model provided clinical net benefit when the risk threshold was > 0.07; and the clinical net benefit of the model was higher than that of age, diabetes mellitus, operation time, exhaust time and albumin. Conclusions:The age (>49 years old), diabetes mellitus, operation time (>184 min), exhaust time (>3 d) and albumin (≤30 g/L) are the independent risk factors of postoperative infection in patients with colon cancer, and the nomogram model based on the above variables could predict postoperative infection.
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Texto completo: 1 Base de dados: WPRIM Idioma: Zh Ano de publicação: 2024 Tipo de documento: Article
Texto completo: 1 Base de dados: WPRIM Idioma: Zh Ano de publicação: 2024 Tipo de documento: Article