评估和分析根治性切除术后结直肠癌患者的神经认知功能障碍:一项回顾性研究。

IF 1.8 4区 医学 Q3 GASTROENTEROLOGY & HEPATOLOGY
Yu Wang, Chao Wang, Han Guo, Su-Hang Wang, Fang-Fang Chen, Qiao-Xiang Chen, Kai Zhou
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引用次数: 0

摘要

背景:目的:分析腹腔镜结直肠癌术后神经认知功能延迟恢复(DNR)的风险因素,构建风险预测模型,为腹腔镜结直肠癌术后DNR的防治提供循证参考:回顾性分析2020年3月至2022年7月在我院接受腹腔镜手术和区域脑饱和氧合(rScO2)监测的227例结直肠癌患者的临床资料。将影响术后DNR的常见因素和潜在因素作为分析变量,逐步进行单变量分析和多因素分析,确定模型的预测因素,构建风险预测模型。用接收者操作特征曲线(ROC)评估模型的预测性能,用校准曲线评估模型与数据的拟合程度,并绘制了提名图。此外,还选取了2023年1月至2023年7月期间符合纳入和排除标准的30名患者,对预测模型进行外部验证:建模组术后DNR发生率为15.4%(35/227)。多变量分析显示,年龄、受教育年限、糖尿病状态和最低 rScO2 值是术后 DNR 的独立影响因素(均 P < 0.05)。因此,建立了腹腔镜结直肠癌术后 DNR 风险预测模型。模型的 ROC 曲线下面积为 0.757(95%CI:0.676-0.839,P <0.001),校正曲线的 Hosmer-Lemeshow 检验表明模型拟合良好(P = 0.516)。行外部验证的 C 指数为 0.617:与 rScO2 监测相关的 DNR 风险预测模型可用于腹腔镜结直肠癌手术患者的个体化评估,并为术后 DNR 的预防提供了临床依据。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Evaluation and analysis of neurocognitive dysfunction in patients with colorectal cancer after radical resection: A retrospective study.

Background: With the continuous progress of colorectal cancer treatment technology, the survival rate of patients has improved significantly, but the problem of postoperative neurocognitive dysfunction has gradually attracted attention.

Aim: To analyze the risk factors for delayed postoperative neurocognitive recovery (DNR) after laparoscopic colorectal cancer surgery and constructed a risk prediction model to provide an evidence-based reference for the prevention and treatment of DNR after laparoscopic colorectal cancer surgery.

Methods: The clinical data of 227 patients with colorectal cancer who underwent laparoscopic surgery and regional cerebral saturation oxygenation (rScO2) monitoring at our hospital from March 2020 to July 2022 were retrospectively analyzed. Common factors and potential factors affecting postoperative DNR were used as analysis variables, and univariate analysis and multifactor analysis were carried out step by step to determine the predictors of the model and construct a risk prediction model. The predictive performance of the model was assessed by the receiver operating characteristic (ROC) curve, the calibration curve was used to assess the fit of the model to the data, and a nomogram was drawn. In addition, 30 patients who met the inclusion and exclusion criteria from January 2023 to July 2023 were selected for external verification of the prediction model.

Results: The incidence of postoperative DNR in the modeling group was 15.4% (35/227). Multivariate analysis revealed that age, years of education, diabetes status, and the lowest rScO2 value were the independent influencing factors of postoperative DNR (all P < 0.05). Accordingly, a DNR risk prediction model was constructed after laparoscopic colorectal cancer surgery. The area under the ROC curve of the model was 0.757 (95%CI: 0.676-0.839, P < 0.001), and the Hosmer-Lemeshow test of the calibration curve suggested that the model was well fitted (P = 0.516). The C-index for external validation of the row was 0.617.

Conclusion: The DNR risk prediction model associated with rScO2 monitoring can be used for individualized assessment of patients undergoing laparoscopic colorectal cancer surgery and provides a clinical basis for the prevention of DNR after surgery.

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