构建老年结直肠癌患者腹腔镜根治术后全身麻醉（全麻）苏醒延迟的风险因素模型，并验证其应用效果。

回顾性选取2021年3月至2024年3月宝鸡市中心医院收治的257例老年结直肠癌患者，均经腹腔镜根治术治疗，按照7∶3比例分别纳入训练组（n=180）、验证组（n=77）。评估其全麻苏醒情况，并比较训练组（n=180）全麻苏醒延迟发生、正常苏醒患者临床资料差异。使用Logistic多因素回归分析，归纳老年结直肠癌患者腹腔镜根治术后全麻苏醒延迟的风险因素，分别进行单变量与多变量的筛选，以识别关键预测因子，并将风险因素纳入Nomogram预测模型，进而建立风险预测模型。利用受试者工作特征曲线来衡量模型的预测准确性，使用Bootstarp法和临床决策曲线分析验证模型校准度。

257例术后出现苏醒延迟患者有105例，发生率为40.87%，其中训练组中术后出现苏醒延迟的为苏醒延迟组（n=72），其余108例为正常苏醒组。苏醒延迟组、正常苏醒组美国麻醉医师协会（ASA）分级、术前合并呼吸功能障碍、麻醉时间、丙泊酚用量、舒芬太尼用量、术中输液量、术中低体温、术后低钾血症方面比较，差异有统计学意义（P<0.05）。Logistic多因素分析示，ASA分级、术前合并呼吸功能障碍、麻醉时间、丙泊酚用量、舒芬太尼用量、术中输液量、术中低体温、术后低钾血症，均为影响老年结直肠癌患者腹腔镜根治术后全麻苏醒延迟的独立危险因素（P<0.05）。基于风险因素构建的Nomogram模型应用于训练组、验证组的曲线下面积分别为0.860、0.823，应用于验证组的灵敏度、特异性分别为82.53%、83.46%。

老年结直肠癌患者腹腔镜根治术后全麻苏醒延迟发生的风险较高，且与ASA分级、术前合并呼吸功能障碍、麻醉时间、丙泊酚用量、舒芬太尼用量、术中输液量、术中低体温、术后低钾血症等因素有关，基于上述因素建立的预测模型能够为老年结直肠癌患者腹腔镜根治术后全麻苏醒延迟减少风险评估提供可靠参考。

To establishment a risk prediction model for delayed recovery from general anesthesia in elderly patients with colorectal cancer after laparoscopic radical surgery and verify its application effect.

A total of 257 elderly patients with colorectal cancer admitted to Baoji Central Hospital from March 2021 to March 2024 were enrolled retrospectively, all of whom were treated with laparoscopic radical surgery. They were included in the training group (n=180) and the verification group (n=77) according to a ratio of 7∶3. The recovery from general anesthesia of patients were evaluated, and the clinical data of patients with delayed and normal recovery from general anesthesia in the training group (n=180) were compared. Multivariate Logistic regression analysis was used to summarize the risk factors for delayed recovery from general anesthesia in elderly patients with colorectal cancer after laparoscopic radical surgery. Univariate and multivariate screening were performed to identify key predictors, and the risk factors were incorporated into the Nomogram prediction model to establish a risk prediction model. The predictive accuracy of the model was measured using receiver operating characteristic (ROC) curve, and the calibration of the model was verified using Bootstarp and Clinical decision curve analysis.

Among 257 patients, 105 had delayed recovery after operation, with an incidence of 40.87%. In the training group, those who experienced delayed recovery after surgery were classified as the delayed recovery group (n=72), and the other 108 cases were in the normal recovery group. There were statistically significant differences between the delayed recovery group and the normal recovery group in American Society of Anesthesiologists (ASA) classification, preoperative respiratory dysfunction, anesthesia time, propofol dosage, sufentanil dosage, intraoperative infusion volume, intraoperative hypothermia and postoperative hypokalemia (P<0.05). Logistic multivariate analysis showed that ASA classification, preoperative respiratory dysfunction, anesthesia time, propofol dosage, sufentanil dosage, intraoperative infusion volume, intraoperative hypothermia, and postoperative hypokalemia were all independent risk factors for delayed recovery from general anesthesia after laparoscopic radical surgery in elderly patients with colorectal cancer (P<0.05). The area under the curve of the Nomogram model was 0.860 in the training group and 0.823 in the verification group, the sensitivity and specificity applied to the verification group were 82.53% and 83.46%, respectively.

The risk of delayed recovery from general anesthesia after laparoscopic radical surgery in elderly patients with colorectal cancer is higher, and it is related to ASA classification, preoperative respiratory dysfunction, anesthesia time, propofol dosage, sufentanil dosage, intraoperative infusion volume, intraoperative hypothermia, postoperative hypokalemia and other factors. The prediction model based on the above factors can provide a reliable reference for the risk assessment of delayed recovery from general anesthesia in elderly patients with colorectal cancer after laparoscopic radical surgery.