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Abstract：
BACKGROUND: Transfer to the ICU is common following non-cardiac surgeries, including radical colorectal cancer (CRC) resection. Understanding the judicious utilization of costly ICU medical resources and supportive postoperative care is crucial. This study aimed to construct and validate a nomogram for predicting the need for mandatory ICU admission immediately following radical CRC resection.
METHODS: Retrospective analysis was conducted on data from 1003 patients who underwent radical or palliative surgery for CRC at Ningxia Medical University General Hospital from August 2020 to April 2022. Patients were randomly assigned to training and validation cohorts in a 7:3 ratio. Independent predictors were identified using the least absolute shrinkage and selection operator (LASSO) and multivariate logistic regression in the training cohort to construct the nomogram. An online prediction tool was developed for clinical use. The nomogram\'s calibration and discriminative performance were assessed in both cohorts, and its clinical utility was evaluated through decision curve analysis (DCA).
RESULTS: The final predictive model comprised age (P = 0.003, odds ratio [OR] 3.623, 95% confidence interval [CI] 1.535-8.551); nutritional risk screening 2002 (NRS2002) (P = 0.000, OR 6.129, 95% CI 2.920-12.863); serum albumin (ALB) (P = 0.013, OR 0.921, 95% CI 0.863-0.982); atrial fibrillation (P = 0.000, OR 20.017, 95% CI 4.191-95.609); chronic obstructive pulmonary disease (COPD) (P = 0.009, OR 8.151, 95% CI 1.674-39.676); forced expiratory volume in 1 s / Forced vital capacity (FEV1/FVC) (P = 0.040, OR 0.966, 95% CI 0.935-0.998); and surgical method (P = 0.024, OR 0.425, 95% CI 0.202-0.891). The area under the curve was 0.865, and the consistency index was 0.367. The Hosmer-Lemeshow test indicated excellent model fit (P = 0.367). The calibration curve closely approximated the ideal diagonal line. DCA showed a significant net benefit of the predictive model for postoperative ICU admission.
CONCLUSIONS: Predictors of ICU admission following radical CRC resection include age, preoperative serum albumin level, nutritional risk screening, atrial fibrillation, COPD, FEV1/FVC, and surgical route. The predictive nomogram and online tool support clinical decision-making for postoperative ICU admission in patients undergoing radical CRC surgery.
BACKGROUND: Despite the retrospective nature of this study, we have proactively registered it with the Chinese Clinical Trial Registry. The registration number is ChiCTR2200062210, and the date of registration is 29/07/2022.
METHODS: Retrospective analysis was conducted on data from 1003 patients who underwent radical or palliative surgery for CRC at Ningxia Medical University General Hospital from August 2020 to April 2022. Patients were randomly assigned to training and validation cohorts in a 7:3 ratio. Independent predictors were identified using the least absolute shrinkage and selection operator (LASSO) and multivariate logistic regression in the training cohort to construct the nomogram. An online prediction tool was developed for clinical use. The nomogram\'s calibration and discriminative performance were assessed in both cohorts, and its clinical utility was evaluated through decision curve analysis (DCA).
RESULTS: The final predictive model comprised age (P = 0.003, odds ratio [OR] 3.623, 95% confidence interval [CI] 1.535-8.551); nutritional risk screening 2002 (NRS2002) (P = 0.000, OR 6.129, 95% CI 2.920-12.863); serum albumin (ALB) (P = 0.013, OR 0.921, 95% CI 0.863-0.982); atrial fibrillation (P = 0.000, OR 20.017, 95% CI 4.191-95.609); chronic obstructive pulmonary disease (COPD) (P = 0.009, OR 8.151, 95% CI 1.674-39.676); forced expiratory volume in 1 s / Forced vital capacity (FEV1/FVC) (P = 0.040, OR 0.966, 95% CI 0.935-0.998); and surgical method (P = 0.024, OR 0.425, 95% CI 0.202-0.891). The area under the curve was 0.865, and the consistency index was 0.367. The Hosmer-Lemeshow test indicated excellent model fit (P = 0.367). The calibration curve closely approximated the ideal diagonal line. DCA showed a significant net benefit of the predictive model for postoperative ICU admission.
CONCLUSIONS: Predictors of ICU admission following radical CRC resection include age, preoperative serum albumin level, nutritional risk screening, atrial fibrillation, COPD, FEV1/FVC, and surgical route. The predictive nomogram and online tool support clinical decision-making for postoperative ICU admission in patients undergoing radical CRC surgery.
BACKGROUND: Despite the retrospective nature of this study, we have proactively registered it with the Chinese Clinical Trial Registry. The registration number is ChiCTR2200062210, and the date of registration is 29/07/2022.
摘要：
背景：非心脏手术后转移到ICU很常见，包括根治性结直肠癌(CRC)切除术。了解合理利用昂贵的ICU医疗资源和术后支持性护理至关重要。这项研究旨在构建和验证列线图，以预测根治性CRC切除术后立即强制ICU入院的需求。
方法：回顾性分析宁夏医科大学总医院2020年8月至2022年4月因CRC行根治性或姑息性手术的1003例患者资料。患者以7:3的比例随机分配到训练和验证队列。在训练队列中使用最小绝对收缩和选择算子（LASSO）和多变量逻辑回归确定独立预测因子，以构建列线图。开发了一种在线预测工具供临床使用。在两个队列中评估了列线图的校准和判别性能，并通过决策曲线分析(DCA)评价其临床效用。
结果：最终的预测模型包括年龄（P=0.003，比值比[OR]3.623，95％置信区间[CI]1.535-8.551）；2002年营养风险筛查（NRS2002）（P=0.000，OR6.129，95％CI2.920-12.863）；血清白蛋白（ALB），OR0.0.0.995％CI=0.1.6P曲线下面积为0.865,一致性指数为0.367。Hosmer-Lemeshow测试表明模型拟合良好(P=0.367)。校准曲线非常接近理想对角线。DCA显示了预测模型对术后ICU入院的显着净益处。
结论：CRC根治性切除术后ICU入院的预测因素包括年龄，术前血清白蛋白水平，营养风险筛查，心房颤动,COPD,FEV1/FVC,和手术路线。预测列线图和在线工具支持接受根治性CRC手术的患者术后ICU入院的临床决策。
背景：尽管这项研究具有回顾性性质，我们已经在中国临床试验注册中心进行了主动注册.注册号为ChiCTR2200062210，注册日期为29/07/2022。
方法：回顾性分析宁夏医科大学总医院2020年8月至2022年4月因CRC行根治性或姑息性手术的1003例患者资料。患者以7:3的比例随机分配到训练和验证队列。在训练队列中使用最小绝对收缩和选择算子（LASSO）和多变量逻辑回归确定独立预测因子，以构建列线图。开发了一种在线预测工具供临床使用。在两个队列中评估了列线图的校准和判别性能，并通过决策曲线分析(DCA)评价其临床效用。
结果：最终的预测模型包括年龄（P=0.003，比值比[OR]3.623，95％置信区间[CI]1.535-8.551）；2002年营养风险筛查（NRS2002）（P=0.000，OR6.129，95％CI2.920-12.863）；血清白蛋白（ALB），OR0.0.0.995％CI=0.1.6P曲线下面积为0.865,一致性指数为0.367。Hosmer-Lemeshow测试表明模型拟合良好(P=0.367)。校准曲线非常接近理想对角线。DCA显示了预测模型对术后ICU入院的显着净益处。
结论：CRC根治性切除术后ICU入院的预测因素包括年龄，术前血清白蛋白水平，营养风险筛查，心房颤动,COPD,FEV1/FVC,和手术路线。预测列线图和在线工具支持接受根治性CRC手术的患者术后ICU入院的临床决策。
背景：尽管这项研究具有回顾性性质，我们已经在中国临床试验注册中心进行了主动注册.注册号为ChiCTR2200062210，注册日期为29/07/2022。
