Abstract：
BACKGROUND: Small bowel obstruction after extubation is among the most serious complications of radical esophageal cancer and jejunostomy resection. This study aimed to explore the risk factors and treatment methods for small bowel obstruction after extubation and construct a predictive model to guide its clinical management.
METHODS: Clinical data for 514 patients who underwent esophagectomy with jejunostomy for esophageal cancer were collected. A nomogram was constructed using the independent risk factors for small bowel obstruction after extubation determined on multivariable logistic regression analysis, and a subgroup analysis was performed of the treatment methods for the 61 patients with small bowel obstruction after extubation.
RESULTS: The nomogram incorporated the independent risk factors for small bowel obstruction after extubation (gastrointestinal function recovery [P < .001], postoperative albumin reduction ratio [P = .009], and serious postoperative complications [P < .001]) in the multivariable logistic regression analysis. The final model had an area under the curve of 0.829 (95% confidence interval, 0.775-0.883). The calibration plots demonstrated high concordance between the predicted and actual probabilities. The model demonstrated excellent discriminatory power for internal and time validation, with adjusted C-statistics of 0.821 and 0.810 (95% confidence interval, 0.686-0.933), respectively. In the subgroup analysis, an abnormal anion gap (P = .016) and low serum albumin level (P = .005) were associated with recurrent small bowel obstruction. The model\'s area under the curve was 0.815 (95% confidence interval, 0.683-0.948). The probability of recurrence among patients with small bowel obstruction after extubation was 78.3% when the 2 risk factors were present.
CONCLUSIONS: The clinical nomogram based on small bowel obstruction after extubation predictors recommends aggressive surgical intervention for patients with small bowel obstruction after extubation and an abnormal anion gap and low serum albumin level at admission.
METHODS: Clinical data for 514 patients who underwent esophagectomy with jejunostomy for esophageal cancer were collected. A nomogram was constructed using the independent risk factors for small bowel obstruction after extubation determined on multivariable logistic regression analysis, and a subgroup analysis was performed of the treatment methods for the 61 patients with small bowel obstruction after extubation.
RESULTS: The nomogram incorporated the independent risk factors for small bowel obstruction after extubation (gastrointestinal function recovery [P < .001], postoperative albumin reduction ratio [P = .009], and serious postoperative complications [P < .001]) in the multivariable logistic regression analysis. The final model had an area under the curve of 0.829 (95% confidence interval, 0.775-0.883). The calibration plots demonstrated high concordance between the predicted and actual probabilities. The model demonstrated excellent discriminatory power for internal and time validation, with adjusted C-statistics of 0.821 and 0.810 (95% confidence interval, 0.686-0.933), respectively. In the subgroup analysis, an abnormal anion gap (P = .016) and low serum albumin level (P = .005) were associated with recurrent small bowel obstruction. The model\'s area under the curve was 0.815 (95% confidence interval, 0.683-0.948). The probability of recurrence among patients with small bowel obstruction after extubation was 78.3% when the 2 risk factors were present.
CONCLUSIONS: The clinical nomogram based on small bowel obstruction after extubation predictors recommends aggressive surgical intervention for patients with small bowel obstruction after extubation and an abnormal anion gap and low serum albumin level at admission.
摘要：
背景：拔管后小肠梗阻是食管癌根治术和空肠造口切除最严重的并发症之一。本研究旨在探讨拔管后小肠梗阻的危险因素及治疗方法,并构建预测模型指导其临床管理。
方法：收集514例食管癌患者的临床资料。使用多变量logistic回归分析确定的拔管后小肠梗阻的独立危险因素构建列线图。对61例小肠梗阻患者拔管后的治疗方法进行亚组分析。
结果：列线图包含了拔管后小肠梗阻的独立危险因素（胃肠功能恢复[P<.001]，术后白蛋白减少率[P=.009]，和严重的术后并发症[P<.001]）在多变量逻辑回归分析中。最终模型的曲线下面积为0.829(95%置信区间，0.775-0.883）。校准图显示了预测概率和实际概率之间的高度一致性。该模型对内部和时间验证表现出了极好的辨别能力，调整后的C统计量为0.821和0.810(95%置信区间，0.686-0.933),分别。在亚组分析中，阴离子间隙异常(P=.016)和低血清白蛋白水平(P=.005)与小肠梗阻复发相关.模型曲线下面积为0.815(95%置信区间，0.683-0.948)。当存在2个危险因素时,小肠梗阻患者拔管后复发的概率为78.3%。
结论：基于拔管后小肠梗阻预测因素的临床列线图建议对拔管后小肠梗阻患者进行积极的手术干预，并在入院时出现阴离子间隙异常和低血清白蛋白水平。
方法：收集514例食管癌患者的临床资料。使用多变量logistic回归分析确定的拔管后小肠梗阻的独立危险因素构建列线图。对61例小肠梗阻患者拔管后的治疗方法进行亚组分析。
结果：列线图包含了拔管后小肠梗阻的独立危险因素（胃肠功能恢复[P<.001]，术后白蛋白减少率[P=.009]，和严重的术后并发症[P<.001]）在多变量逻辑回归分析中。最终模型的曲线下面积为0.829(95%置信区间，0.775-0.883）。校准图显示了预测概率和实际概率之间的高度一致性。该模型对内部和时间验证表现出了极好的辨别能力，调整后的C统计量为0.821和0.810(95%置信区间，0.686-0.933),分别。在亚组分析中，阴离子间隙异常(P=.016)和低血清白蛋白水平(P=.005)与小肠梗阻复发相关.模型曲线下面积为0.815(95%置信区间，0.683-0.948)。当存在2个危险因素时,小肠梗阻患者拔管后复发的概率为78.3%。
结论：基于拔管后小肠梗阻预测因素的临床列线图建议对拔管后小肠梗阻患者进行积极的手术干预，并在入院时出现阴离子间隙异常和低血清白蛋白水平。
