食管癌术后呼吸衰竭危险因素分析及预测模型的构建

doi:10.3969/j.issn.1006-6233.2019.10.003

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Abstract Objective: To investigate the risk factors of postoperative respiratory failure and the construction of predictive models for esophageal cancer. Methods: 114 patients underwent radical esophageal cancer surgery in the ICU of our hospital from Jan. 2015 to Dec. 2018 were enrolled. The follow-up was divided into two groups according to arterial blood gas analysis: respiratory failure and non-respiratory failure. Risk factors for respiratory failure after radical resection of esophageal cancer. The regression equation for predicting respiratory failure after radical resection of esophageal cancer was further obtained, and the ROC curve was used to evaluate the optimal diagnostic cutoff value and diagnostic efficacy of the predictive model. Results: Of the 114 patients who underwent radical esophageal cancer in the ICU of our hospital, 78 had respiratory failure and 36 had no respiratory failure. Gender, age, height, hyperlipidemia, body weight, FEV1, hypertension, and high There were no significant differences in blood glucose surgery anastomosis, preoperative infection, operation time and other surgical complications (P>0.05). The BMI, smoking index, lung function damage, intraoperative blood loss, lung surgery history and The postoperative mechanical ventilation time was statistically significant (P<0.05). The correlations between smoking index, intraoperative blood loss, lung surgery history and postoperative mechanical ventilation time were 35.427, 1.13, 106.661 and 3.21, respectively. Post-respiratory failure is highly correlated. The probabilistic predictive model of postoperative respiratory failure in esophageal cancer was P=1/[1+e (45.947-3.567 smoking index-0.122 intraoperative blood loss-4.67 lung surgery history-1.166 mechanical ventilation time)], new variable P the AUC is 0.994, which is higher than other variables, indicating that its diagnostic performance is the best. According to the maximum value of the Youden index, the critical value of the new variable P is 0.391. The sensitivity at this time is 96.70% and the specificity is 95.80%. Conclusion: Estimating the incidence of respiratory failure after radical resection of esophageal cancer combined with multiple independent risk factors can improve the diagnostic efficiency of respiratory failure after radical resection of esophageal cancer, improve its diagnostic sensitivity and specificity, and have high clinical value.

Key words： Esophageal cancer radical resection Respiratory failure Risk factors Predictive model

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http://www.hbyxzzs.cn/EN/10.3969/j.issn.1006-6233.2019.10.003 OR http://www.hbyxzzs.cn/EN/Y2019/V25/I10/1593

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