Abstract：
UNASSIGNED: Numerous studies have investigated methods of predicting postoperative pulmonary complications (PPCs) in lung cancer surgery, with chronic obstructive pulmonary disease (COPD) and low forced expiratory volume in 1 second (FEV1) being recognized as risk factors. However, predicting complications in COPD patients with preserved FEV1 poses challenges. This study considered various diffusing capacity of the lung for carbon monoxide (DLCO) parameters as predictors of pulmonary complication risks in mild COPD patients undergoing lung resection.
UNASSIGNED: From January 2011 to December 2019, 2,798 patients undergoing segmentectomy or lobectomy for non-small cell lung cancer (NSCLC) were evaluated. Focusing on 709 mild COPD patients, excluding no COPD and moderate/severe cases, 3 models incorporating DLCO, predicted postoperative DLCO (ppoDLCO), and DLCO divided by the alveolar volume (DLCO/VA) were created for logistic regression. The Akaike information criterion and Bayes information criterion were analyzed to assess model fit, with lower values considered more consistent with actual data.
UNASSIGNED: Significantly higher proportions of men, current smokers, and patients who underwent an open approach were observed in the PPC group. In multivariable regression, male sex, an open approach, DLCO <80%, ppoDLCO <60%, and DLCO/VA <80% significantly influenced PPC occurrence. The model using DLCO/VA had the best fit.
UNASSIGNED: Different DLCO parameters can predict PPCs in mild COPD patients after lung resection for NSCLC. The assessment of these factors using a multivariable logistic regression model suggested DLCO/VA as the most valuable predictor.
UNASSIGNED: From January 2011 to December 2019, 2,798 patients undergoing segmentectomy or lobectomy for non-small cell lung cancer (NSCLC) were evaluated. Focusing on 709 mild COPD patients, excluding no COPD and moderate/severe cases, 3 models incorporating DLCO, predicted postoperative DLCO (ppoDLCO), and DLCO divided by the alveolar volume (DLCO/VA) were created for logistic regression. The Akaike information criterion and Bayes information criterion were analyzed to assess model fit, with lower values considered more consistent with actual data.
UNASSIGNED: Significantly higher proportions of men, current smokers, and patients who underwent an open approach were observed in the PPC group. In multivariable regression, male sex, an open approach, DLCO <80%, ppoDLCO <60%, and DLCO/VA <80% significantly influenced PPC occurrence. The model using DLCO/VA had the best fit.
UNASSIGNED: Different DLCO parameters can predict PPCs in mild COPD patients after lung resection for NSCLC. The assessment of these factors using a multivariable logistic regression model suggested DLCO/VA as the most valuable predictor.
摘要：
■许多研究已经调查了预测肺癌手术术后肺部并发症（PPCs）的方法，慢性阻塞性肺疾病（COPD）和1秒用力呼气量低（FEV1）被认为是危险因素。然而,预测FEV1保留的COPD患者并发症存在挑战.这项研究认为，在接受肺切除术的轻度COPD患者中，肺对一氧化碳（DLCO）参数的各种扩散能力可预测肺部并发症的风险。
■从2011年1月至2019年12月，评估了2,798例接受肺段切除术或肺叶切除术的非小细胞肺癌（NSCLC）患者。关注709名轻度COPD患者，不包括COPD和中度/重度病例，3个包含DLCO的模型，预测术后DLCO（ppoDLCO），和DLCO除以肺泡体积（DLCO/VA）进行逻辑回归。分析了Akaike信息准则和Bayes信息准则来评估模型拟合度，较低的值被认为与实际数据更一致。
■男性比例明显更高，当前吸烟者,在PPC组中观察到接受开放入路的患者。在多变量回归中，男性,一个开放的方法，DLCO<80%,ppoDLCO<60%，DLCO/VA<80%显著影响PPC发生。使用DLCO/VA的模型具有最佳拟合。
■不同的DLCO参数可以预测NSCLC肺切除术后轻度COPD患者的PPCs。使用多变量逻辑回归模型评估这些因素表明DLCO/VA是最有价值的预测因子。
■从2011年1月至2019年12月，评估了2,798例接受肺段切除术或肺叶切除术的非小细胞肺癌（NSCLC）患者。关注709名轻度COPD患者，不包括COPD和中度/重度病例，3个包含DLCO的模型，预测术后DLCO（ppoDLCO），和DLCO除以肺泡体积（DLCO/VA）进行逻辑回归。分析了Akaike信息准则和Bayes信息准则来评估模型拟合度，较低的值被认为与实际数据更一致。
■男性比例明显更高，当前吸烟者,在PPC组中观察到接受开放入路的患者。在多变量回归中，男性,一个开放的方法，DLCO<80%,ppoDLCO<60%，DLCO/VA<80%显著影响PPC发生。使用DLCO/VA的模型具有最佳拟合。
■不同的DLCO参数可以预测NSCLC肺切除术后轻度COPD患者的PPCs。使用多变量逻辑回归模型评估这些因素表明DLCO/VA是最有价值的预测因子。
