{Reference Type}: Journal Article
{Title}: Different DLCO Parameters as Predictors of Postoperative Pulmonary Complications in Mild Chronic Obstructive Pulmonary Disease Patients with Lung Cancer.
{Author}: Kim MH;Lee J;Son JW;Shih BC;Jeong W;Jeon JH;Kim K;Jheon S;Cho S;
{Journal}: J Chest Surg
{Volume}: 57
{Issue}: 5
{Year}: 2024 Sep 5
暂无{DOI}: 10.5090/jcs.24.010
{Abstract}: <B>UNASSIGNED: </B>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.<BR><B>UNASSIGNED: </B>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.<BR><B>UNASSIGNED: </B>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.<BR><B>UNASSIGNED: </B>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.