Background: It is generally agreed that using a bilateral internal thoracic artery (BITA) composite graft improves long-term survival after coronary artery bypass grafting (CABG). Although the left internal thoracic artery (LITA)-based Y-composite graft is widely adopted, technical or anatomical difficulties necessitate complex configurations. We aimed to investigate whether BITA configuration impacts survival or patency in patients undergoing coronary revascularization. Methods: Between January 2006 and June 2017, 1,161 patients underwent CABG at Seoul National University Bundang Hospital, where the standard technique is a LITA-based Y-composite graft with the right internal thoracic artery (RITA) sequentially anastomosed to non-left anterior descending (LAD) targets. Total of 160 patients underwent CABG using BITA with modifications. Their medical records and imaging data were reviewed retrospectively to investigate technical details, clinical outcomes, and graft patency. Results: Modifications of the typical Y-graft (group 1, n=90), LITA-based I-graft (group 2, n=39), and RITA-based composite graft (group 3, n=31) were used due to insufficient RITA length (47%), problems using LITA (28%), and target vessel anatomy (25%). The overall 30- day mortality rate was 1.9%. Among 116 patients who underwent computed tomography or conventional angiography at a mean interval of 29.9±33.1 months postoperatively, the graft patency rates were 98.7%, 95.3%, and 83.6% for the LAD, left circumflex artery, and right coronary artery territories, respectively. Patency rates for the inflow, secondary, and tertiary grafts were 98.2%, 90.5%, and 80.4%, respectively. The RITA-based graft (group 3) had the lowest patency rate of the various configurations (p<0.011). Conclusion LITA-based Y composite graft, showed satisfactory clinical outcomes and patency whereas modifications of RITA- based composite graft had the lowest patency and 5-year survival rates. Therefore, when using RITA-based composite graft, other options should be considered before proceeding atypical configurations.

Shone complex is a rare congenital disorder that involves 4 obstructive lesions of the left heart, as follows: parachute mitral valve, supravalvular mitral ring, subaortic stenosis, and coarctation of the aorta. Incomplete forms with 2 or 3 of these lesions in adult patients have been rarely reported in the literature, meaning that insufficient general data exist concerning the surgical strategy and clinical follow-up. Herein, we report the case of a 31-year-old woman with a diagnosis of incomplete form of Shone complex with parachute mitral valve and coarctation of the aorta who underwent successful single-stage surgical repair.
Adult ; Aortic Coarctation ; Congenital, Hereditary, and Neonatal Diseases and Abnormalities ; Constriction, Pathologic ; Diagnosis ; Female ; Follow-Up Studies ; Heart ; Heart Defects, Congenital ; Humans ; Mitral Valve

Shone complex is a rare congenital disorder that involves 4 obstructive lesions of the left heart, as follows: parachute mitral valve, supravalvular mitral ring, subaortic stenosis, and coarctation of the aorta. Incomplete forms with 2 or 3 of these lesions in adult patients have been rarely reported in the literature, meaning that insufficient general data exist concerning the surgical strategy and clinical follow-up. Herein, we report the case of a 31-year-old woman with a diagnosis of incomplete form of Shone complex with parachute mitral valve and coarctation of the aorta who underwent successful single-stage surgical repair.

Background: 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 FEV 1 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. Methods: 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. Results: 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. Conclusion 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.

Background: 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 FEV 1 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. Methods: 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. Results: 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. Conclusion 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.

Background: 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 FEV 1 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. Methods: 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. Results: 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. Conclusion 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.

Background: 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 FEV 1 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. Methods: 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. Results: 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. Conclusion 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.