Article Abstract

Refined risk stratification for thoracoscopic lobectomy or segmentectomy

Authors: Ruoyu Zhang, Jürgen Dippon, Godehard Friedel


Background: Given the wide adoption of thoracoscopic lobectomy and positive effect of the thoracoscopic approach for improving postoperative outcomes, questions have arisen regarding the validity of previously published risk assessment models. We sought to review the reliability of the established predictors for patients undergoing thoracoscopic lobectomy.
Methods: From January 2009 to May 2017, 606 patients (275 women, 331 men; median age 67 years) underwent thoracoscopic lobectomy or segmentectomy for confirmed or suspected early-stage lung cancer or metastasis at our institution. Logistic regression analyses were performed to determine the predictors of postoperative complications, followed by assessments of causal inference.
Results: The postoperative mortality, pulmonary complication, cardiovascular complication and overall morbidity rates were 1.0%, 8.9%, 5.8% and 18.0%, respectively. While the American Society of Anesthesiologists physical status (ASA-PS) emerged as an independent morbidity predictor, only a slightly significant association between lung function determinants and overall morbidity was found in the univariable regression analyses. Regarding causal inference, inverse probability of treatment weighting using propensity scores revealed 2- and 1.7-fold increases in the odds of cardiopulmonary complications and overall morbidity in patients with ASA-PS grade 3 or 4 compared with those with ASA-PS grade 1 or 2 (OR =2.116, 95% CI: 1.252–3.577, P=0.005; OR =1.740, 95% CI: 1.095–2.765, P=0.019, respectively).
Conclusions: Our results suggested that the current physiologic evaluation algorithm is also applicable to major lung resection via thoracoscopic approach. ASA-PS is an easily assessable factor capable of predicting major complications following thoracoscopic lobectomy in patients properly selected in compliance with the current guideline. It is recommended to incorporate the ASA-PS into the existing algorithm for more accurate risk stratification in this patient population.