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Minimally Invasive Lobectomy Modality and Other Predictors of Conversion to Thoracotomy

Brandon S. Hendriksen, Christopher S. Hollenbeak, Matthew D. Taylor, Michael F. Reed

发表年份
2019
引用次数
15

摘要

Objective Minimally invasive approaches to lobectomy are increasing. Rates of conversion to thoracotomy are well reported but risk factors are poorly understood. This study aimed to determine the impact of surgical modality (video-assisted thoracoscopic surgery [VATS] and robotic) on conversion as well as to identify other risk factors for conversion. Methods The National Cancer Database (NCDB) was used to identify patients who underwent minimally invasive lobectomy between 2010 and 2015. Patient characteristics were compared between VATS and robotic approaches using chi-squared tests and t-tests. Logistic regression models were used to control for covariates and identify factors associated with all minimally invasive conversion, VATS conversion, and robotic conversion. Propensity score matching was used to compare conversion rates of VATS and robotic lobectomy. Results The study included 51,723 patients with lung cancer who underwent minimally invasive lobectomy (VATS or robotic). Conversion was identified in 7,109 (7.3%) operations. The odds of VATS conversions were nearly twice that of robotic conversions (OR 1.94 P < 0.0001). After controlling for VATS and robotic patient imbalances with propensity score matching, there was a 5% difference in conversion rates (14% vs. 9%, P < 0.0001). Other predictors of minimally invasive conversion included community hospitals, tumor size 4.5 cm or greater, and an increasing Charlson comorbidity index ( P < 0.03 for all). Conclusions VATS is associated with nearly twice the odds of conversion as robotic lobectomy. Identifying specific risk factors for both VATS and robotic conversions may aid in appropriate modality selection and reduction of conversions.

关键词

ThoracotomyModality (human–computer interaction)MedicineComputer scienceSurgeryArtificial intelligence

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