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Learning curve for robot-assisted lobectomy of lung cancer

	author = {Guisong Song and Xiao Sun and Shuncheng Miao and Shicheng Li and Yandong Zhao and Yunpeng Xuan and Tong Qiu and Zejun Niu and Jianfang Song and Wenjie Jiao},
	title = {Learning curve for robot-assisted lobectomy of lung cancer},
	journal = {Journal of Thoracic Disease},
	volume = {11},
	number = {6},
	year = {2019},
	keywords = {},
	abstract = {Background: Robotic lobectomy is widely used for lung cancer treatment. So far, few studies have been performed to systematically analyze the learning curve. Our purpose is to define the learning curve to provide a training guideline of this technique.
Methods: A total of 208 consecutive patients with primary lung cancer who underwent robotic-assisted lobectomy by our surgical team were enrolled in this study. Baseline information and postoperative outcomes were collected. Learning curves were then analyzed using the cumulative sum (CUSUM) method. Patients were divided into three groups according to the cut-off points of the learning curve. Intraoperative characteristics and short-term outcomes were compared among the three groups. 
Results: CUSUM plots revealed that the docking time, console time and total surgical time in patients were 20, 34 and 32 cases, respectively. Comparison of the surgical time among the 3 phases revealed that the total surgical time (197.03±27.67, 152.61±21.07, 141.35±29.11 min, P},
	issn = {2077-6624},	url = {}