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Journal of gastrointestinal surgery : official journal of the Society for Surgery of the Alimentary Tract · 2022

Perioperative Outcomes and Learning Curve of Robot-Assisted McKeown Esophagectomy.

СтатьяПоддержка исследования: вне правительства СШАНазвание и аннотация: Перевод пока не подготовлен
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Sun Hai-Bo, Jiang Duo, Liu Xian-Ben, Xing Wen-Qun, Liu Shi-Lei, Chen Pei-Nan, Li Peng, Ma Ya-Xing

Аннотация

BACKGROUND: This study aimed to evaluate the perioperative outcomes of patients undergoing robot-assisted McKeown esophagectomy (RAME) and the learning curves of surgeons performing RAME at a single center.

METHODS: Perioperative outcomes of RAME and video-assisted McKeown esophagectomy (VAME) were compared after eliminating confounding factors by propensity score matching (PSM). The cumulative sum (CUSUM) method was used to evaluate the learning curves of RAME for a single surgical team.

RESULTS: In general, a total of 198 patients with esophageal cancer (RAME: 45 patients, VAME: 153 patients) were included in this study, and 43 pairs of patients receiving RAME or VAME were matched using 1:1 PSM analysis. Those in the RAME group had more lymph nodes dissected in the total lymph nodes (median 29.0 vs. 26.0, P = 0.011) and the upper mediastinum (median 8.0 vs. 6.0, P < 0.001), especially the left recurrent laryngeal nerve (RLN) lymph node (median 4.0 vs. 2.0, P = 0.001). According to the trend of the CUSUM plot, the learning curve was divided into two stages at the 20th RAME procedure. After mastering the learning curve, RAME harvested a significantly higher number of upper mediastinal lymph nodes (median 9.0 vs. 6.0, P = 0.001), left RLN lymph nodes (median 5.0 vs. 3.5, P = 0.003), and right RLN lymph nodes (median 4.0 vs. 2.0, P = 0.002). Meanwhile, the incidence of postoperative pneumonia in the proficiency phase was significantly lower than that in the learning phase (4.0% vs. 25.0%, P = 0.04).

CONCLUSIONS: RAME improved left RLN lymph node dissection. Surgeons with extensive VAME experience need at least 20 cases to achieve early proficiency in RAME.

Предметные рубрики MeSH

ИП Урсолов Владлен Сергеевич

ИНН 500118482352 · ОГРНИП 314500117700049

Реквизиты и контакты