Improving Outcome of Superior Mediastinal Lymph Node Dissection During Esophagectomy: A Novel Approach Combining Continuous and Intermittent Recurrent Laryngeal Nerve Monitoring

Autor: Fion S. Chan, Desmond K. K. Chan, Rui Qi Zhang, Simon Law, Raymond K. Y. Tsang, Jeanette Yat-Yin Kwok, Claudia Wong, Ian Y H Wong
Rok vydání: 2021
Předmět:
Zdroj: Annals of surgery. 274(5)
ISSN: 1528-1140
Popis: OBJECTIVE This study aimed at demonstrating the effects and learning curve of utilizing combined intermittent and continuous recurrent laryngeal nerve (RLN) monitoring for lymphadenectomy during esophagectomy. BACKGROUND RLN lymphadenectomy is oncologically important but is technically demanding. Vocal cord (VC) palsy as a result from RLN injury, carries significant morbidities. METHODS This is a retrospective study of consecutive esophageal squamous cell carcinoma (ESCC) patients who underwent transthoracic esophagectomy from 2010 to 2020. Combined nerve monitoring (CNM) included: CNM which involved a periodic stimulating left vagal electrode and intermittent nerve monitoring which utilized a stimulating probe to identify the RLNs. The integrity of the RLNs was assessed both intermittently and continuously. This technique was introduced in 2014. Patients were divided into "before CNM" and "CNM" groups. The primary outcome was the difference in number of RLN lymph nodes harvested and VC palsy rate. Learning curves were demonstrated by cumulative sum (CUSUM) analysis. RESULTS Two hundred and fifty-five patients were included with 157 patients in "CNM" group. The mean number of RLN lymph nodes harvested was significantly higher (4.31 vs 0.45, P < 0.0001) for the "CNM" group. VC palsy rates were significantly lower (17.8% vs 32.7%, P = 0.007). There was an initial increase in VC palsy rate, peaked at around 46 cases. The increase in lymph nodes harvested above the mean plateaued at around 96 cases. CONCLUSIONS CNM helped improve bilateral RLN lymphadenectomy. Lymph node harvesting was increased with reduction of VC palsy after a learning curve.
Databáze: OpenAIRE