Abstract
We investigated the learning curve for using intraoperative neural monitoring technology in thyroid cancer, with a view to reducing recurrent laryngeal nerve injury complications. Radical or combined radical surgery for thyroid cancer was performed in 82 patients with thyroid cancer and 147 recurrent laryngeal nerves were dissected. Intraoperative neural monitoring technology was applied and the “four-step method” used to monitor recurrent laryngeal nerve function. When the intraoperative signal was attenuated by more than 50%, recurrent laryngeal nerve injury was diagnosed, and the point and causes of injury were determined. The time required to identify the recurrent laryngeal nerve was 0.5–2 min and the injury rate was 2.7%; injuries were diagnosed intraoperatively. Injury most commonly occurred at or close to the point of entry of the nerve into the larynx and was caused by stretching, tumor adhesion, heat, and clamping. The groups are divided in chronological order; a learning curve for using intraoperative neural monitoring technology in thyroid cancer surgery was generated based on the time to identify the recurrent laryngeal nerve and the number of cases with nerve injury. The time to identify the recurrent laryngeal nerve and the number of injury cases decreased markedly with increasing patient numbers. There is a clear learning curve in applying intraoperative neural monitoring technology to thyroid cancer surgery; appropriate use of such technology aids in the protection of the recurrent laryngeal nerve.
Highlights
With the rise in the incidence of thyroid cancer, increasing numbers of patients are undergoing total thyroidectomy, with consequential voice changes due to recurrent laryngeal nerve (RLN) injury, which has a serious impact on the patient’s quality of life
Electrophysiological intraoperative neural monitoring (IONM) for RLN protection emerged after the regional protection method and fine dissection method
Four patients were diagnosed with RLN injury intraoperatively
Summary
With the rise in the incidence of thyroid cancer, increasing numbers of patients are undergoing total thyroidectomy, with consequential voice changes due to recurrent laryngeal nerve (RLN) injury, which has a serious impact on the patient’s quality of life. According to the Diagnosis and Treatment Guidelines for Patients with Thyroid Nodule and Differentiated Thyroid Cancer in China, the effective protection of the RLN is one of the key points in thyroid cancer surgery. In these guidelines, electrophysiological intraoperative neural monitoring (IONM) for RLN protection emerged after the regional protection method and fine dissection method. Use of IONM is cost-effective for patients undergoing bilateral thyroid surgery [1]. IONM involves applying a stimulating current to contract the dominant muscles through nerve conduction, and transmitting the electromyographic signals back to a nerve monitor through a signal reception electrode in contact with these muscles. The monitor analyzes the absence/presence and strength of the electromyographic signal to determine the nerve positioning and judge its function
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