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Intraoperative nerve monitoring in thyroid surgery: Analysis of recurrent laryngeal nerve identification and operative time

  • Siriraj Hospital
  • Harvard Medical School

Research output: Contribution to journalArticlepeer-review

16 Citations (Scopus)

Abstract

Objective: To evaluate the clinical value of intraoperative nerve monitoring (IONM) by comparing the procedure times for thyroidectomies performed with and without IONM. Methods: A prospective, randomized, controlled study was conducted on 32 patients (representing 41 nerves at risk) undergoing thyroidectomies carried out by two experienced head and neck surgeons (CC & WP). Sixteen thyroidectomies were performed without IONM (the “non-IONM group”), while 16 thyroidectomies were performed with IONM (the “IONM group”). The measured datapoints were setup time, time to visual identification of the recurrent laryngeal nerve (RLN), time to confirm the RLN electrophysiologically, dissection time, and total operative time. Results: With both surgeons, the IONM group had shorter visual times to RLN identification than the non-IONM group (CC: 3.7 minutes vs 5.3 minutes; WP: 3.4 minutes vs 9.7 minutes). Additionally, the electrophysiological identification time for the IONM group was shorter than the visual identification time for the non-IONM group. The setup times, dissection times, and total operative times of the 2 groups did not significantly differ (P >.05). No RLN injuries were observed. Conclusions: IONM reduces the time needed for RLN identification in thyroidectomies. Functional RLN confirmation can reassure surgeons of the operative results. Moreover, use of IONM does not significantly impact setup and total operative times. Level of evidence: 2.

Original languageEnglish
Pages (from-to)354-361
Number of pages8
JournalLaryngoscope Investigative Otolaryngology
Volume6
Issue number2
DOIs
Publication statusPublished - Apr 2021

Keywords

  • intraoperative nerve monitoring (IONM)
  • operative time
  • recurrent laryngeal nerve (RLN)
  • thyroid surgery
  • visual identification of RLN

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