The learning curve for intraoperative neuromonitoring of the recurrent laryngeal nerve in thyroid surgery

Beata Wojtczak,Marcin Barczyński,Mateusz Głód,Krzysztof Sutkowski,Krzysztof Kaliszewski

doi:10.1007/s00423-016-1438-8

Beata Wojtczak, Marcin Barczyński + Show 3 more

Open Access

https://doi.org/10.1007/s00423-016-1438-8

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Abstract

PurposeIntraoperative neuromonitoring (IONM) of the recurrent laryngeal nerve (RLN) is often used in thyroid surgery. However, this procedure is complex and requires a learning period to master the technique. The aim of the study was to evaluate the learning curve for IONM.MethodsA 3-year period (2012–2014) of working with IONM (NIM3.0, Medtronic) was prospectively analyzed with a special emphasis on comparing the initial implementation phase in 2012 (101 patients, 190 RLNs at risk) with subsequent years of IONM use in 2013 (70 patients, 124 RLNs at risk) and 2014 (65 patients, 120 RLNs at risk).ResultsThe rate of successful IONM-assisted RLN identification increased gradually over the 3-year study period (92.11 % in 2012 vs. 95.16 % in 2013 vs. 99.16 % in 2014; p = 0.022), with a corresponding decrease in the rate of technical problems (12.87, 4.3, and 4.6 %, respectively; p = 0.039). The rate of RLN injuries tended to decrease over time: 3.68, 1.55, and 0.83 %, respectively (p = 0.220). Between 2012 and 2014, increases in the sensitivity (71.4 vs. 100 %), specificity (98 vs. 99 %), positive predictive value (62.5 vs. 75 %), negative predictive value (98 vs. 100 %), and overall accuracy of IONM (97.4 vs. 99.6 %) were observed (p = 0.049). Increasing experience with IONM resulted in more frequent utilization of total thyroidectomy (92 % in 2012 vs. 100 % in 2013–2014; p = 0.004).ConclusionsThere was a sharp decrease in the number of technical problems involving equipment setup from 2012 to 2014.

Highlights

Identification of the recurrent laryngeal nerve (RLN) during thyroid surgery minimizes the risk of nerve injury and is considered the gold standard [1,2,3,4,5,6]
There was a sharp decrease in the number of technical problems involving equipment setup from 2012 to 2014
While a course in neuromonitoring alone provides a good basis for introducing the technique for thyroid surgery, only independent experience of a number of thyroid procedures using Intraoperative neuromonitoring (IONM) can enable surgeons to use it to its full advantage in order to minimize the RLN injury rate [8,9,10,11]

Summary

Introduction

Identification of the recurrent laryngeal nerve (RLN) during thyroid surgery minimizes the risk of nerve injury and is considered the gold standard [1,2,3,4,5,6]. Intraoperative neuromonitoring (IONM), a complement to visualization of the RLN, was introduced in 1966 by Shedd [1, 7] It facilitates nerve identification and permits intraoperative evaluation and prediction of RLN function [1, 7]. IONM is currently a standardized technology, and its everyday use is increasingly widespread [1] Introducing this technique requires previous experience in thyroid surgery, as well as theoretical preparation, preferably at a center with extensive experience working with IONM technology. While a course in neuromonitoring alone provides a good basis for introducing the technique for thyroid surgery, only independent experience of a number of thyroid procedures using IONM can enable surgeons to use it to its full advantage in order to minimize the RLN injury rate [8,9,10,11]. The aim of this study was to evaluate the learning curve for IONM of the RLN at an academic center

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