Evaluation of intraoperative neuromonitoring (IONM) data with the Mainz IONM Quality Assurance and Analysis tool

Abstract

Abstract Background Intraoperative neuromonitoring is widely used in thyroid and parathyroid surgery to prevent unilateral and especially bilateral recurrent nerve paresis. Reference values for amplitude and latency for the recurrent laryngeal nerve and vagus nerve have been published. However, data quality measures that exclude errors of the underlying intraoperative neuromonitoring (IONM) data (immanent software errors, false data labelling) before statistical analysis have not yet been implemented. Methods The authors developed an easy-to-use application (the Mainz IONM Quality Assurance and Analysis tool) using the programming language R. This tool allows visualization, automated and manual correction, and statistical analysis of complete raw data sets (electromyogram signals of all stimulations) from intermittent and continuous neuromonitoring in thyroid and parathyroid surgery. The Mainz IONM Quality Assurance and Analysis tool was used to evaluate IONM data generated and exported from ‘C2’ and ‘C2 Xplore’ neuromonitoring devices (inomed Medizintechnik GmbH) after surgery. For the first time, reference values for latency and amplitude were calculated based on ‘cleaned’ IONM data. Results Intraoperative neuromonitoring data files of 1935 patients consecutively operated on from June 2014 to May 2020 were included. Of 1921 readable files, 34 were excluded for missing data labelling. Automated plausibility checks revealed: less than 3 per cent device errors for electromyogram signal detection; 1138 files (approximately 60 per cent) contained potential labelling errors or inconsistencies necessitating manual review; and 915 files (48.5 per cent) were indeed erroneous. Mean(s.d.) reference onset latencies for the left vagus nerve, right vagus nerve, recurrent laryngeal nerve, and external branch of the superior laryngeal nerve were 6.8(1.1), 4.2(0.8), 2.5(1.1), and 2.1(0.5) ms, respectively. Conclusion Due to high error frequencies, IONM data should undergo in-depth review and multi-step cleaning processes before analysis to standardize scientific reporting. Device software calculates latencies differently; therefore reference values are device-specific (latency) and/or set-up-specific (amplitude). Novel C2-specific reference values for latency and amplitude deviate considerably from published values.