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J Neurol Surg A Cent Eur Neurosurg 2021; 82(04): 308-316
DOI: 10.1055/s-0040-1701616
Original Article

Facial Nerve EMG: Low-Tech Monitoring with a Stopwatch

Julian Prell
1   Department of Neurosurgery, University of Halle, Halle, Germany
,
Christian Scheller
1   Department of Neurosurgery, University of Halle, Halle, Germany
,
Sebastian Simmermacher
1   Department of Neurosurgery, University of Halle, Halle, Germany
,
Christian Strauss
1   Department of Neurosurgery, University of Halle, Halle, Germany
,
Stefan Rampp
1   Department of Neurosurgery, University of Halle, Halle, Germany
› Author Affiliations Funding Source All the authors report grants from Deutsche Forschungsgemeinschaft DFG (PR1275/1-2) during the conduct of the study.
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Abstract

Objective The quantity of A-trains, a high-frequency pattern of free-running facial nerve electromyography, is correlated with the risk for postoperative high-grade facial nerve paresis. This correlation has been confirmed by automated analysis with dedicated algorithms and by visual offline analysis but not by audiovisual real-time analysis.

Methods An investigator was presented with 29 complete data sets measured during actual surgeries in real time and without breaks in a random order. Data were presented either strictly via loudspeaker (audio) or simultaneously by loudspeaker and computer screen (audiovisual). Visible and/or audible A-train activity was then quantified by the investigator with the computerized equivalent of a stopwatch. The same data were also analyzed with quantification of A-trains by automated algorithms.

Results Automated (auto) traintime (TT), known to be a small, yet highly representative fraction of overall A-train activity, ranged from 0.01 to 10.86 s (median: 0.58 s). In contrast, audio-TT ranged from 0 to 1,357.44 s (median: 29.69 s), and audiovisual-TT ranged from 0 to 786.57 s (median: 46.19 s). All three modalities were correlated to each other in a highly significant way. Likewise, all three modalities correlated significantly with the extent of postoperative facial paresis. As a rule of thumb, patients with visible/audible A-train activity < 1 minute presented with a more favorable clinical outcome than patients with > 1 minute of A-train activity.

Conclusion Detection and even quantification of A-trains is technically possible not only with intraoperative automated real-time calculation or postoperative visual offline analysis, but also with very basic monitoring equipment and real-time good quality audiovisual analysis. However, the investigator found audiovisual real-time-analysis to be very demanding; thus tools for automated quantification can be very helpful in this respect.

Keywords

facial nerve - neurophysiologic monitoring - vestibular schwannoma - facial palsy - electromyography


Publication History

Received: 19 March 2019

Accepted: 03 July 2019

Article published online:
08 January 2021

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