| Title | Train time as a quantitative electromyographic parameter for facial nerve function in patients undergoing surgery for vestibular schwannoma. | | Author(s) | Prell J, Rampp S, Romstöck J, Fahlbusch R, Strauss C | | Institution | Department of Neurosurgery, University of Halle-Wittenberg, Halle, Germany. julian.prell@medizin.uni-halle.de | | Source | J Neurosurg 2007 May; 106(5):826-32. | | MeSH | Adult
Aged
Electromyography
Facial Nerve
Facial Paralysis
Female
Humans
Male
Middle Aged
Monitoring, Intraoperative
Neuroma, Acoustic
Postoperative Complications
Prognosis
Reaction Time
Reference Values
Risk Factors
Signal Processing, Computer-Assisted
Software
| | Abstract | OBJECT: The authors describe a quantitative electromyographic (EMG) parameter for intraoperative monitoring of facial nerve function during vestibular schwannoma removal. This parameter is based on the automated detection of A trains, an EMG pattern that is known to be associated with postoperative facial nerve paresis.
METHODS: For this study, 40 patients were examined. During the entire operative procedure, free-running EMG signals were recorded in muscles targeted by the facial nerve. A software program specifically designed for this purpose was used to analyze these continuous recordings offline. By automatically adding up time intervals during which A trains occurred, a quantitative parameter was calculated, which was named "train time." A strong correlation between the length of train time (measured in seconds) and deterioration of postoperative facial nerve function was demonstrated. Certain consecutive safety thresholds at 0.5 and 10 seconds were defined. Their transgression reliably indicated postoperative facial nerve paresis. At less than a 10-second train time, discrete worsening, and at more than 10 seconds, profound deterioration of facial nerve function can be anticipated.
CONCLUSIONS: Train time as a quantitative parameter was shown to be a reliable indicator of facial nerve paresis after surgery for vestibular schwannoma. | | Language | eng | | Pub Type(s) | Journal Article
Research Support, Non-U.S. Gov't
| | PubMed ID | 17542526 |
|
