Best Practices in Facial Nerve Monitoring.

OBJECTIVES/HYPOTHESIS: Facial nerve monitoring (FNM) has evolved into a widely used adjunct for many surgical procedures along the course of the facial nerve. Even though majority opinion holds that FNM reduces the incidence of iatrogenic nerve injury, there are few if any studies yielding high-level evidence and no practice guidelines on which clinicians can rely. Instead, a review of the literature and medicolegal cases reveals significant variations in methodology, training, and clinical indications. STUDY DESIGN: Literature review and expert opinion. METHODS: Given the lack of standard references to serve as a resource for FNM, we assembled a multidisciplinary group of experts representing more than a century of combined monitoring experience to synthesize the literature and provide a rational basis to improve the quality of patient care during FNM. RESULTS: Over the years, two models of monitoring have become well-established: 1) monitoring by the surgeon using a stand-alone device that provides auditory feedback of facial electromyography directly to the surgeon, and 2) a team, typically consisting of surgeon, technologist, and interpreting neurophysiologist. Regardless of the setting and the number of people involved, the reliability of monitoring depends on the integration of proper technical performance, accurate interpretation of responses, and their timely application to the surgical procedure. We describe critical steps in the technical set-up and provide a basis for context-appropriate interpretation and troubleshooting of recorded signals. CONCLUSIONS: We trust this initial attempt to describe best practices will serve as a basis for improving the quality of patient care while reducing inappropriate variations. LEVEL OF EVIDENCE: 4 Laryngoscope, 131:S1-S42, 2021.

Transcranial Motor Evoked Potential Alarm Criteria to Predict Foot Drop Injury During Lumbosacral Surgery.

STUDY DESIGN: A retrospective cohort analysis. OBJECTIVE: This study aims to investigate whether waveform alterations in transcranial motor evoked potentials (TCMEPs) can reliably predict postoperative foot drop. SUMMARY OF BACKGROUND DATA: Nerve injury leading to foot drop is a potential complication of lumbosacral surgery. Very limited data exist on the use of intraoperative TCMEPs to identify iatrogenic foot drop. METHODS: We retrospectively reviewed neuromonitoring data from 130 consecutive spine surgeries with instrumentation involving L4-S1. TCMEP waveform analysis included amplitude (A), area under the curve (AUC), latency (L), and duration (D). Patient outcomes were correlated with neuromonitoring results. Intraoperative alert criteria were established on the basis of observed intraoperative changes. RESULTS: Three patients developed severe foot drop with a muscle weakness functional grade ranging from 0/5 to 3/5. Two patients developed a mild foot drop with functional grade 4/5. Twenty-three patients had preoperative weakness in an L5 distribution. One-hundred two patients who had neither preoperative nor postoperative neurological complications served as a control group. Amplitude significantly decreased in patients with a severe postoperative deficit (P = 0.005) as did AUC and duration (P < 0.05). Intraoperative alert criteria defined as a >65% decrease in AUC resulted in a sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of 100%, 91.4%, 12%, and 100%, respectively. When defining an alert criteria as a >50% decrease in amplitude, sensitivity, specificity, PPV, and NPV were 100%, 87.9%, 8.8%, and 100%, respectively. CONCLUSION: Reduction of TCMEP waveform associated with postoperative severe foot drop can be detected during lumbar surgery. Other waveform parameters such as AUC may predict foot drop better than the amplitude. Additional examinations in larger samples of foot drops are needed to validate these alert threshold findings. LEVEL OF EVIDENCE: 4.

Perils of intraoperative neurophysiological monitoring: analysis of "false-negative" results in spine surgeries.

BACKGROUND CONTEXT: Although some authors have published case reports describing false negatives in intraoperative neurophysiological monitoring (IONM), a systematic review of causes of false-negative IONM results is lacking. PURPOSE: The objective of this study was to analyze false-negative IONM findings in spine surgery. STUDY DESIGN: This is a retrospective cohort analysis. PATIENT SAMPLE: A cohort of 109 patients with new postoperative neurologic deficits was analyzed for possible false-negative IONM reporting. OUTCOME MEASURES: The causes of false-negative IONM reporting were determined. MATERIALS AND METHODS: From a cohort of 62,038 monitored spine surgeries, 109 consecutive patients with new postoperative neurologic deficits were reviewed for IONM alarms. RESULTS: Intraoperative neurophysiological monitoring alarms occurred in 87 of 109 surgeries. Nineteen patients with new postoperative neurologic deficits did not have an IONM alarm and surgeons were not warned. In addition, three patients had no interpretable IONM baseline data and no alarms were possible for the duration of the surgery. Therefore, 22 patients were included in the study. The absence of IONM alarms during these 22 surgeries had different origins: "true" false negatives where no waveform changes meeting the alarm criteria occurred despite the appropriate IONM (7); a postoperative development of a deficit (6); failure to monitor the pathway, which became injured (5); the absence of interpretable IONM baseline data which precluded any alarm (3); and technical IONM application issues (1). CONCLUSIONS: Overall, the rate of IONM method failing to predict the patient's outcome was very low (0.04%, 22/62,038). Minimizing false negatives requires the application of a proper IONM technique with the limitations of each modality considered in their selection and interpretation. Multimodality IONM provides the most inclusive information, and although it might be impractical to monitor every neural structure that can be at risk, a thorough preoperative consideration of available IONM modalities is important. Delayed development of postoperative deficits cannot be predicted by IONM. Absent baseline IONM data should be treated as an alarm when inconsistent with the patient's preoperative neurologic status. Alarm criteria for IONM may need to be refined for specific procedures and deserves continued study.

Intraoperative Neuromonitoring Alarms: Relationship of the Surgeon's Decision to Intervene (or Not) and Clinical Outcomes in a Subset of Spinal Surgical Patients with a New Postoperative Neurological Deficit.

BACKGROUND: The goal of intraoperative neurophysiologic monitoring (IONM) is to minimize neurologic injury during surgery, yet patients still emerge with postoperative deficits. Few studies focus on outcomes relative to IONM alarms and interventions in this population. The authors sought to analyze the influence of IONM alarms with and without surgical intervention on patient outcome in spinal surgical patients who suffered immediate postoperative neurologic deficits. METHODS: Of 62,038 spinal surgeries with multimodality IONM, 90 patients with new or worsened postoperative neurologic deficits and whose outcomes were reported immediate to the surgery and at discharge were analyzed. Outcomes at discharge were compared for surgeries in which an IONM alarm versus no alarm occurred. Outcomes where surgical intervention was performed versus not performed were also compared. RESULTS: By discharge, 48 (53.3%) of 90 patients had complete or partial recovery of their postoperative deficit. Patients with IONM alarms and surgical interventions had an 80% (39/49) recovery rate overall versus only 26% (7/27) recovery rate of patients with IONM alarms but no interventions, and only 14% (2/14) of patients without IONM alarms and without interventions (P < 0.001). CONCLUSIONS: These data showed significantly more patients recovered by the time of discharge when a surgical intervention was precipitated by an IONM alarm versus when it was not. The authors conclude that surgical interventions based on IONM alarms do improve patient outcomes despite immediate postoperative deficit.

Differential rates of false-positive findings in transcranial electric motor evoked potential monitoring when using inhalational anesthesia versus total intravenous anesthesia during spine surgeries.

BACKGROUND CONTEXT: False-positive loss of transcranial electrical motor evoked potentials (TCe-MEPs) limits the efficacy of motor tract monitoring during spine surgery. Although total intravenous anesthesia (TIVA) is widely regarded as the optimal regimen for TCe-MEPs, inhalational anesthesia is an alternative regimen. PURPOSE: To compare the rates of false-positive TCe-MEPs during spine surgery for patients anesthetized with TIVA and inhalation anesthesia. STUDY DESIGN: A retrospective analysis of data collected from consecutive patients undergoing TCe-MEP monitoring during spinal surgery. PATIENT SAMPLE: Consecutive adult patients from multiple surgical centers undergoing spine surgery inclusive of cervical or thoracic spinal levels during 2008-2009 who received TIVA or inhalation anesthesia. OUTCOME MEASURES: The primary outcome measure was the rate of false-positive alerts using TCe-MEPS, defined as a persistent loss of 90% or greater of the amplitude of TCe-MEP in one or more muscles not attributed to technical or transient systemic factors (hypotension or hypoxia) and not associated with any postoperative neurologic deficit. METHODS: Patients were divided into two groups according to anesthetic regimen: those anesthetized with one or more inhalational agents (n=1,303) and patients anesthetized with TIVA (n=511). The Fisher exact test and unpaired t test were used to compare group characteristics and false-positive rates. Each group was further subdivided by spinal region (cervical, thoracic, and thoracolumbar) and by presence of preoperative motor deficit. A Pearson chi-squared test was used to identify differences according to spinal region. This study was not supported by any financial sources nor do the authors have any financial relationships to disclose. RESULTS: Patient with inhaled anesthesia showed significantly higher rates of false-positive TCe-MEP changes (15.0% vs. 3.2%) compared with the TIVA group. These differences were significant across all surgical subgroups. The inhaled group had a larger number of patients with preoperative motor deficits compared with TIVA (45.0% vs. 37.4%), a potential confounder for false-positive results. However, a significantly higher rate of false-positive TCe-MEP changes was still observed in the inhaled group (11.4% vs. 0.6% for TIVA) when analyzing only those patients without preoperative motor deficits. CONCLUSIONS: Use of inhalation anesthesia during adult spinal surgery is associated with significantly higher rates of false-positive changes compared with TIVA during TCe-MEP monitoring. This relationship appears independent of preoperative motor status. Further study and multivariate analysis of anesthetic agents, diagnosis, and symptoms is necessary to elucidate the impact of these variables. The potential confounding effects of inhalational anesthesia on TCe-MEP monitoring should be considered when determining anesthetic regimen.

Quality assurance and performance improvement in intraoperative neurophysiologic monitoring programs.

Quality assurance (QA) as it relates to intraoperative neurophysiological monitoring (IONM) can be defined as the systematic monitoring, evaluation, and modification of the IONM service to insure that desired standards of quality are being met. In practice, that definition is usually extended to include the concept that the quality of the IONM service will be improved wherever possible and, although there are some differences in the two terms, in this article the term QA will be understood to include quality improvement (QI) processes as well. The measurement and documentation of quality is becoming increasingly important to healthcare providers. This trend is being driven by pressures from accrediting agencies, payers, and patients. The essential elements of a QA program are described. A real-life example of QA techniques and management relevant to IONM providers is presented and discussed.