|Year : 2018 | Volume
| Issue : 1 | Page : 84-93
Intraoperative neurophysiological monitoring team's communiqué with anesthesia professionals
Anurag Tewari1, Lisa Francis1, Ravi N Samy2, Dean C Kurth1, Joshua Castle3, Tiffany Frye3, Mohamed Mahmoud1
1 Department of Anesthesia, Cincinnati Children's Hospital Medical Center, Cincinnati, USA
2 Department of Otolaryngology-Head and Neck Surgery, University of Cincinnati (UC) College of Medicine, and Neurosensory Disorders Center at UC Gardner Neuroscience Institute, Cincinnati, USA
3 Evokes LLC, Cincinnati, Ohio, USA
|Date of Web Publication||15-Mar-2018|
Department of Anesthesia, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio
Source of Support: None, Conflict of Interest: None
Background and Aims: Intraoperative neurophysiological monitoring (IONM) is the standard of care during many spinal, vascular, and intracranial surgeries. High-quality perioperative care requires the communication and cooperation of several multidisciplinary teams. One of these multidisciplinary services is intraoperative neuromonitoring (IONM), while other teams represent anesthesia and surgery. Few studies have investigated the IONM team's objective communication with anesthesia providers. We conducted a retrospective review of IONM-related quality assurance data to identify how changes in the evoked potentials observed during the surgery were communicated within our IONM-anesthesia team and determined the resulting qualitative outcomes.
Material and Methods: Quality assurance records of 3,112 patients who underwent surgical procedures with IONM (from 2010 to 2015) were reviewed. We examined communications regarding perioperative evoked potential or electroencephalography (EEG) fluctuations that prompted neurophysiologists to alert/notify the anesthesia team to consider alteration of anesthetic depth/drug regimen or patient positioning and analyzed the outcomes of these interventions.
Results: Of the total of 1280 (41.13%) communications issued, there were 347 notifications and 11 alerts made by the neurophysiologist to the anesthesia team for various types of neuro/orthopedic surgeries. Prompt communication led to resolution of 90% of alerts and 80% of notifications after corrective measures were executed by the anesthesiologists. Notifications mainly related to limb malpositioning and extravasation of intravenous fluid.
Conclusion: Based on our institutions' protocol and algorithm for intervention during IONM-supported surgeries, our findings of resolution in alerts and notifications indicate that successful communications between the two teams could potentially lead to improved anesthetic care and patient safety.
Keywords: Anesthesia, communication, electroencephalography, electromyography, intraoperative neurophysiological monitoring, motor evoked potentials, patient safety, somatosensory evoked potentials, transcranial motor evoked potentials
|How to cite this article:|
Tewari A, Francis L, Samy RN, Kurth DC, Castle J, Frye T, Mahmoud M. Intraoperative neurophysiological monitoring team's communiqué with anesthesia professionals. J Anaesthesiol Clin Pharmacol 2018;34:84-93
|How to cite this URL:|
Tewari A, Francis L, Samy RN, Kurth DC, Castle J, Frye T, Mahmoud M. Intraoperative neurophysiological monitoring team's communiqué with anesthesia professionals. J Anaesthesiol Clin Pharmacol [serial online] 2018 [cited 2021 Apr 18];34:84-93. Available from: https://www.joacp.org/text.asp?2018/34/1/84/227574
| Introduction|| |
The growing trend to improve quality, safety, efficiency, and efficacy in all areas of healthcare, in general, has also extended to specific processes, such as the complex profile of perioperative care with its highly technical, multidisciplinary teams. With an increasing focus on patient safety, institutions are adopting process improvement initiatives. This is not only related to procedural skills but also involves system failures associated with the organization and communication challenges as the lack of communication leads to errors, morbidity, and mortality. Enhancing communication across multidisciplinary teams increases healthcare quality by limiting adverse events, decreasing the length of stay, and improving outcomes.
One of these multidisciplinary services is intraoperative neuromonitoring (IONM) that works in tandem with the teams responsible for anesthesia and surgery. IONM uses electrophysiological monitoring to detect and prevent intraoperative neurologic injuries before they progress to permanent deficits. IONM is a truly collaborative, team-based practice requiring close cooperation and excellent communication. IONM is performed by highly trained technicians and neurophysiologists. The neurophysiologist can be on-site or remote. Pre-requisites for effective IONM real-time include instant communication between the surgeon(s), anesthesiologist(s), the IONM technician(s), and the neurophysiologist(s). Integration of IONM into the protocols of various spinal, vascular, and intracranial surgeries has now become the standard of care.,,,,
Several electrophysiological modalities are used during IONM. The choice of modality used depends upon the type of surgery and the neural structures at risk. Monitoring modalities typically include electroencephalography (EEG), somatosensory evoked potentials (SSEPs), transcranial motor evoked potentials (TcMEPs), brainstem auditory evoked potentials (BAERs), electromyography (EMG), and train of four (TOF). During monitoring, there is a paucity of information regarding improvements that could be identified in a stepwise manner to address technical or communications issues. Intraoperative EEG is indicative of the anesthetic depth, and deviations in its parameters may warrant a quick adjustment in the patient's anesthetic regimen to ensure balanced anesthesia. While fluctuations in peripheral SSEPs may indicate traction on nerves or brachial plexus, necessitating adjustment in patient's limb positioning.
Each member of the IONM team has a separate role, and all team members should understand each other's job. The technologist and interpreting physician need to understand the surgical procedure and recognize where the role of IONM is vital. Therefore, successful IONM requires communication and cooperation among the monitoring, anesthesia, and surgical teams. Improvements in IONM can be seen in both the technical aspects of the process and chain of the team's communications.
Our IOMN team works closely with the anesthesiology and surgical teams to optimize signal acquisition and to effectively communicate changes to the patient's nervous system that indicates impending injury. A qualified neurophysiologist works in tandem with a technician to provide real-time analysis of signals and rapid interpretation of signal changes. Signal changes can result in no action, notification, or an alert. There are specific protocols to be followed in the event of an alert.
Several studies have focused upon improved patient outcomes with effective interactions between the IONM and surgical teams.,,,, We were unable to find any existing literature elaborating the efficacy of perioperative communication between the IONM and anesthesia providers. In our experience, we have observed that communications, specifically between the IONM-anesthesiologist team, though ubiquitous, remains undocumented even though this interaction could potentially lead to improved anesthetic care, patient safety, and outcome. Hence, we reviewed quality assurance IONM records to determine how changes observed in IONM modalities were communicated to the anesthesiologists and their resulting qualitative outcomes.
| Material and Methods|| |
This study was conducted at the University of Cincinnati Medical Center (UC), Cincinnati, Ohio, and Cincinnati Children's Hospital Medical Center (CCHMC), Cincinnati, Ohio after obtaining approval from the Institutional Review Board of both the institutes. We retrospectively reviewed electronic medical records (EMRs) of patients who underwent surgery with IONM between May 2010 and February 2015 at either institution. IONM modalities included EEG, SSEP, TcMEPs, and EMG. The type of monitoring used was noted on the quality assurance (QA) form completed after each surgery [Appendix A [Additional file 1]], and data were entered into an electronic database. We extracted and analyzed communications that exclusively pertained to information exchange between IONM and anesthesia team. We noted the type of communication, defined by IONM protocol, and corrective steps that were undertaken by the anesthesiologists.
Intraoperative neuromonitoring alert and notifications
Communications were defined as either “alerts” or “notifications” as per our IONM protocol. The qualified neurophysiologist monitoring the case decides when either of the above is to be communicated to the anesthesia team.
Our IONM protocol defines an alert as a significant change in the IONM signals requiring immediate intervention by the anesthesia team. For example, an EEG alert describes the cessation of EEG activity, burst suppression (i.e., isoelectric activity ≥3 s) or loss of faster frequencies, focal slowing, or loss of amplitude., An SSEP alert pertains to complete loss or >50% decrease in amplitude or 10% increase in latency after ruling out technical and surgical causes. A TcMEP alert is defined as 80% or more decrement in the motor evoked potential amplitude or increase in the stimulation threshold of 100 V or more from the baseline.
IONM protocol defines a notification as an abnormal IONM signal change in that neither constitutes an alert nor warrants immediate intervention. A notification represents a change that could either resolve or progress to an alert. Notifications are issued to prevent deterioration in the perioperative neurophysiological status of the patient during surgery. This abnormal signal change warranted no immediate intervention but requires a close observation for further deterioration.
Patient records of all cases where IONM signal changes prompted further action by the anesthesia team were included in the study. Records were included if a notification or alert (identified by a QA form) was issued exclusively to the anesthesia provider, and surgical or mechanical cause was ruled out [Figure 1].
Patient records documenting communications not directed to anesthesia providers, communications that were vague or inconclusive on the cause of IONM signal abnormalities, and incomplete documentation by the IONM team were excluded from the study.
Multiple alerts or notifications in a single patient were recorded as a single event. Notifications that progressed to alerts were recorded as a single alert. IONM modality, changes in drug dosage (infusion rate, bolus intravenous administration, etc.), and resolution or persistence of notification were recorded based on IONM and anesthesia records. The data was analyzed using appropriate statistical tests along with Bonferroni correction to decrease the overall incidence of false positives.
Communication flow: Intraoperative neurophysiological monitoring-anesthesia team
Our QA form details any communication (notification or alert) initiated by the IONM team to any other team (i.e., surgery and anesthesia). This included electronic medical records (EMRs) that noted an IONM team member had informed the anesthesia provider about a substantial change in the IONM signals after excluding a surgical or mechanical cause(s). In each case, the initial alert or notification was issued by the IONM team. This communication was followed by either the physician or neuromonitoring technician verbally informing the anesthesia provider (staff/attending anesthesiologist, fellow, resident, or nurse anesthesia practitioner), and bringing to his or her attention regarding the evoked potential signal change(s). We also identified any subsequent change in administered drug dosage (infusion rates or bolus of intravenous drug) in the anesthesia record related to the notification or alert, and any other action taken to resolve the issue [Figure 2]. This was followed by documentation of outcome observed after the anesthetic intervention.
|Figure 2: Flowchart of communication between the IONM and Anesthesia service providers during the surgical procedure followed at our institute|
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In our institute, the neurophysiologist physician(s) providing the oversight for the surgical cases is based in-house and is solely focused on real-time monitoring with the neurotechnologist(s) in the operation theatre. This allows their presence in the operation theater in case there is an alert being issued to either the surgical or the anesthesiologist team, thereby providing for an earlier and successful resolution of the problem.
Anesthesia protocol and strategies for surgeries using intraoperative neurophysiological monitoring
Our IONM protocol strongly advocates use of total intravenous anesthesia (TIVA) for patients who undergo neurosurgical or spinal surgeries using IONM, particularly if TcMEP monitoring is planned. Propofol and remifentanil are the most common drugs used for TIVA. Neuromuscular blockers are avoided if the IONM involves EMG or TcMEP, but short-acting neuromuscular blockers (NMB) are acceptable for intubation. Neuromuscular or TOF monitoring is used to ensure the patient has 4/4 twitches before commencing IONM monitoring and surgery.
Perioperatively, the anesthesiologists/CRNAs notify the IONM team if they are administering drug(s) that could potentially interfere in the interpretation of the IONM modalities being monitored. These may include but are not limited to neuromuscular blockers, ketamine, bolus of propofol, opioids, benzodiazepines, etc., or when they increase the volatile anesthetics being delivered (increasing MAC).
| Results|| |
During the 5-year study period, 3112 consecutive patients undergoing surgical procedures under general anesthesia with IONM (1480 form CCHMC and 1632 from UC) were included in the study. In total, 1280 (41.13%) communications were issued to the surgical or anesthesia teams during the study period. Anesthesiologists were advised 358 (27.96%) times (11 alerts and 347 notifications) about the IONM signal changes [Table 1].
|Table 1: Distribution of IONM modality alerts and notifications issued to the anesthesiology team|
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A total of 261 (8.39%) IONM alerts were issued during the study period, of which only 11 alerts exclusively directed towards to the anesthesiologists [Table 1]. All 11 alerts were related to persistent EEG burst suppression intraoperatively. These alerts occurred in 5 spinal surgeries, 4 craniotomies, 1 carotid endarterectomy, and 1 lower limb salvage surgery. The anesthesia providers acknowledged all the alerts. Corrective measures, such as changing TIVA regimens, were undertaken in all cases. The EEG aberration causing the alert resolved in 10 (91%) patients before the end of the surgical procedure. EEG remained in burst suppression despite anesthetic intervention in 1 (10%) patient. In this case, an elderly gentleman undergoing a craniotomy for tumor resection and delayed emergence from anesthesia warranted admission to neurointensive care unit for extubation and further care. Postoperative follow-up did not reveal any clinically significant cognitive dysfunction. An Exact Binomial Test for EEG Alerts, to check if the proportion of resolved alerts were higher than that of alerts that persisted found an P value of 0.006, and since it is lesser than 0.05, it implies that for EEG it is more likely for an alert to be resolved than for it to persist.
A total of 1019 (32.74%) notifications were issued to both surgical and anesthesiology teams in the 3112 recorded cases. Of these only 347 (34.05%) notifications issued were specifically directed towards the anesthesiologists [Table 1]. Anesthetic remedial action resolved 276 (79.54%) notifications, while in 71 (20.46%) the changes in IONM signals persisted till the end of the procedure.
A total of 268 (77.23%) notifications were related to EEG signal changes; of these, 96 (35.82%) were related to intracranial surgeries, 145 (54.1%) to spinal surgeries, and 26 (9.7%) to other types of surgeries. Related EEG results indicated 178 (66%) to deepened planes of anesthesia or EEG burst suppression and 90 (34%) to lighter planes of anesthesia evidenced by increases in signal frequency or spectral index. Subsequently, 215 (80.22%) cases resolved and IONM signals returned to baseline. Using Exact binomial test and after Bonferroni correction, a P value of less than 0.0001 was observed. Hence, we have a statistically significant evidence that for EEG the proportion of resolved notifications is higher than that of notifications that persisted.
Signal changes remained abnormal in 53 (19.78%) cases. Notably, patients who were predominantly afflicted with abnormal EEG signals experienced delayed emergence from anesthesia. None of these patients exhibited postoperative/permanent neurological deficits.
We also noted that in the pediatric population there were more notifications issued at the time before surgical incision to allow deeper planes of anesthesia and avoidance of patient movement. Ninety (33.48%) notifications were also issued when the EEG signal frequency or EEG spectral index increased, indicating that the patients were enduring lighter planes of anesthesia.
The SSEP notifications were related to malpositioning of an extremity [Table 1] and extravasation of intravenous fluid in the patient's limb [an example is shown in [Figure 3]. Statistically significant P< 0.05 suggested that the proportion of resolved notifications is higher than that for the notifications that persisted. In all cases, SSEP issues resolved when anesthesia providers took corrective actions and signals returned to baseline. No neurological deficits were observed postoperatively during the follow up period.
|Figure 3: SSEP signals in a 49-year-old male who underwent lumbar fusion and decompression surgery in prone position on Mizuho OSI Modular Table System. This represents a right arm positioning change prior to spinal manipulation. The anesthesia team was informed and they corrected the right arm positioning and thereafter the signals returned to baseline|
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TcMEPs notifications correlated with hemodynamic and anesthetic depth of the patients and resolved with appropriate adjustments in anesthetics. IONM signal changes prompted interventions by anesthesiologists to increase mean arterial pressure (inotropic support or fluid challenge), and in six (0.19%) patients steroids were administered. A P value with Bonferroni correction (0.0014) was less than 0.05, thus suggesting statistically significant indication that for TcMEP; the proportion of resolved notifications was higher when compared to notifications that persevered.
A total of 520 (16.71%) EMG-related notifications were issued, of which 26 pertained to neurogenic activity seen in the hallicus and brevis group of muscles and were not related to surgical manipulation. The remaining 494 notifications were related to surgical causes. Anesthetic corrections resolved 21 (80.77%) while 5 (19.23%) persisted. These 5 patients required pain medications for prolonged period in the postoperative period due to muscular pain. The P values obtained using Exact Binomial test (0.014) and after Bonferroni correction (0.057) were not comparable. Without the Bonferroni correction, the P value of the test is less than 0.05, and we could infer that significant evidence exists that for EMG, the proportion of resolved notifications was higher than that of notifications that persisted. However, with the Bonferroni correction, the result was no longer significant at 0.05. It is “safer” to report that, with the Bonferroni corrected P value, there is only marginal evidence that the proportion of resolved notifications is higher than that of notifications that persisted.
| Discussion|| |
Communications breakdowns are one of the main causes of surgical errors. A study of three teaching hospitals attributed 43% of errors to systems-related communications failures. In a strategy to address adverse events related to communication-related failures, Awad et al. adopted the crew resource management principles practiced in the aviation industry. Over a 2-month training period, the medical team of surgeons, anesthesiologists, and nurses in the OR reported improved interpersonal communications, safer environment, and fewer antagonistic events, thus promoting effective communication towards the goal of patient safety.
Given the evidence that improved IONM-surgical team interactions can improve patient outcomes,,,,, our study focused on defining the type and effect of communication between the anesthesia providers and IONM team during a 5-year period. Of the 3112 patient records and 1019 (33%) communications reviewed, 347 notifications and 11 alerts were made explicitly to anesthesia providers. This is close to one-third of the communiqué analyzed in the study, thereby demonstrating an active perioperative interaction between the two teams. This has not been documented or elaborated upon previously in literature to the best of our knowledge.
Based on our protocol's definitions of alerts and notifications during IONM-supported surgeries, our findings indicated resolution in 90% of alerts and 80% of notifications. This indicates that successful conduct and interpretation of IONM has the potential of refining anesthetic care and patient safety.
Our institution's IONM protocol defines the communication type and path for the surgical team. It also outlines action steps when signals point to a problematic change in neural status. For notifications, after corrective actions taken by the anesthesiologist, 276 (80%) cases resolved and returned to the baseline. IONM signals remained abnormal in 71 (20%) of the cases studied. For alerts, EEG problems resolved in 10 (90%) patients. Thus, our neurophysiologist-anesthesiologist communications proved effective in enhancing anesthetic depth management.
In the OR, anesthesia providers can be overwhelmed with data, making it a herculean task to prioritize, integrate, and act appropriately. The effectiveness of IONM in providing real-time monitoring of the patient's neural status, in part, reflects the collaboration of the neurophysiologist-anesthesiologist communication. This interface allows for adjustments to the anesthetic management and avoidance of adverse patient outcomes. The neurophysiologist relies on anesthesia providers to provide a milieu that is supportive for monitoring (e.g., significant IONM changes related to anesthetic agents can impede interpretation). The anesthesia provider depends on the IONM team to detect physiologic deterioration depicted by monitoring potentials.
During intraoperative monitoring, EEG waveforms represent the fluctuations of excitatory postsynaptic potentials and inhibitor postsynaptic potentials on the dendrites of cortical neurons. This technique based on wave patterns and spectral edge frequency (SEF) estimates the depth of anesthesia. In part, it can guide the IONM-anesthesia team in avoiding the problems of either too little (patient movement ,) or too much (hemodynamic suppression ,) anesthesia. Nonetheless, correlation of sedation scores and SEF-95 can be imperfect. Bispectral index (BIS) is an example of this imperfect correlation. Compared with older children, those younger than two years old (especially <12 months) will have higher SEF-95 or BIS values for similar sedation scores.
Good communication between the anesthesia and IONM teams is essential given the dose-dependent effects of anesthetic agents on EEG potentials and is critical in procedures such as carotid endarterectomy. Anesthetic agents may either cause or obscure focal EEG abnormalities. During cross clamping, attenuation or loss of higher frequency background called widespread, anterior maximum, rhythmic activity and the advent of regional delta activity constitute the two principal changes associated with critically low cerebral blood flow up. Importantly, higher concentrations of anesthetics can lead to suppression-burst or complete cessation of EEG activity, rendering detection of cerebral ischemia nearly impossible. Therefore, coordination between the IONM-anesthesia team during such critical periods can help to ensure appropriate levels of anesthetic depth. In our study, we noted a high incidence of alert (55%) for EEG-related changes during carotid endarterectomy.
Monitoring SSEPs can depict the integrity of the sensory tract from the periphery to the primary sensory cortex. Therefore, early recognition and prevention of imminent position-related nerve injury are possible. Poor patient positioning can cause a gradual decline in the median or ulnar nerve SSEPs because of traction on the brachial plexus. These changes should not be ignored; limbs should be repositioned if necessary to restore the SSEPs to the baseline. Uncorrected positioning errors (usually related to inadequate vigilance) can lead to prolonged deterioration, loss of the SSEPs, and associated increased postoperative morbidity. Similar to other case reports,, we noted similar incidental findings: attentive perioperative SSEP monitoring (especially with positioning) validated its practicality in the early recognition and prevention of imminent position-related nerve injury and extravasation of intravenous fluids.
During IONM, the acute, complete loss of SSEP or MEP represents a crisis – a potential scenario where the failure of communication among the operating team can be disastrous. Anesthesia providers should have an in-depth understanding of the anesthetic and physiological factors that can influence evoked potentials, including blood pressure, temperature, hematocrit, acid-base balance, and oxygen and carbon dioxide levels. These effects must be differentiated from signal decay due to pathological causes to avoid false-positive alerts. Though not yet systematically analyzed, the phenomenon of “anesthetic fade,” (prolonged exposure to anesthetic agent necessitating higher stimulating threshold to elicit MEP responses) should be kept in mind.
Once the acute loss is detected, there is an urgent need to restore adequate perfusion to neural tissue. Based on our institution's protocol, a critical neurophysiologic alert triggered a sequence of distinct interventional steps as defined in an algorithm [Figure 4], specifically identifying roles of the surgeon, anesthesia providers, operating room nurses, and IONM team. In efforts to continue improving patient safety in procedures that use IONM, we recently implemented simulation sessions. The team practices stepwise, team-based activities for scenarios such as acute loss of MEP during a spine procedure. The critical-event training algorithms and lessons learned during simulation enhance teamwork and reduce risk during complex procedures. This has been shown in our institutions as well as in high-risk scenarios from other professions., We advocate the creation of a culture in which any provider, at any level, can speak up at any time. Healthcare providers are more willing to voice potential safety concerns when they feel their input is desired and respected. In the realm of IONM and anesthesia, providers must communicate any concern immediately, considering the patient's condition, type of surgical procedure, and monitoring modalities used.
|Figure 4: Spinal Deformity IONM Alert Pathway followed by our IONM department|
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Our retrospective study has several inherent limitations that could be addressed in a future prospective, high-powered study. First, we examined only the interactions between the anesthesia and IONM teams and the resultant changes in anesthetic regimen; we did not follow the clinical course of the anesthesia adjustments and links to adverse outcome(s). Second, no specific values were noted from the EEG notifications from narrow index range. That is, the accuracy of EEG monitoring to measure anesthetic depth is difficult; there is no clinical or neurophysiological gold standard beyond the loss of responsiveness to which the monitor can be calibrated or tested against. The data collection was limited to categories present in the QA form [Appendix A] that did not quantify multiple alerts or notification in a singular case. Our study excluded extensive follow-up of postoperative clinical course of patients in whom aberrant IONM signals did not return to the baseline signals. Unlike other studies which imparted training to improve communication and teamwork techniques and then compared the “before and after” effects of training various teams involved in the process surgery,,,, we focused on the prevailing situation in our institute to establish a landmark and hope further efforts and research is initiated to improve the present and future circumstances.
| Conclusion|| |
Given the importance of team performance in patient safety, understanding and communicating the factors affecting IONM modalities has assumed a greater level of importance recently. Effective communication and adoption of standardized tools and behaviors is essential for the delivery of high-quality, safe patient care, especially during the critical situations that arise when neuromonitoring signals are severely compromised. Continuous IONM is a useful real-time adjunct to help anesthesiologists adjust their anesthetic dosing, and nerve injury related to malpositioning. Efforts to educate anesthesia team about the neuromonitoring modalities and improve communication with the neuromonitoring team should proceed in tandem with advances in neuromonitoring technology. We also believe that more interaction and understanding between the IONM and anesthesiologists would encourage research and innovation opportunities in the future aimed at improved patient outcomes.
We would sincerely like to thank Ms. Mary Kemper (University of Cincinnati Medical Center) and Ms. Maria Ashton (Cincinnati Childrens Hospital Medical Center) who helped in proof-reading and editing this manuscript for grammar and syntax.
There are no affiliations with or involvement in any organization or entity with any financial interest (such as honoraria; educational grants; participation in speakers' bureaus; membership, employment, consultancies, stock ownership, or other equity interest; and expert testimony or patent-licensing arrangements), or non-financial interest (such as personal or professional relationships, affiliations, knowledge or beliefs) in the subject matter or materials discussed in this manuscript.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
| References|| |
Epstein NE. Multidisciplinary in-hospital teams improve patient outcomes: A review. Surg Neurol Int 2014;5(Suppl 7):S295-S303.
Cheng JS, Ivan ME, Stapleton CJ, Quinones-Hinojosa A, Gupta N, Auguste KI. Intraoperative changes in transcranial motor evoked potentials and somatosensory evoked potentials predicting outcome in children with intramedullary spinal cord tumors. J Neurosurg Pediatr 2014;13:591-9.
Lall RR, Lall RR, Hauptman JS, Munoz C, Cybulski GR, Koski T, et al
. Intraoperative neurophysiological monitoring in spine surgery: Indications, efficacy, and role of the preoperative checklist. Neurosurg Focus 2012;33:E10.
Macdonald DB, Skinner S, Shils J, Yingling C, American Society of Neurophysiological M. Intraoperative motor evoked potential monitoring-a position statement by the American Society of Neurophysiological Monitoring. Clin Neurophysiol 2013;124:2291-316.
Phillips JL, Chalouhi N, Jabbour P, Starke RM, Bovenzi CD, Rosenwasser RH, et al
. Somatosensory evoked potential changes in neuroendovascular procedures: Incidence and association with clinical outcome in 873 patients. Neurosurgery 2014;75:560-7; discussion 566-7.
Stecker MM. A review of intraoperative monitoring for spinal surgery. Surg Neurol Int 2012;3:S174-87.
] [Full text]
Lopez JR. The use of evoked potentials in intraoperative neurophysiologic monitoring. Phys Med Rehabil Clin N
Husain AM, Wright DR, Stolp BW, Friedman AH, Keifer JC. Neurophysiological Intraoperative monitoring of the glossopharyngeal nerve: Technical case report. Neurosurgery 2008;63:277-8; discussion 278.
Legatt AD, Emerson RG, Epstein CM, MacDonald DB, Deletis V, Bravo RJ, et al
. ACNS Guideline: Transcranial Electrical Stimulation Motor Evoked Potential Monitoring. J Clin Neurophysiol 2016;33:42-50.
Gawande AA, Zinner MJ, Studdert DM, Brennan TA. Analysis of errors reported by surgeons at three teaching hospitals. Surgery 2003;133:614-21.
Awad SS, Fagan SP, Bellows C, Albo D, Green-Rashad B, De la Garza M, et al
. Bridging the communication gap in the operating room with medical team training. Am J Surg 2005;190:770-4.
Escallier KE, Nadelson MR, Zhou D, Avidan MS. Monitoring the brain: processed electroencephalogram and peri-operative outcomes. Anaesthesia 2014;69:899-910.
Shanks AM, Avidan MS, Kheterpal S, Tremper KK, Vandervest JC, Cavanaugh JM, et al
. Alerting thresholds for the prevention of intraoperative awareness with explicit recall: A secondary analysis of the Michigan Awareness Control Study. Eur J Anaesthesiol 2015;32:346-53.
Avila EK, Elder JB, Singh P, Chen X, Bilsky MH. Intraoperative neurophysiologic monitoring and neurologic outcomes in patients with epidural spine tumors. Clin Neurol Neurosurg 2013;115:2147-52.
Ellerkmann RK, Grass A, Hoeft A, Soehle M. The response of the composite variability index to a standardized noxious stimulus during propofol-remifentanil anesthesia. Anesth Analg 2013;116:580-8.
Williams M, Lee JK. Intraoperative blood pressure and cerebral perfusion: Strategies to clarify hemodynamic goals. Paediatr Anaesth 2014;24:657-67.
Bruhn J, Bouillon TW, Radulescu L, Hoeft A, Bertaccini E, Shafer SL. Correlation of approximate entropy, bispectral index, and spectral edge frequency 95 (SEF95) with clinical signs of “anesthetic depth” during coadministration of propofol and remifentanil. Anesthesiology 2003;98:621-7.
Jeleazcov C, Schmidt J, Schmitz B, Becke K, Albrecht S. EEG variables as measures of arousal during propofol anaesthesia for general surgery in children: Rational selection and age dependence. Br J Anaesth 2007;99:845-54.
Blume WT, Sharbrough FW. EEG monitoring during carotid endacrtectomy and open heart surgery. In: Niedermeyer E, Lopes da Silva F, editors. Electroencephlaography: Basic principles, clinical applications and related fields. 2nd
Ed. Balitimore: Urban & Schwarzenberg; 1987. pp 645-56.
La Neve JE, Zitney GP. Use of somatosensory evoked potentials to detect and prevent impending brachial plexus injury during surgical positioning for the treatment of supratentorial pathologies. Neurodiagn J 2014;54:260-73.
Jellish WS, Sherazee G, Patel J, Cunanan R, Steele J, Garibashvilli K, et al
. Somatosensory evoked potentials help prevent positioning-related brachial plexus injury during skull base surgery. Otolaryngol Head Neck Surg 2013;149:168-73.
Lyon R, Feiner J, Lieberman JA. Progressive suppression of motor evoked potentials during general anesthesia: The phenomenon of “anesthetic fade.” J Neurosurg Anesthesiol 2005;17:13-9.
Clark AJ, Ziewacz JE, Safaee M, Lau D, Lyon R, Chou D, et al
. Intraoperative Neuromonitoring With MEPs and Prediction of Postoperative Neurological Deficits in Patients Undergoing Surgery for Cervical and Cervicothoracic Myelopathy. Neurosurg Focus 2013;35:E7.
McCulloch P, Catchpole K. A three-dimensional model of error and safety in surgical health care microsystems. Rationale, development and initial testing. BMC Surg 2011;11:23.
Neily J, Mills PD, Young-Xu Y, Carney BT, West P, Berger DH, et al
. Association Between Implementation of a Medical Team Training Program and Surgical Mortality. JAMA 2010;304:1693-700.
Mazzocco K, Petitti DB, Fong KT, Bonacum D, Brookey J, Graham S, et al
. Surgical team behaviors and patient outcomes. Am J Surg 2009;197:678-85.
Pettker CM, Thung SF, Norwitz ER, et al
. Impact of a comprehensive patient safety strategy on obstetric adverse events. Am J Obstet Gynecol 2009;200:492.e1-8.
[Figure 1], [Figure 2], [Figure 3], [Figure 4]