Factors Associated With Inadequate Intraoperative Baseline Lower Extremity Somatosensory Evoked Potentials

Intraoperative somatosensory evoked potential (SEP) monitoring: an updated position statement by the American Society of Neurophysiological Monitoring

Somatosensory evoked potentials (SEPs) are used to assess the functional status of somatosensory pathways during surgical procedures and can help protect patients' neurological integrity intraoperatively. This is a position statement on intraoperative SEP monitoring from the American Society of Neurophysiological Monitoring (ASNM) and updates prior ASNM position statements on SEPs from the years 2005 and 2010. This position statement is endorsed by ASNM and serves as an educational service to the neurophysiological community on the recommended use of SEPs as a neurophysiological monitoring tool. It presents the rationale for SEP utilization and its clinical applications. It also covers the relevant anatomy, technical methodology for setup and signal acquisition, signal interpretation, anesthesia and physiological considerations, and documentation and credentialing requirements to optimize SEP monitoring to aid in protecting the nervous system during surgery.

Feasibility of multimodal intraoperative neurophysiological monitoring for extramedullary spinal cord tumor surgery in elderly patients

BACKGROUND/PURPOSE

Extramedullary spinal cord tumors (EMSCTs) are mostly benign tumors which are increasingly diagnosed and operatively treated in the elderly. While there are hints that multimodal intraoperative neurophysiological monitoring (IONM) could be influenced by age and age-related comorbidities, no study has ever systematically evaluated its feasibility and value for EMSCT surgery in elderly patients.

METHODS

We retrospectively evaluated all patients with microsurgical EMSCT resection under continuous multimodal IONM with SSEPs, MEPs and electromyography between 2016 and 2020. Epidemiological, clinical, imaging and operative/IONM records as well as detailed individual outcomes were analyzed and compared for the cohort < / ≥ 65 years.

RESULTS

Mean age was 45 years in cohort < 65 years (n = 109) and 76 years in cohort ≥ 65 years (n = 64), while baseline/operative characteristics did not significantly differ. Mean baseline SSEPs' latencies (left-right average) were significantly higher in the cohort ≥ 65 years for both median (20.9 ms vs. 22.1 ms; p < 0.01) and tibial nerve (42.9 ms vs. 46.1 ms; p < 0.01) without significant differences for SSEPs' amplitudes. Stimulation intensity to elicit intraoperative MEPs was significantly higher in the cohort ≥ 65 years (surrogate-marker: left-right-averaged quotient ID1-muscle/abductor-hallucis-muscle; 1.6 vs. 2.1; p < 0.001). Intraoperatively, SSEP and MEP monitoring were feasible in 99%/100% and 99%/98% for the cohort < / ≥ 65 years without significant differences in rates for significant IONM changes during surgery or postoperatively new sensorimotor deficits. Sensitivity of IONM was 29%/43%, specificity 99%/98%, positive and negative predictive values 67%/75% and 95%/93% for the cohort < / ≥ 65 years. Overall, age was no risk factor for IONM feasibility or rate of significant IONM changes.

DISCUSSION

Multimodal IONM is feasible/reliable for EMSCT surgery in elderly patients. An age-related prolongation of SSEPs' latencies and demand for higher stimulation intensities for MEPs' elicitation has to be considered.

Patient Factors Impacting Baseline Motor Evoked Potentials (MEPs) in Patients Undergoing Cervical Spine Surgery for Myelopathy or Radiculopathy

STUDY DESIGN

Retrospective review of 2532 adults who underwent elective surgery for cervical radiculopathy or myelopathy with intraoperative neuromonitoring (IONM) with motor evoked potentials (MEPs) between 2017 and 2019.

OBJECTIVE

Evaluate attainability of monitorable MEPs across demographic, health history, and patient-reported outcomes measure (PROM) factors.

SUMMARY OF BACKGROUND DATA

When baseline IONM responses cannot be obtained, the value of IONM on mitigating the risk of postoperative deficits is marginalized and a clinical decision to proceed must be made based, in part, on the differential diagnosis of the unmonitorable MEPs. Despite known associations with baseline MEPs and anesthetic regimen or preoperative motor strength, little is known regarding associations with other patient factors.

METHODS

Demographics, health history, and PROM data were collected preoperatively. MEP baseline responses were reported as monitorable or unmonitorable at incision. Multivariable logistic regression estimated the odds of having at least one unmonitorable MEP from demographic and health history factors.

RESULTS

Age [odds ratio (OR)=1.031, P <0.001], sex (male OR=1.572, P =0.007), a primary diagnosis of myelopathy (OR=1.493, P =0.021), peripheral vascular disease (OR=2.830, P =0.009), type II diabetes (OR=1.658, P =0.005), and hypertension (OR=1.406, P =0.040) were each associated with increased odds of unmonitorable MEPs from one or more muscles; a history of thyroid disorder was inversely related (OR=0.583, P =0.027). P atients with unmonitorable MEPs reported less neck-associated disability and pain ( P <0.036), but worse SF-12 physical health and lower extremity (LE) and upper extremity function ( P <0.016). Compared with radiculopathy, unmonitorable MEPs in myelopathy patients more often involved LE muscles. Cord function was monitorable in 99.1% of myelopathic patients with no reported LE dysfunction and no history of hypertension or diabetes.

CONCLUSION

Myelopathy, hypertension, peripheral vascular disease, diabetes, and/or symptomatic LE dysfunction increased the odds of having unmonitorable baseline MEPs. Unmonitorable baseline MEPs was uncommon in patients without significant LE weakness, even in the presence of myelopathy.

Natural language processing for automated surveillance of intraoperative neuromonitoring in spine surgery

We sought to develop natural language processing (NLP) methods for automated detection and characterization of neuromonitoring documentation from free-text operative reports in patients undergoing spine surgery. We included 13,718 patients who received spine surgery at two tertiary academic medical centers between December 2000 - December 2020. We first validated a rule-based NLP method for identifying operative reports containing neuromonitoring documentation, comparing performance to standard administrative codes. We then trained a deep learning model in a subset of 993 patients to characterize neuromonitoring documentation and identify events indicating change in status or difficulty establishing baseline signals. Performance of the deep learning model was compared to gold-standard manual chart review. In our patient population, 3,606 (26.3%) patients had neuromonitoring documentation identified using NLP. Our NLP method identified notes containing neuromonitoring documentation with an F1-score of 1.0, surpassing performance of standard administrative codes which had an F1-score of 0.64. In the subset of 993 patients used for training, validation, and testing a deep learning model, the prevalence of change in status was 6.5% and difficulty establishing neuromonitoring baseline signals was 6.6%. The deep learning model had an F1-score = 0.80 and AUC-ROC = 1.0 for identifying change in status, and an F1-score = 0.80 and AUC-ROC = 0.97 for identifying difficulty establishing baseline signals. Compared to gold standard manual chart review, our methodology has greater efficiency for identifying infrequent yet important types of neuromonitoring documentation. This method may facilitate large-scale quality improvement initiatives that require timely analysis of a large volume of EHRs.

Neurophysiological Intraoperative Monitoring in the Elderly

INTRODUCTION

Intraoperative neurophysiological monitoring (IONM) is widely used to prevent nervous system injury during surgeries in elderly patients. However, there are no studies that describe the characteristics and changes in neurophysiological tests during the IONM of patients aged 60 years and older. The study aims to describe and compare IONM changes during surgeries in adult patients aged 18 to 59 years with those aged 60 years and older.

METHODS

We performed a comparative retrospective study of patients aged 18 to 59 years versus those 60 aged years and older who underwent IONM during 2013 to 2018 in Mexico City. Sociodemographic characteristics were recorded and compared. Intraoperative neurophysiological monitoring techniques, their changes, and surgical procedures for both groups were analyzed and compared using descriptive statistics, Mann-Whitney U, Fisher, and χ2 tests. The sensitivity, specificity, and positive and negative predictive values were calculated.

RESULTS

In total, 195 patients were analyzed: 104 patients, 68.63 ± 6.54 years old (elderly group) and 91 patients, 42.3 ± 10.5 years old (younger group). No differences were found in the rates of signal change during IONM between the group of elderly patients and the younger group. The sensitivity, specificity, and positive and negative predictive values were 80%, 99%, 80%, and 99%, respectively.

CONCLUSIONS

Elderly patients have a similar rate of changes in IONM signals compared with younger patients during heterogeneous surgeries guided by IONM.

Success Rate of Obtaining Baseline Somatosensory and Motor Evoked Potentials in 695 Consecutive Cranial and Spine Surgeries

PURPOSE

Intraoperative neurophysiological monitoring has been well documented as an adjunctive technique that significantly decreases the risk of developing inadvertent sensory and motor deficits during cranial and spine surgeries. The ability to detect neurologic problems intraoperatively depends largely on accurately identifying changes that occur in somatosensory evoked potentials (SSEPs) and motor evoked potentials (MEPs) during each procedure. Therefore, obtaining accurate and reproducible SSEP and MEP data during the initial setup is paramount for intraoperative monitoring. In 2007, Chen et al. found the overall success rate for establishing reliable MEP responses to be 94.8% in the upper extremities and 66.6% in the lower extremities. Since then, the success rate of obtaining baseline sensory and motor evoked potential responses has not been specifically reevaluated. The main goal of this study was to evaluate the current success rates of obtaining adequate SSEP and MEP baseline data in the current era, as well as take a closer look into some of the factors that can reduce the success rates.

METHODS

Somatosensory evoked potential and MEP monitoring was attempted in a total of 695 consecutive brain and spine surgeries performed by neurosurgeons and orthopedic surgeons between January 2010 and July 2011. Somatosensory evoked potential and MEP baseline data were obtained after initiation of general anesthesia and before skin incision. The primary measure is the ability to obtain adequate SSEP and MEP baseline in each extremity. A secondary measure was to stratify the success rate based on preoperative diagnosis.

RESULTS

Six hundred ninety-five consecutive cranial and spinal cases that required intraoperative monitoring were reviewed. Baseline upper extremity SSEPs were successfully obtained in 679 cases (98.1%), and baseline lower extremity SSEPs were successfully obtained in 626 cases (90.1%). However, if the preoperative diagnosis was in the category spine trauma or spine infection, the success rate of obtaining adequate baseline in the lower extremities dropped to around 60% for both SSEPs and MEPs.

CONCLUSIONS

The success rates of obtaining adequate baseline SSEP and MEP data are overall higher than previously reported. Preoperative diagnosis like spinal infection or trauma may predict lower success rates for acquiring adequate baseline SSEPs and MEPs.

Neuroanesthesiology Update

This review provides a summary of the literature pertaining to the perioperative care of neurosurgical patients and patients with neurological diseases. General topics addressed in this review include general neurosurgical considerations, stroke, traumatic brain injury, neuromonitoring, neurotoxicity, and perioperative disorders of cognitive function.