Background/Objectives: Intraoperative neurophysiological monitoring (IONM) is used to detect, reduce, and prevent neurological injury during extramedullary spinal cord tumor (EMSCT) resection. This meta-analysis aims to systematically assess the performance of IONM modalities, somatosensory evoked potentials (SSEPs), transcranial motor evoked potentials (TcMEPs), and multimodal approaches in EMSCT surgery, with a particular focus on determining whether a single monitoring modality is sufficient to predict postoperative neurological deficits.
Methods: Following PRISMA-DTA guidelines, we searched MEDLINE, PubMed, and Ovid (inception to April 2025) for studies on IONM in EMSCT surgeries (PROSPERO: CRD420251047345). Pooled sensitivity, specificity, and reversibility metrics were calculated using bivariate models, with quality assessed via QUADAS-2. Z-test and Bayesian meta-analysis were used for comparisons.
Results: Across 20 studies (2,672 patients), multimodal IONM showed a log DOR of 4.310 (95% CI: 3.581–5.039) and an AUC of 94.2%, TcMEP monitoring showed a log DOR of 4.457 (95% CI: 3.775–5.139) and an AUC of 92%, while SSEP monitoring showed a log DOR of 3.463 (95% CI: 2.702–4.224) and an AUC of 82%. All modalities demonstrated high specificity (>95%), indicating low false-positive rates. Bayesian analysis revealed >90% probability that TcMEP-based approaches were superior to SSEPs. Reversible TcMEP changes were associated with an 11% (95% CI: 4–24%) postoperative deficit rate, compared to 35% (95% CI: 12–67%) for SSEPs.
Conclusions:
These findings caution against relying solely on SSEPs and support the use of multimodal IONM strategies, which enhance the early detection of impending neurological injury, enable timely surgical interventions, and help prevent permanent neurological damage in EMSCT resections. Although TcMEP and multimodal monitoring showed similar diagnostic accuracy, we continue to recommend multimodal approaches as the current standard of care, pending prospective studies to determine if TcMEP alone can reliably replace multimodal monitoring.