ReviewJournal of anesthesia and translational medicine2026
Intraoperative neurophysiological monitoring (IONM) in neurosurgery: A critical appraisal of established practices, ongoing controversies, and future trajectories.
Review in Journal of anesthesia and translational medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
1 citing paper in PubMed.
- Neurophysiological monitoring of cranial nerves III and VI in endoscopic skull base surgery: scoping review and comparative study.Frontiers in oncology · 2026Article
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Intraoperative neurophysiological monitoring (IONM) has evolved from a novel technique into an evidence-based standard treatment method for high-risk neurosurgical and spinal surgeries. Its effectiveness is based on two interrelated pillars: optimized multimodal monitoring, mainly including motor and somatosensory evoked potentials (MEPs/SSEPs) as well as electromyography (EMG), and total intravenous anesthesia (TIVA) combined with a precise neuromuscular blockade-based anesthesia protocol. IONM significantly reduces neurological function damage during surgeries for spinal deformities, intramedullary tumors, acoustic neuromas, and gliomas in the brain functional area, redefining the standards of safe surgical practice. However, there are still certain challenges, including the difficulty in converting signal changes into clinical actions, controlling high false alarm rates, and overcoming technical/logistical obstacles in complex and lengthy surgeries. These objectively existing problems further highlight the importance of clinical judgment. Looking to the future, a key developmental direction involves transforming intraoperative neurophysiological monitoring (IONM) from a passive monitoring tool into a system capable of predictive guidance and comprehensive neuroprotection. Emerging models include artificial intelligence (AI) technologies for real-time analysis and technologies for fusing multimodal data into surgical "dashboards", but they still face significant obstacles in data quality, clinical validation, and human-centered design. Closed-loop systems and the application of neurobiomarker recognition to achieve neuroprotection remain enduring research topics. In summary, the development of IONM technology towards a more mature direction requires a coordinated planning scheme: establishing evidence-based standards, promoting data-driven discoveries through large-scale collaborative research, and achieving deep multidisciplinary integration within the surgical team. The ultimate goal is to make IONM an intelligent guiding tool that not only monitors but also actively optimizes surgical strategies to ensure the preservation of neural function.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.