Advances in Multimodality Monitoring in Traumatic Brain Injury

The review systematically evaluates the current state of MMM technologies, their clinical applications, and their emerging role in improving TBI management, focusing on real-time physiological data streams that can provide management guidance. Relative to more static modalities such as imaging and biomarkers, the review explicitly scopes itself to real-time physiological data streams commensurate with the onset of sudden events such as seizures, brain hypoxic events, and excursions of cerebral hypertension. This is a narrative review whose evidence base is a synthesis of existing literature rather than new primary data or trial results.

Integrating physiological variables such as intracranial pressure, brain tissue oxygenation, arterial blood pressure, and electroencephalography with artificial intelligence and advanced analytics may enable earlier detection and prediction of adverse events. The review advances MMM from mere multiparameter acquisition to a framework integrated with AI and advanced analytics to support earlier detection and prediction of adverse events. The text uses 'may enable,' framing this as a potential capability based on recent studies rather than an established clinical effect.

Recent studies highlight the potential of MMM to reduce variability in TBI outcomes associated with secondary insults. The review positions the value of MMM in reducing outcome variability caused by secondary insults, rather than merely describing monitoring parameters themselves. The text states that 'Recent studies highlight the potential,' summarizing suggestive findings from recent research.

MMM is emerging as a cornerstone technology to enhance patient phenotyping in TBI, enabling more individualized and timely therapeutic interventions. The review elevates the role of MMM from a research tool to an emerging component of patient phenotyping and individualized therapy in precision neurocritical care. The text uses 'is emerging as,' a judgment about a developmental trend that still requires prospective validation to support clinical adoption.

The review focuses on real-time physiological data streams that can provide management guidance and explicitly does not cover more static modalities such as imaging and biomarkers; its discussion applies to neurocritical care settings for secondary brain injury after TBI, aiming to provide clinicians and researchers with an assessment framework for the current state of MMM technologies, their clinical applications, and the path toward broader clinical adoption.

Readers should still watch: the optimal combination of monitoring modalities is not yet determined, interpretation of complex data streams remains insufficiently mature, and larger harmonized datasets, standardized acquisition and interpretation methods, and prospective validation of multimodal-guided interventions remain open issues; in addition, the loaded text is summary-level content lacking figures and specific study data, which may limit further summarization of technical details and evidence strength.