Multimodal Monitoring Results Around Delayed Cerebral Infarction After Aneurysmal Subarachnoid Hemorrhage
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Background– Delayed cerebral ischemia following aneurysmal subarachnoid hemorrhage is a major cause of secondary brain injury, with progression to infarction occurring in a subset of patients. Although multimodal neuromonitoring provides continuous physiological data, biomarkers characterizing the transition from delayed cerebral ischemia to infarction remain insufficiently defined. Methods– In this prospective single-center study, 69 patients with aneurysmal subarachnoid hemorrhage (2014–2020) underwent invasive neuromonitoring. Twenty-four patients developed delayed cerebral ischemia–related infarction, while 45 served as controls. Monitoring included brain tissue oxygenation, cerebral microdialysis, intracranial pressure, and pressure reactivity index assessment. Temporal dynamics of physiological parameters surrounding infarct detection were analyzed using generalized additive models. A Random Forest classifier evaluated multimodal biomarker patterns across a 73-hour window encompassing infarct detection. Results– Distinct metabolic disturbances preceded infarction development. Glutamate concentrations increased markedly beginning approximately 48 h before infarct detection, consistent with excitotoxic injury. Glycerol levels rose persistently after infarct detection, indicating membrane breakdown. Pressure reactivity index deteriorated after infarction, while brain tissue oxygenation increased post-detection. The Random Forest model demonstrated good discriminative performance (area under the curve 0.814), with temporal glutamate patterns contributing most to feature importance. Averaged biomarker trends outperformed instantaneous measurements. Conclusions– Multimodal neuromonitoring reveals characteristic physiological patterns associated with delayed cerebral ischemia–related infarction. Integration of metabolic, oxygenation, and cerebrovascular reactivity markers enhances characterization of infarction development, warranting validation in larger cohorts. This study was retrospectively registered with the German Clinical Trials Registry(DRKS00030505) on the third of January 2023.
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Acknowledgements: We thank Marek Czosnyka, Emeritus Professor at Cambridge University and founder of the Brain Physics Laboratory, for his valuable and insightful input.
Funder: Universitätsklinikum RWTH Aachen (8915)
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1868-601X

