Metabolic profile of injured human spinal cord determined using surface microdialysis

Abstract

The management of patients having traumatic spinal cord injury would benefit from understanding and monitoring of spinal cord metabolic states. We hypothesized that the metabolism of the injured spinal cord could be visualized using Kohonen self-organizing maps. Sixteen patients with acute, severe spinal cord injuries were studied. Starting within 72 h of the injury, and for up to a week, we monitored the injury site hourly for tissue glucose, lactate, pyruvate, glutamate, and glycerol using microdialysis as well as intraspinal pressure and spinal cord perfusion pressure. A Kohonen map, which is an unsupervised, self-organizing topology-preserving neural network, was used to analyze 3366 h of monitoring data. We first visualized the different spinal cord metabolic states. Our data show that the injured cord assumes one or more of four metabolic states. On the basis of their metabolite profiles, we termed these states near-normal, ischemic, hypermetabolic, and distal. We then visualized how patients’ intraspinal pressure and spinal cord perfusion pressure affect spinal cord metabolism. This revealed that for more than 60% of the time, spinal cord metabolism is patient-specific; periods of high intraspinal pressure or low perfusion pressure are not associated with specific spinal cord metabolic patterns. Finally, we determined relationships between spinal cord metabolism and neurological status. Patients with complete deficits have shorter periods of near-normal spinal cord metabolic states (7 ± 4% vs. 58 ± 12%, p < 0.01, mean ± standard error) and more variable injury site metabolic responses (metabolism spread in 70 ± 11 vs. 40 ± 6 hexagons, p < 0.05), compared with patients who have incomplete neurological deficits. We conclude that Kohonen maps allow us to visualize the metabolic responses of the injured spinal cord and may thus aid us in treating patients with acute spinal cord injuries. (Figure presented.).