The aim of this study was to analyze using an artificial intelligence engine (IA) the influence of the pathophysiological environment (set parametric monitoring data, imaging, biology etc.) of acute spinal cord trauma on spinal pain. This project seeks to establish the principles of a new approach for studying spinal cord injury patients. It does not meet the usual criteria of clinical trials in so far as it does not test on patients the effect of a therapeutic

Objectives

The objectives are multiple:

1. Analyze clinical situation in the pathophysiology of spinal pain.
2. somatosensory evoked potentials analysis (PES) and motors (PEM) on injuries of the spinal cord in the acute phase.
3. Increasing the mass of data integrated from current standards (volume). The reason is not only an imperative of statistical power as in a conventional test but the probability of specific events characterize this type of pathology and the consequences of their management (monitoring and therapeutic).
4. Identify new predictive parameters and monitoring of spinal pain.

5. Design the tools of computer collection, successful storage formats, adaptations of collection tools: This is validation of the technical solution (i.e. IA).

Expected results

This system will allow to record and analyze a large amount of parameters, largely beyond the human resources. Analysis of these data should allow better understanding of the pathophysiology of acute trauma of the spinal cord which is an essential prerequisite to research new therapies. The realization evoked potentials, ever conducted on this patient in the acute phase should also allow the investigators to better understand the mechanisms of evolution of the SCI (Spinal Cord Injury).

Moreover, this model expert system must allow, through the creation of routines, discovering new predictive parameters and monitoring, improving the management of these patients.

This is a completely open system that can be enriched with new parameters as and above all enriching also as and when the inclusion of new cases. It therefore offers a theoretical field of infinite discovery extremely promising.

Inclusion Criteria:

• Patient with acute spinal cord injury between the cord opposite the vertebra C2 and marrow compared to the T12 vertebra.
• neurological lesion classified A, B, C or D according to Frankel classification at the initial examination (Annex 1).
• Patient able to give informed consent

Exclusion Criteria:

There are no exclusion criteria. All patients meeting the inclusion criteria are includable. However, it differs remarkable different situations:

• The clinical neurological assessment of patients may be difficult depending on the context: intubated patients admitted - ventilated multiple trauma.
• Neurological assessment via evoked potentials may be difficult depending on the environment for patient care: need for multiple investigations, resuscitation. Evoked potentials will be installed only after agreement of the healthcare team once the patient is stabilized.
• The patient can refuse to submit to one additional exam is not part of the standard care (i.e. PES / PEM); it will be offered to participate in the study without the completion of this review. It will be in this case a simple use of clinical and laboratory data collected retrospectively anonymized so for scientific purposes.