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vol.14 issue3SPINAL CORD TRAUMA PATIENTS TREATED IN A TERTIARY HOSPITAL IN PALMAS, BRAZILTREATMENT OF THORACOLUMBAR BURST FRACTURES FIXED WITH INTERMEDIATE PINS BY THE POSTERIOR APPROACH author indexsubject indexarticles search
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Coluna/Columna

Print version ISSN 1808-1851On-line version ISSN 2177-014X

Abstract

ONO, Allan Hiroshi de Araujo et al. SUBAXIAL CERVICAL FRACTURE: APPLICATION AND CORRELATION OF AO AND SLIC. Coluna/Columna [online]. 2015, vol.14, n.3, pp.218-222. ISSN 2177-014X.  https://doi.org/10.1590/S1808-185120151403114135.

Objective:

To evaluate the AO/Magerl classification and the SLIC (Subaxial Cervical Spine Injury Classification), used in the cervical spine fractures and assess whether they are correlated to the neurological severity of patients, the choice of approach to be used, de duration of surgery an between themselves.

Method:

Retrospective analysis of medical records and radiological image files of 77 patients surgically treated of subaxial cervical fracture or dislocation from August 2010 to September 2012.

Results:

The SLIC classification showed a strong correlation with neurological deficit and Pearson correlation value of -0.600. The AO classification was not correlated with the Frankel scale and the value of Pearson was 0.06 with a statistical significance of 0.682 (p<0.05), that is, unable to determine or suggest the severity of the deficit. When compared to each other the two classifications showed statistical correlation and the value of Pearson was 0.282 with a significance value of 0.022 (p<0.05).

Conclusion:

Among the most used classifications, the SLIC has been able to statistically define the need for surgical treatment and the severity of the neurological status, but was unable to predict the approach or the time of the surgery; the classification AO failed to predict the severity of neurological injury, surgical time, and did not help to choose the approach, just being a morphological classification.

Keywords : Spinal fracture; Cervical vertebrae; Classification; Arthrodesis; Statistics, nonparametric.

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