[Equilibrium and orthognathodontic surgery: correlations in a group of patients undergoing treatment]

Minerva Stomatol. 2000 Oct;49(10):455-61.
[Article in Italian]

Abstract

Background: The aim of this study was to evaluate the main parameters provided by the static stabilometric test (mean X, mean Y, mean velocity, length of tracing, standard deviation of velocity, ellipse area) in the follow-up of patients suffering from skeletal occlusive pathology undergoing orthognathodontic surgery to confirm the re-establishment of postural equilibrium.

Methods: Fifteen patients with skeletal dysgnathia were correlated with a group of 10 healthy subjects. The same parameters were analysed in the dysgnathic subjects at 6 and 12 months after surgical correction. The patients enrolled in this study underwent surgery at the Division of Maxillofacial surgery of Turin University. Student's "t"-test and multivariate statistical analysis (Cox regression) were used for the statistical analysis of results.

Results: A significant variability was noted in some of the main parameters analysed (mean X, mean Y, tracing length) between the two populations (healthy and dysgnathic) compared to visual signs (eyes opened-closed). The change in stabilometric values within the group of dysgnathic patients was highly significant 6 and 12 months after surgery, not only in terms of visual signs but also the cervical component (retroflexion of the head), above all the value of mean Y (p = 0.001).

Conclusions: An analysis of these results shows that static stabilometry can be a valuable aid both during the preoperative evaluation and during the follow-up in patients undergoing jaw surgery since it can quantify the improvement of body balance.

Publication types

  • English Abstract

MeSH terms

  • Adolescent
  • Adult
  • Female
  • Follow-Up Studies
  • Humans
  • Male
  • Malocclusion, Angle Class II / surgery*
  • Malocclusion, Angle Class III / surgery*
  • Patient Selection
  • Postural Balance / physiology*
  • Posture / physiology
  • Proportional Hazards Models
  • Regression Analysis