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A craniometry-based predictive model to determine occlusal vertical dimension.

Claudio Morata1, Andrea Pizarro2, Hector Gonzalez3

  • 1Professor, Faculty of Dentistry, Pedro de Valdivia Univerisity, Santiago, Chile.

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Occlusal vertical dimension (OVD) prediction is improved by considering facial type and sex. A new model using left eye-to-ear distance offers a simpler method for determining OVD in clinical practice.

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Area of Science:

  • Dentistry
  • Anthropology
  • Biometrics

Background:

  • Craniometry is used to determine occlusal vertical dimension (OVD).
  • Existing prediction models lack personalization, failing to account for facial type and sex.
  • A single variable normalization approach is insufficient for accurate OVD prediction.

Purpose of the Study:

  • To investigate the influence of sex, facial type, and age on OVD prediction models.
  • To develop a predictive model for OVD using the left or right eye-to-ear distance.
  • To assess the model's applicability in both dentate and edentate individuals.

Main Methods:

  • A cohort of 385 healthy individuals (18-50 years) was classified by sex, age, and facial type.
  • Distances including nose-to-chin and eye-to-ear were measured using a specialized gauge.
  • Statistical analyses, including Pearson correlation and multiple regression, were employed to develop the predictive model.

Main Results:

  • The left eye-to-ear distance showed a stronger correlation with nose-to-chin distance across all facial types.
  • OVD was found to be dependent on sex and facial type, but not age.
  • A predictive equation was formulated: OVD=42.17+(0.46×left eye-to-ear distance)+sex+facial type adjustments.

Conclusions:

  • Occlusal vertical dimension is significantly influenced by sex and facial type.
  • The left eye-to-ear distance provides a reliable craniometric reference for OVD determination.
  • A straightforward mathematical model incorporating these factors offers a baseline for improved OVD prediction.