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NCT06714747

Soft Tissue Prediction in Orthognathic Surgery by Making Anatomically Accurate Virtual Model

Recruiting now Last updated 4 December 2024
What this trial tests

trial in Orthognathic Surgery in 10 participants. Currently enrolling.

Timeline
11 January 2022
Primary endpoint
11 September 2026
11 November 2026

Quick facts

Lead sponsorIRCCS Azienda Ospedaliero-Universitaria di Bologna
StatusRecruiting now
Study typeOBSERVATIONAL
Enrollment10
Start date11 January 2022
Primary completion11 September 2026
Estimated completion11 November 2026
Sites1 location across Italy

Conditions studied

Sponsor

IRCCS Azienda Ospedaliero-Universitaria di Bologna — full company profile →

Who can join

18 and older, any sex, with Orthognathic Surgery. Patients with the condition only — healthy volunteers not accepted.

Sponsor's own description

The role of orthognathic surgery in the correction of dento-skeletal dysmorphies, whether they are Class II or Class III or asymmetries, is to improve both the function and aesthetic appearance of thepatient. Both aspects are equally important to achieve optimal results. When the surgeon plans the surgery, he or she must therefore take into account the effects that bone displacements will have at the level of the soft tissues directly involved in the surgery, such as the maxilla and mandible. Traditionally, such surgery consists of an orthodontic presurgical phase1,2 .

Publications & conference data

No peer-reviewed publications indexed yet for this trial.

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Other recruiting trials for Orthognathic Surgery

Currently open trials in the same condition.

Other IRCCS Azienda Ospedaliero-Universitaria di Bologna trials

Trials by the same sponsor.

Verify against primary sources

Data sources for this page

Drug Landscape aggregates and links these public records for informational use only. Always verify against the primary source before clinical or regulatory decisions. Canonical URL: https://druglandscape.com/trial/NCT06714747.

Primary sources · FDA · ClinicalTrials.gov · EMA · SEC EDGAR · ChEMBL · Wikidata · full sourcing