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Clinical Research Directory

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5 clinical studies listed.

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Class I Malocclusion

Tundra lists 5 Class I Malocclusion clinical trials. Each listing includes eligibility criteria, study locations, and direct links to research sites in the Tundra directory.

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NOT YET RECRUITING

NCT07521267

Nano Coated Orthodontic Miniscrews for en Mass Retraction of the Upper Arch

study will be directed to evaluate silver-hydroxyapatite nano-coated versus uncoated orthodontic miniscrews for en masse retraction of the upper anterior segment.

Gender: All

Ages: 14 Years - 20 Years

Updated: 2026-04-09

1 state

Class I Malocclusion
Maxillary Prognathism
Orthodontic Tooth Movement
NOT YET RECRUITING

NCT07466641

LLLLT vs Piezocision in Accelerating Orthodontic Canine Retraction

This comparative controlled clinical study aims to evaluate and compare the effectiveness of piezocision and low-level laser therapy (LLLT) as adjunctive interventions to accelerate orthodontic canine retraction. Participants will be randomly assigned to one of three groups: piezocision, LLLT, or a control group (no adjunctive procedure). The study will assess the impact of these interventions on the rate of tooth movement, the type of tooth movement, and patient experience.

Gender: All

Ages: 18 Years - 25 Years

Updated: 2026-03-12

1 state

Malocclusion, Angle Class II, Division 1
Bimaxillary Protrusion
Class I Malocclusion
NOT YET RECRUITING

NCT07350343

The Predictability of Directly Printed Versus Thermoformed Clear Aligners

The study is randomized controlled trial ...The null hypothesis suggests that there is no significant difference between actual and predicted dental movement in patients treated using direct printed aligners produced with Graphy™ Tera Harz TA-28 resin as compared to those treated with thermoformed clear aligner therapy.

Gender: All

Ages: 16 Years - 40 Years

Updated: 2026-01-20

Class I Malocclusion
Crowded Teeth
Spacing of Anterior Teeth
+1
RECRUITING

NCT07162753

Assesment of Ethnic Bias in an Artificial Intelligence Based Orthodontic Diagnosis System

This study explores how artificial intelligence (AI) can be used in orthodontics, which is the area of dentistry that focuses on correcting jaw and bite problems. AI is a computer technology that can learn from large amounts of data and then make predictions or decisions. It is already being tested in medicine and dentistry to help doctors and dentists diagnose conditions. For this study, the AI system was trained using photographs and X-rays from patients in Turkey. The system learned to recognize specific orthodontic skeletal malocclusions. After the training stage, the AI was tested in two groups: one group included Turkish patients whose records were not used in training, and the other group included patients from different ethnic backgrounds who were treated at a clinic in Belgium. This design allows researchers to see if the AI works equally well for people of different backgrounds. Only photographs and X-rays taken before orthodontic treatment are used in the study, and all data are anonymized so that no personal information is shared. The images must meet certain quality standards. For example the head must be in natural position, with no beards, scars, or previous orthodontic treatment that might affect the image. Patients who do not meet these criteria are not included. The AI program analyzes the profile photographs, prepares them for evaluation by adjusting and standardizing the images, and then tries to decide each patient has which malocclusion. The results from Turkish patients and patients from other ethnic groups are compared to see if the system makes fair and accurate decisions for everyone. The purpose of this study is not to test a new treatment, but to understand how well AI can recognize orthodontic problems in different populations. This information is important because AI systems are increasingly being used in healthcare, and they need to be fair and accurate for all patients, not just those from one group. By participating, patients help researchers learn whether AI in orthodontics is reliable across diverse communities. This knowledge can guide future improvements in AI technology, ensuring that it supports orthodontists in providing safe, equal, and effective care for everyone.

Gender: All

Ages: 4 Years - Any

Updated: 2025-12-05

1 state

Class I Malocclusion
Class II Div 1 Malocclusion
Class II Division 2 Malocclusion
+1
RECRUITING

NCT06652230

Assessment of Treatment Efficacy Using Smile Arc Marginal Ridge Approach Versus MBT Chart Method for Bracket Positioning

The goal of this randomized clinical trial is to evaluate the effect of Smile Arc Marginal Ridge Approach (SAMRA) versus MBT chart method for bracket positioning on orthodontic treatment results. The main questions it aims to answer are: Is there a difference in orthodontic treatment results between smile arc marginal ridge approach (SAMRA) and MBT chart method for bracket positioning? Does SAMRA provide more accurate orthodontic results and reduce the number of archwire bendings and brackets repositioning needed during finishing? The investigators will compare Smile Arc Marginal Ridge Approach (SAMRA) with MBT Chart Method (gold standard) to see if SAMRA provides more accurate orthodontic results and reduce the need for archwire bendings and brackets repositioning during finishing. Participants will: * Undergo orthodontic treatment and divided into two groups, Group A (SAMRA) and Group B (MBT Chart Method). * 0.018-inch MBT brackets will be used in both groups. * Follow ups every 1 month will take place to change the archwires after becoming passive. * After leveling and alignment is completed, orthodontic treatment results, number of archwire bendings and brackets repositioning needed will be determined to see which type of intervention is better or if both provide similar results.

Gender: All

Ages: 11 Years - 30 Years

Updated: 2024-10-22

1 state

Class I Malocclusion