Skeletal DysplasiaNCT06002373
Assessment of Artificial Intelligence for Treatment Decision Recommendation of Adult Skeletal Class III Patients
An observational study of Skeletal Dysplasia and Reverse Overjet, run by Cairo University at 1 site in Egypt.
Trial summary
The study titled "Reliability Of Artificial Intelligence for Treatment Decision Recommendation of Adult Skeletal Class III Patients" aims to assess the accuracy and dependability of artificial intelligence (AI) in providing treatment decision recommendations for adult patients with skeletal Class III malocclusion. Read more about this study
- Who is it for?
- Ages 18 years and olderHealthy volunteers can take part
- Conditions the study is for
- Skeletal Dysplasia, Reverse Overjet
- How many people
- 150 participants
- Where
- 1 siteEgypt
- Study dates
- 1 May 2023to Feb 2024
- Phase
- Observational
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 years and older
- All sexes
- Healthy volunteers accepted
- Adult, Older adult
Study population: Adult patients with skeletal Class III malocclusion
Who may be able to join
- Skeletally mature patients with CVMI 6.
- Skeletal class III patients
- No congenital deformity, syndrome, or cleft.
- No previous surgical intervention
- No mandibular transverse functional shift.
- Normal overjet, overbite after completion of treatment.
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- Patients with well finished occlusion.
- Patients who have achieved adequate functional and aesthetic results at the end of their treatment.
- Good quality initial and final lateral cephalometric radiographs.
- No sex predilection.
Who cannot join
- Adolescents and skeletally immature patients.
- Patients with pseudo class III.
- Syndromic patients.
- Patients with facial deformity at the naso-maxillary complex
Trial locations and contacts
1 site in 1 country.
About this study
Official title: Reliability Of Artificial Intelligence for Treatment Decision Recommendation of Adult Skeletal Class III Patients: A Diagnostic Test Accuracy Study
The study titled "Reliability Of Artificial Intelligence for Treatment Decision Recommendation of Adult Skeletal Class III Patients" aims to assess the accuracy and dependability of artificial intelligence (AI) in providing treatment decision recommendations for adult patients with skeletal Class III malocclusion. Skeletal Class III malocclusion is characterized by an underdeveloped upper jaw or an overdeveloped lower jaw, leading to facial and dental irregularities. The study focuses on evaluating whether AI-based recommendations can reliably guide orthodontic treatment planning for this specific patient group.
This diagnostic test accuracy study involves collecting a diverse dataset of adult patients diagnosed with skeletal Class III malocclusion. AI algorithms will be trained on this dataset using various clinical and radiographic parameters to learn patterns and make treatment recommendations. The study will then compare the AI-generated treatment recommendations to those provided by experienced orthodontists.
Read more
Key aspects of the study include:
AI Reliability: The primary objective is to assess how consistently and accurately the AI system can recommend appropriate treatment decisions for adult skeletal Class III patients.
Diagnostic Test Accuracy: The study will determine the sensitivity, specificity, positive predictive value, and negative predictive value of the AI-generated treatment recommendations. This analysis will highlight the AI's ability to correctly identify patients who require specific treatment interventions.
Clinical Validity: Researchers will investigate whether the AI recommendations align with the decisions made by experienced orthodontists. This assessment is crucial to establish the AI system's clinical applicability.
Potential Benefits: If the AI system proves reliable and accurate, it could offer a time-efficient and standardized method for treatment decision support, aiding orthodontists in providing personalized care to adult skeletal Class III patients.
By conducting this study, researchers aim to contribute to the advancement of AI-assisted medical decision-making within the field of orthodontics. Successful outcomes would have the potential to revolutionize treatment planning processes, improve patient outcomes, and provide a valuable tool for orthodontists to make informed treatment decisions for adult skeletal Class III patients
- Conditions
- Skeletal Dysplasia, Reverse Overjet
- Medical subject headings
- Mucopolysaccharidosis IV
What is being measured
The primary outcome is the main question the study is designed to answer.
sensitivity and specificity
the difference in sensitivity and specificity between the treatment decisions taken by the clinicians in comparison to those provided by the artificial intelligence software
Measured: 1 month
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted21 Aug 2023
- Study start1 May 2023
- Primary completionJan 2024 (estimated)
- Study completionFeb 2024 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Skeletal DysplasiaStudies of the same condition, open and under way.
- More trials run by Cairo UniversityThe sponsor's other registered studies.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Cohort
- Time perspective
- Retrospective
- Enrolment
- 150 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Cairo University
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, Maha Abd El-Monem Nasr, Cairo University
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT06002373
- Sponsor's protocol ID
- 8114
- Status last verified
- Aug 2023
- First submitted
- 13 Aug 2023
- Last updated
- 23 Aug 2023
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
Study at a glance
From the registry record, last updated by the sponsor on 23 Aug 2023. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Reliability Of Artificial Intelligence for Treatment Decision Recommendation of Adult Skeletal Class III Patients: A Diagnostic Test Accuracy Study
- ClinicalTrials.gov ID
- NCT06002373
- Acronym / sponsor ID
- 8114
- Conditions
- Skeletal Dysplasia, Reverse Overjet
- Study type
- Observational
- Recruitment status
- Unknown status
- Enrolment
- 150 participants (estimated)
- Lead sponsor
- Cairo UniversityUniversity, hospital or other
- Study start
- 1 May 2023 (actual)
- Primary completion
- Jan 2024 (estimated)
- Study completion
- Feb 2024 (estimated)
- First posted
- 21 Aug 2023 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
The study titled "Reliability Of Artificial Intelligence for Treatment Decision Recommendation of Adult Skeletal Class III Patients" aims to assess the accuracy and dependability of artificial intelligence (AI) in providing treatment decision recommendations for adult patients with skeletal Class III malocclusion. Skeletal Class III malocclusion is characterized by an underdeveloped upper jaw or an overdeveloped lower jaw, leading to facial and dental irregularities. The study focuses on evaluating whether AI-based recommendations can reliably guide orthodontic treatment planning for this specific patient group.
This diagnostic test accuracy study involves collecting a diverse dataset of adult patients diagnosed with skeletal Class III malocclusion. AI algorithms will be trained on this dataset using various clinical and radiographic parameters to learn patterns and make treatment recommendations. The study will then compare the AI-generated treatment recommendations to those provided by experienced orthodontists.
Key aspects of the study include:
AI Reliability: The primary objective is to assess how consistently and accurately the AI system can recommend appropriate treatment decisions for adult skeletal Class III patients.
Diagnostic Test Accuracy: The study will determine the sensitivity, specificity, positive predictive value, and negative predictive value of the AI-generated treatment recommendations. This analysis will highlight the AI's ability to correctly identify patients who require specific treatment interventions.
Clinical Validity: Researchers will investigate whether the AI recommendations align with the decisions made by experienced orthodontists. This assessment is crucial to establish the AI system's clinical applicability.
Potential Benefits: If the AI system proves reliable and accurate, it could offer a time-efficient and standardized method for treatment decision support, aiding orthodontists in providing personalized care to adult skeletal Class III patients.
By conducting this study, researchers aim to contribute to the advancement of AI-assisted medical decision-making within the field of orthodontics. Successful outcomes would have the potential to revolutionize treatment planning processes, improve patient outcomes, and provide a valuable tool for orthodontists to make informed treatment decisions for adult skeletal Class III patients
Study design
- Observational model
- Cohort
- Time perspective
- Retrospective
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Adult, Older adult
- Study population
- Adult patients with skeletal Class III malocclusion
Key inclusion criteria (10 listed)
- Skeletally mature patients with CVMI 6.
- Skeletal class III patients
- No congenital deformity, syndrome, or cleft.
- No previous surgical intervention
- No mandibular transverse functional shift.
Key exclusion criteria (4 listed)
- Adolescents and skeletally immature patients.
- Patients with pseudo class III.
- Syndromic patients.
- Patients with facial deformity at the naso-maxillary complex
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Primary outcome
sensitivity and specificity
Time frame: 1 month
the difference in sensitivity and specificity between the treatment decisions taken by the clinicians in comparison to those provided by the artificial intelligence software
Results and safety
Results are not available in the source record.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 23 Aug 2023.
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Skeletal Dysplasia and Reverse Overjet, run by Cairo University at 1 site in Egypt.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 10 inclusion and 4 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: status not confirmed, as of the sponsor's last update on 23 Aug 2023. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in Egypt. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
Results are not available in the source record.
How can a doctor refer a patient or contact the research team?
Contact Maha AM Swelam, PhD (00201123344551, maha.swelam@gmail.com), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
sensitivity and specificity (time frame: 1 month). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 23 Aug 2023.