Periodontal DiseasesNCT06071338
A Decision Support System Based on Classification Algorithms for the Diagnosis of Periodontal Disease
An observational study of Periodontal Diseases, run by Ministry of Health, Saudi Arabia.
Trial summary
The study purposes For periodontal applications, such as diagnosing gingivitis and periodontal disease, artificial intelligence (AI) models have been developed; however, their accuracy and technological maturity are to be evolved. Read more about this study
- Who is it for?
- Ages 18 years and olderHealthy volunteers can take part
- Conditions the study is for
- Periodontal Diseases
- What is being tested?
- Clinical Periodontal Examination
- How many people
- 250 participants
- Where
- No sites listed yet
- Study dates
- 1 Oct 2023to 30 Dec 2024
- How long will I take part?
- 1 Month
- 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: Data will be collected randomly during the study period planned to end by the end of the year 2023. Data will be collected from participants attending the periodontal department at Abha Specialized Dental Center seeking periodontal treatment.
Who may be able to join
- age 18 or more
- no periodontal treatment has been done at least 6 months prior to the enrollment
- seeking periodontal treatment
Who cannot join
- refuse to volunteer in the study
Trial locations and contacts
No sites are listed yet.
About this study
The study purposes For periodontal applications, such as diagnosing gingivitis and periodontal disease, artificial intelligence (AI) models have been developed; however, their accuracy and technological maturity are to be evolved. The applications of such technologies in the field of periodontics are walking baby steps worldwide. The Kingdom of Saudi Arabia is moving fast in technology adoption and implementation in different sectors. However, the healthcare sector, especially clinical-related, needs original research applied to Saudi subjects. The literature in the field of machine learning applications in dentistry is limited. Although AI models for periodontology applications are still being developed, they could serve as potent diagnostic instruments. The current study was planned to add to the current gap in the literature.
Read the detailed description
A cross-sectional study design will be applied. Two hundred fifty patients will be evaluated by an experienced periodontist and used as input variables. The final diagnosis output will be generated by considering relevant information from the patient's medical history, clinical dental examination, and radiographic exam. Of the sample of 250 patients, 20% of the participants will be assigned randomly to the test group, while the rest will be assigned to the training group before feeding it to the algorithms.
The study purposes For periodontal applications, such as diagnosing gingivitis and periodontal disease, artificial intelligence (AI) models have been developed; however, their accuracy and technological maturity are to be evolved. The applications of such technologies in the field of periodontics are walking baby steps worldwide. The Kingdom of Saudi Arabia is moving fast in technology adoption and implementation in different sectors. However, the healthcare sector, especially clinical-related, needs original research applied to Saudi subjects. The literature in the field of machine learning applications in dentistry is limited. Although AI models for periodontology applications are still being developed, they could serve as potent diagnostic instruments. The current study was planned to add to the current gap in the literature.
- Conditions
- Periodontal Diseases
- Being tested
- Clinical Periodontal Examination
- Keywords
- periodontal, disease, diagnosis, machine, learning, Saudi
- Medical subject headings
- Periodontal Diseases, Disease
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Clinical Periodontal ExaminationDiagnostic test
Also called orthopantomography Assessment
No details will be published from the clinical assessment.
What is being measured
The primary outcome is the main question the study is designed to answer.
Age
<30, 30-34, 35-39, 40-44, 45-49, 50-54, 55-59, 60-64, 65-69, 70-74, 75-79, >80
Measured: One time measure; baseline during periodontal clinical examination.
Gender
Male; Female.
Measured: One time measure; baseline during periodontal clinical examination.
Marital statue
Married, widowed, divorced, never married
Measured: One time measure; baseline during periodontal clinical examination.
Education
< secondary school, secondary school, graduate or equivalent, some college or associates degree, College graduate or higher
Measured: One time measure; baseline during periodontal clinical examination.
Physical Activities
Light, Moderate, Heavy
Measured: One time measure; baseline during periodontal clinical examination.
Bleeding on Probing
Yes; No
Measured: One time measure; baseline during periodontal clinical examination.
Gingival Index
Percentage
Measured: One time measure; baseline during periodontal clinical examination.
Plaque Index
Percentage
Measured: One time measure; baseline during periodontal clinical examination.
Periodontal Probing Depth
PPD at the site of greatest loss (number)
Measured: One time measure; baseline during periodontal clinical examination.
Recession Type
Yes; No
Measured: One time measure; baseline during periodontal clinical examination.
Clinical Attachment Loss
CAL at the site of greatest loss (number)
Measured: One time measure; baseline during periodontal clinical examination.
Radiographic Bone Loss
RBL at the site of greatest loss (percentage)
Measured: One time measure; baseline during periodontal clinical examination.
Tooth Mobility
Yes; No
Measured: One time measure; baseline during periodontal clinical examination.
Missing Teeth
Yes; No
Measured: One time measure; baseline during periodontal clinical examination.
Furcation Involvement
Yes; No
Measured: One time measure; baseline during periodontal clinical examination.
Diabetes
Healthy, <7% HbA1c,
≥7% HbA1c
Measured: One time measure; baseline during periodontal clinical examination.
Smoking
None, <10 cig/day, ≥10cig/day
Measured: One time measure; baseline during periodontal clinical examination.
Body Mass Index
Underweight, Healthy, Overweight, Obese
Measured: One time measure; baseline during periodontal clinical examination.
Cardiovascular Disease
Yes; No
Measured: One time measure; baseline during periodontal clinical examination.
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted6 Oct 2023
- Study start1 Oct 2023 (estimated)
- Primary completion30 Dec 2024 (estimated)
- Study completion30 Dec 2024 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (2)Papers the sponsor has linked to this study.
- Other trials for Periodontal DiseasesStudies of the same condition, open and under way.
- 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
- Other
- Time perspective
- Cross-sectional
- Enrolment
- 250 participants (estimated)
- Target duration
- 1 Month
Sponsor and investigators
- Lead sponsor
- Ministry of Health, Saudi Arabia
- Sponsor type
- Other government
- Responsible party
- Principal investigator, Abdulrahman Alshehri, Ministry of Health, Saudi Arabia
- Investigators
- Abdulrahman Al Shehri, BDS, MS, Principal investigator, General Directorate of Health Affairs, Aseer Region, KSA.
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT06071338
- Sponsor's protocol ID
- H-06-B-091
- Status last verified
- Oct 2023
- First submitted
- 22 Sep 2023
- Last updated
- 6 Oct 2023
- Results posted
- No
- Data monitoring committee
- Yes
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No: No intention and no need to share individual patient data with research community.
Publications
Ozden FO, Ozgonenel O, Ozden B, Aydogdu A. Diagnosis of periodontal diseases using different classification algorithms: a preliminary study. Niger J Clin Pract. 2015 May-Jun;18(3):416-21. doi: 10.4103/1119-3077.151785.
PubMed 25772929Alqahtani HM, Koroukian SM, Stange K, Schiltz NK, Bissada NF. Identifying Factors Associated with Periodontal Disease Using Machine Learning. J Int Soc Prev Community Dent. 2022 Dec 30;12(6):612-622. doi: 10.4103/jispcd.JISPCD_188_22. eCollection 2022 Nov-Dec.
PubMed 36777017
Study at a glance
From the registry record, last updated by the sponsor on 6 Oct 2023. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- A Decision Support System Based on Classification Algorithms for the Diagnosis of Periodontal Disease
- ClinicalTrials.gov ID
- NCT06071338
- Acronym / sponsor ID
- H-06-B-091
- Conditions
- Periodontal Diseases
- Keywords
- periodontal, disease, diagnosis, machine, learning, Saudi
- Study type
- Observational
- Recruitment status
- Unknown status
- Enrolment
- 250 participants (estimated)
- Lead sponsor
- Ministry of Health, Saudi ArabiaOther government
- Study start
- 1 Oct 2023 (estimated)
- Primary completion
- 30 Dec 2024 (estimated)
- Study completion
- 30 Dec 2024 (estimated)
- First posted
- 6 Oct 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 purposes For periodontal applications, such as diagnosing gingivitis and periodontal disease, artificial intelligence (AI) models have been developed; however, their accuracy and technological maturity are to be evolved. The applications of such technologies in the field of periodontics are walking baby steps worldwide. The Kingdom of Saudi Arabia is moving fast in technology adoption and implementation in different sectors. However, the healthcare sector, especially clinical-related, needs original research applied to Saudi subjects. The literature in the field of machine learning applications in dentistry is limited. Although AI models for periodontology applications are still being developed, they could serve as potent diagnostic instruments. The current study was planned to add to the current gap in the literature.
Detailed description
A cross-sectional study design will be applied. Two hundred fifty patients will be evaluated by an experienced periodontist and used as input variables. The final diagnosis output will be generated by considering relevant information from the patient's medical history, clinical dental examination, and radiographic exam. Of the sample of 250 patients, 20% of the participants will be assigned randomly to the test group, while the rest will be assigned to the training group before feeding it to the algorithms.
The study purposes For periodontal applications, such as diagnosing gingivitis and periodontal disease, artificial intelligence (AI) models have been developed; however, their accuracy and technological maturity are to be evolved. The applications of such technologies in the field of periodontics are walking baby steps worldwide. The Kingdom of Saudi Arabia is moving fast in technology adoption and implementation in different sectors. However, the healthcare sector, especially clinical-related, needs original research applied to Saudi subjects. The literature in the field of machine learning applications in dentistry is limited. Although AI models for periodontology applications are still being developed, they could serve as potent diagnostic instruments. The current study was planned to add to the current gap in the literature.
Study design
- Observational model
- Other
- Time perspective
- Cross-sectional
- Target follow-up
- 1 Month
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Adult, Older adult
- Study population
- Data will be collected randomly during the study period planned to end by the end of the year 2023. Data will be collected from participants attending the periodontal department at Abha Specialized Dental Center seeking periodontal treatment.
Key inclusion criteria (3 listed)
- age 18 or more
- no periodontal treatment has been done at least 6 months prior to the enrollment
- seeking periodontal treatment
Key exclusion criteria (1 listed)
- refuse to volunteer in the study
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| Clinical Periodontal ExaminationAlso: orthopantomography AssessmentNo details will be published from the clinical assessment. | Diagnostic test | – |
Primary outcome
Age
Time frame: One time measure; baseline during periodontal clinical examination.
<30, 30-34, 35-39, 40-44, 45-49, 50-54, 55-59, 60-64, 65-69, 70-74, 75-79, >80
Gender
Time frame: One time measure; baseline during periodontal clinical examination.
Male; Female.
Marital statue
Time frame: One time measure; baseline during periodontal clinical examination.
Married, widowed, divorced, never married
Education
Time frame: One time measure; baseline during periodontal clinical examination.
< secondary school, secondary school, graduate or equivalent, some college or associates degree, College graduate or higher
Physical Activities
Time frame: One time measure; baseline during periodontal clinical examination.
Light, Moderate, Heavy
Bleeding on Probing
Time frame: One time measure; baseline during periodontal clinical examination.
Yes; No
Gingival Index
Time frame: One time measure; baseline during periodontal clinical examination.
Percentage
Plaque Index
Time frame: One time measure; baseline during periodontal clinical examination.
Percentage
Periodontal Probing Depth
Time frame: One time measure; baseline during periodontal clinical examination.
PPD at the site of greatest loss (number)
Recession Type
Time frame: One time measure; baseline during periodontal clinical examination.
Yes; No
Clinical Attachment Loss
Time frame: One time measure; baseline during periodontal clinical examination.
CAL at the site of greatest loss (number)
Radiographic Bone Loss
Time frame: One time measure; baseline during periodontal clinical examination.
RBL at the site of greatest loss (percentage)
Tooth Mobility
Time frame: One time measure; baseline during periodontal clinical examination.
Yes; No
Missing Teeth
Time frame: One time measure; baseline during periodontal clinical examination.
Yes; No
Furcation Involvement
Time frame: One time measure; baseline during periodontal clinical examination.
Yes; No
Diabetes
Time frame: One time measure; baseline during periodontal clinical examination.
Healthy, <7% HbA1c, ≥7% HbA1c
Smoking
Time frame: One time measure; baseline during periodontal clinical examination.
None, <10 cig/day, ≥10cig/day
Body Mass Index
Time frame: One time measure; baseline during periodontal clinical examination.
Underweight, Healthy, Overweight, Obese
Cardiovascular Disease
Time frame: One time measure; baseline during periodontal clinical examination.
Yes; No
Results and safety
Results are not available in the source record.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 6 Oct 2023.
- Results publication: PubMed 25772929Ozden FO, Ozgonenel O, Ozden B, Aydogdu A. Diagnosis of periodontal diseases using different classification algorithms: a preliminary study. Niger J Clin Pract. 2015 May-Jun;18(3):416-21. doi: 10.4103/1119-3077.151785.
- Results publication: PubMed 36777017Alqahtani HM, Koroukian SM, Stange K, Schiltz NK, Bissada NF. Identifying Factors Associated with Periodontal Disease Using Machine Learning. J Int Soc Prev Community Dent. 2022 Dec 30;12(6):612-622. doi: 10.4103/jispcd.JISPCD_188_22. eCollection 2022 Nov-Dec.
- Individual participant dataSharing planned: No. No intention and no need to share individual patient data with research community.
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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.
Abdulrahman Al Shehri, BDS, MS principal investigator
General Directorate of Health Affairs, Aseer Region, KSA.
Questions about this trial
What is this clinical trial studying?
An observational study of Periodontal Diseases, run by Ministry of Health, Saudi Arabia.
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 3 inclusion and 1 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 6 Oct 2023. Status can change between updates, so confirm with the study contact before making plans.
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 Abdulrahman Al Shehri, BSD, MS (+966507090251, alshehriabdulrahman3@gmail.com), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Age (time frame: One time measure; baseline during periodontal clinical examination.). The study lists 19 primary outcomes in all. It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT06071338, which also lists 2 linked publications.
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 6 Oct 2023.