A Decision Support System Based on Classification Algorithms for the Diagnosis of Periodontal Disease

NCT06071338 | Unknown DMC

• 1 other identifier: H-06-B-091
• Study Type: observational
• Target: 250
• Locations: 0 countries
• Sites: N/A

Brief 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. 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

Keywords

periodontal; disease; diagnosis; machine; learning; Saudi

Outcome Measures

Primary Outcomes (19)

• Age

  \<30, 30-34, 35-39, 40-44, 45-49, 50-54, 55-59, 60-64, 65-69, 70-74, 75-79, \>80

  One time measure; baseline during periodontal clinical examination.

• Gender

  Male; Female.

  One time measure; baseline during periodontal clinical examination.

• Marital statue

  Married, widowed, divorced, never married

  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

  One time measure; baseline during periodontal clinical examination.

• Physical Activities

  Light, Moderate, Heavy

  One time measure; baseline during periodontal clinical examination.

• Bleeding on Probing

  Yes; No

  One time measure; baseline during periodontal clinical examination.

• Gingival Index

  Percentage

  One time measure; baseline during periodontal clinical examination.

• Plaque Index

  Percentage

  One time measure; baseline during periodontal clinical examination.

• Periodontal Probing Depth

  PPD at the site of greatest loss (number)

  One time measure; baseline during periodontal clinical examination.

• Recession Type

  Yes; No

  One time measure; baseline during periodontal clinical examination.

• Clinical Attachment Loss

  CAL at the site of greatest loss (number)

  One time measure; baseline during periodontal clinical examination.

• Radiographic Bone Loss

  RBL at the site of greatest loss (percentage)

  One time measure; baseline during periodontal clinical examination.

• Tooth Mobility

  Yes; No

  One time measure; baseline during periodontal clinical examination.

• Missing Teeth

  Yes; No

  One time measure; baseline during periodontal clinical examination.

• Furcation Involvement

  Yes; No

  One time measure; baseline during periodontal clinical examination.

• Diabetes

  Healthy, \<7% HbA1c, ≥7% HbA1c

  One time measure; baseline during periodontal clinical examination.

• Smoking

  None, \<10 cig/day, ≥10cig/day

  One time measure; baseline during periodontal clinical examination.

• Body Mass Index

  Underweight, Healthy, Overweight, Obese

  One time measure; baseline during periodontal clinical examination.

• Cardiovascular Disease

  Yes; No

  One time measure; baseline during periodontal clinical examination.

Interventions

Clinical Periodontal Examination DIAGNOSTIC_TEST

No details will be published from the clinical assessment.

Also known as: orthopantomography Assessment

Eligibility Criteria

• Age: 18 Years+
• Sex: all
• Healthy Volunteers: Yes
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Probability Sample

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.

You may qualify if:

• age 18 or more
• no periodontal treatment has been done at least 6 months prior to the enrollment
• seeking periodontal treatment

You may not qualify if:

• refuse to volunteer in the study

Sponsors & Collaborators

• Ministry of Health, Saudi Arabia: lead

Related Publications (2)

• 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.

  PMID: 25772929 RESULT

• Alqahtani 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.

  PMID: 36777017 RESULT

MeSH Terms

Conditions

Periodontal Diseases; Disease

Condition Hierarchy (Ancestors)

Mouth Diseases; Stomatognathic Diseases; Pathologic Processes; Pathological Conditions, Signs and Symptoms

Study Officials

• Abdulrahman Al Shehri, BDS, MS

  General Directorate of Health Affairs, Aseer Region, KSA.

  PRINCIPAL INVESTIGATOR

Central Study Contacts

Abdulrahman Al Shehri, BSD, MS

CONTACT

+966507090251; alshehriabdulrahman3@gmail.com

Abdulrahman Al Shehri, BDS, MS

CONTACT

+966507090251; alshehriabdulrahman3@gmail.com

Study Design

• Study Type: observational
• Observational Model: OTHER
• Time Perspective: CROSS SECTIONAL
• Target Duration: 1 Month
• Sponsor Type: OTHER GOV
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Principal Investigator/Clinical Specialist

Study Record Dates

• First Submitted: September 22, 2023
• First Posted: October 6, 2023
• Study Start: October 1, 2023
• Primary Completion: December 30, 2024
• Study Completion: December 30, 2024
• Last Updated: October 6, 2023

Record last verified: 2023-10

Data Sharing

• IPD Sharing: Will not share