Study on the link between gum disease and heart problems using artificial intelligence

Machine learning analysis of asymmetric dimethylarginine (ADMA) levels in patients with periodontitis and cardiovascular disease: a cross-sectional study

Status

Active, not recruiting

Phases

Unknown

Study type

Observational

Source

ISRCTN

Registry ID

ISRCTN15877121

Enrollment

140

Registered

2025-09-23

Start date

2024-09-01

Completion date

Unknown

Last updated

2025-10-06

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Periodontitis, cardiovascular disease, endothelial dysfunction, asymmetric dimethylarginine (ADMA) elevation Other

Interventions

This is an observational cross-sectional study with no interventions. Participants undergo a single visit including: 1. Clinical periodontal examination (probing depth, clinical attachment level, blee

Eligibility

Sex/Gender

All

Inclusion criteria

Inclusion criteria: 1. Age 18-75 years 2. Minimum 16 natural teeth present 3. For periodontitis groups: 3.1. =40% sites with CAL =2mm and PD =4mm 3.2. Radiographic evidence of bone loss 3.3. =40% sites with bleeding on probing 4. For CVD groups: 4.1. =50% stenosis of at least one coronary artery (angiographically verified) 4.2. OR history of documented coronary intervention 5. For healthy controls: 5.1. No systemic disease 5.2. =10% sites with bleeding on probing 5.3. No sites with PD =4 mm 6. Ability to provide informed consent 7. Willing to complete all study procedures

Exclusion criteria

Exclusion criteria: 1. Antibiotic or anti-inflammatory medication within 3 months prior to enrollment 2. Pregnancy or lactation 3. Uncontrolled diabetes (HbA1c >7.5%) 4. Current smoking >10 cigarettes/day 5. Systemic conditions affecting periodontal health (e.g., immunosuppression) 6. Active cancer treatment 7. Chronic kidney disease (eGFR <30 ml/min/1.73m²) 8. Periodontal treatment within 6 months 9. Unable to provide informed consent 10. Severe cognitive impairment 11. Active substance abuse 12. Participation in other clinical studies within 30 days

Design outcomes

Primary

Measure	Time frame
Serum ADMA levels as a biomarker of endothelial dysfunction measured using high-performance liquid chromatography (HPLC) at baseline (single assessment)	—

Secondary

Measure	Time frame
1. Periodontal parameters (probing depth, clinical attachment level, bleeding on probing, plaque index) measured using UNC-15 probe at baseline (single assessment) 2. Inflammatory markers (hs-CRP, IL-6, TNF-a) measured using ELISA at baseline (single assessment) 3. Machine learning algorithm accuracy for ADMA prediction based on clinical parameters, assessed at study completion	—

Countries

Italy

Contacts

Public ContactFrancesco Inchingolo

francesco.inchingolo@policlinico.bari.it+39 (0)80 559 1111

Outcome results

None listed

Source: ISRCTN (via WHO ICTRP) · Data processed: Feb 4, 2026