Periodontal Furcation Lesions
Conditions
Brief summary
This randomized controlled clinical trial aims to determine which biomaterial combination yields superior clinical and tomographic outcomes in the treatment of mandibular class II furcation defects. In addition, modifications of gingival phenotype in the furcation area will be assessed.
Interventions
PROCEDURESurgical procedure using different types of biomaterials
Compared the results of using different combinations of NovaBone and allograft with a microderm or collagen membranes aiming to decrease or close the furcation lesion.
Sponsors
Lake Erie College of Osteopathic Medicine
Osteogenics Biomedical
Study design
Allocation
RANDOMIZED
Intervention model
PARALLEL
Primary purpose
TREATMENT
Masking
TRIPLE (Subject, Investigator, Outcomes Assessor)
Eligibility
Sex/Gender
ALL
Age
18 Years to No maximum
Healthy volunteers
No
Inclusion criteria
* Adults diagnosed with Stage III or Stage IV periodontitis presenting with at least one mandibular molar with a Class II furcation defect requiring regenerative surgical treatment. * Ability and willingness to provide written informed consent. * Medically stable and able to undergo periodontal surgery. * Willingness to comply with all study procedures and follow-up visits.
Exclusion criteria
* Stage I or Stage II periodontitis. * Current smokers. * Uncontrolled diabetes mellitus. * Alcohol or substance use disorder. * Chronic inflammatory diseases requiring continuous anti-inflammatory therapy. * Current use of bisphosphonates or other medications associated with medication-related osteonecrosis of the jaw. * Current use of medications known to induce gingival enlargement. * Continuous use of systemic antibiotics or anti-inflammatory medications. * Pregnant or breastfeeding individuals. * Known allergy or hypersensitivity to the antibiotics, local anesthetics, or other study-related medications. * Medical conditions that, in the investigator's judgment, make the participant unsuitable for periodontal surgery or study participation.
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Horizontal Bone Gain (HBG). | 6 months | Cone-beam computed tomography (CBCT) measurements will be obtained at baseline and 6 months from the buccal or lingual bone edge to the deepest bone defect, measured horizontally. Sites will be classified as buccal or lingual and analyzed at the site level, first pooled and then separately. Change scores (6 months-baseline) will be assessed using the Shapiro-Wilk test. Within-group changes will be analyzed with paired t-tests or Wilcoxon signed-rank tests, as appropriate. Between-group comparisons of baseline values and 6-month changes will be performed using one-way ANOVA with Tukey's HSD or Kruskal-Wallis with Dunn's test (Holm adjustment). To account for multiple sites per participant, primary bone outcomes will be analyzed using linear mixed-effects models or generalized estimating equations when required. Statistical significance will be set at P\<0.05. Analyses will be performed in Python 3 (pandas, SciPy, statsmodels). |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Improvement of the Gingival Phenotype | 6 months | Measurements will be obtained at baseline and 6 months using combined cone-beam computed tomography (CBCT) and oral scan images to determine gingival tissue width 2 mm apical to the gingival margin. Sites will be classified as buccal or lingual and analyzed at the site level, first pooled and then separately. Change scores (6 months-baseline) will be assessed using the Shapiro-Wilk test. Within-group changes will be analyzed with paired t-tests or Wilcoxon signed-rank tests, as appropriate. Between-group comparisons of baseline values and 6-month changes will be performed using one-way ANOVA with Tukey's HSD or Kruskal-Wallis with Dunn's test (Holm adjustment). To account for multiple sites per participant, outcomes will be analyzed using linear mixed-effects models or generalized estimating equations when required. Statistical significance will be set at P\<0.05. Analyses will be performed in Python 3 (pandas, SciPy, statsmodels). |
Countries
United States
Outcome results
None listed