Examining The Relationship Between Gingival Thickness and Tooth and Gingival Parameters
- Conditions
- Gingival Thickness
- Registration Number
- NCT06369493
- Lead Sponsor
- Ondokuz Mayıs University
- Brief Summary
This study aims to assess whether there is a valid correlation between the identified multiple clinical and morphometric parameters and the gingival thickness.
- Detailed Description
This study focused on the relationship between the clinical parameters of crown and gingival morphology and gingival phenotypes. This study investigated the relationship between clinical and morphological parameters and gingival phenotype and included all teeth up to the first molar. It also compares gingival phenotypes across arch locations and tooth groups.
Study Design and Participants:
This was a cross-sectional, controlled, randomized, and analytical data study.
This cross-sectional study was conducted with 50 participants (21 females, 29 males) aged 18-31 (mean age 22.42 ± 2.87 years) who applied to the Ondokuz Mayis University Faculty of Dentistry's Periodontology Department for periodontal treatment between September 2022 and May 2023. The statistical power of the study based on crown morphology was determined to be 80%, with a type 1 error rate of 0.05, and a sample size of at least 42 people was determined. The study was conducted in accordance with the principles of the Helsinki Declaration and with the approval of the Ondokuz Mayis University Clinical Research Ethics Committee (OMUKAEK-Protocol No:2022/210. All participants provided written informed consent prior to enrollment.
Fifty participants were divided into two groups based on the GT measurement taken from the point corresponding to the base of the gingival sulcus and categorized as thin (GT:≤ 1 mm) and thick (GT: \> 1 mm).
Clinic Measurements
Clinical periodontal parameters, including Plaque Index (PI), Gingival Index (GI), Bleeding on Probing Index (BPI), and probing pocket depth in six regions (mesial labial, midfacial, distal labial, mesial palatal, midpalatal and distal palatal) of each tooth with University of North Carolina (UNC) probe.
To reduce pain before the direct measurement, xylocaine spray (10% lidocaine) was applied. GT was measured by with a 20-gauge endodontic file in the buccal region of the incisors, canines, premolars, and first molars in both the upper and lower jaws, corresponding to the base of the gingival sulcus. After fixing the plastic stopper, the distance between the stopper and the tip of the endodontic file was measured using a modified digital caliper with 0.01 mm precision.
Papilla Length (PL) was determined by measuring the distance between the zenith points of adjacent teeth and the perpendicular line connecting to the apex of the papilla with a periodontal probe. Each tooth position had its mesial PL recorded.
The functional method proposed by Olssoni et al. was used to measure the keratinized gingival width (KGW). KGW was measured to the nearest 0.5 mm from the marginal gingiva\'s mid-buccal position to the mucogingival junction.
Measurements of Dental Stone Models
An alginate impression of the upper and lower jaw was taken in a stock tray and poured in Type 3 hard plaster according to the manufacturer's specifications to obtain the study model. The following assessments were made on the casts using a digital caliper according to the recommendations of Olssoni et al.
Crown length (CL) was determined by measuring the distance between the gingival margin or, if discernible, the cemento-enamel junction and the incisal edge of the crown. the crown.
Crown width (CW) was determined by dividing the length of the crown into three portions of equal-height; cervical (C), middle (M), and incisal (I). The distance between the approximal tooth surfaces was measured at the border between portions C and M.
Following these measurements, the ratio of crown width (CW)/ crown length (CL) was calculated for each tooth.
Using a digital angle gauge with a measurement range of 0-999.9º and a precision of 0.3º, the gingival angle (GA) was calculated by connecting the angle between two lines at the most apical part of the gingival margin of each measured tooth and the most coronal parts of the two adjacent papillae.
Intra-Examiner Repeatability:
All measurements were performed by a single examiner (SY), and intra-examiner reliability was assessed by repeating the GT measurements on 10 randomly selected participants 2 weeks later.
Statistical Analysis
Statistical analyses were performed using a statistical software package. Spearman's Correlation analysis was used to examine the relationship between parameters that did not follow a normal distribution. Binary Logistic Regression Analysis was used to examine the parameters related to gingival thickness. receiver operating characteristic (ROC) analysis was used to determine the cut-off values for parameters in predicting gingival thickness. To assess the consistency of repeated measurements by the researcher, the intraclass correlation coefficient (ICC) was used. Statistical significance level was considered p\< 0.05 Data are expressed as means ± standard deviations and median (minimum-maximum).
The relationship and interaction of clinical and morphometric parameters were recorded on the basis of individuals, tooth groups, and dental arch location.
Recruitment & Eligibility
- Status
- COMPLETED
- Sex
- All
- Target Recruitment
- 50
- Non-smokers ≥18 years old
- Periodontal health with ≤10% bleeding on full mouth probing.
- Participants with no history of systemic diseases or consistent medication use.
- Participants with teeth present in the maxillary and mandibular anterior and posterior regions, with a measured clinical attachment level (CAL) ≤ 3 mm; without buccal attachment loss or gingival inflammation
- Participants with no evidence of dental caries, crown shape alterations, or restorations affecting the occlusal edge in the maxillary and mandibular teeth, and no radiographic evidence of bone loss
- At least one tooth in maxillary and mandibular segments, representing molar and premolar regions
- No tooth loss due to periodontal reasons
- Pregnant or lactating women
- Participants who have received or are receiving orthodontic treatment and using removable dentures or orthodontic devices
- Participants with a history of periodontitis or periodontal surgery involving teeth
- Presence of abrasion or erosion in teeth
Study & Design
- Study Type
- OBSERVATIONAL
- Study Design
- Not specified
- Primary Outcome Measures
Name Time Method Evaluation of the correlation between KGW, CW, CL PH parameters of GT measured in "mm" with a digital caliper with 0.001 mm precision in 1200 teeth in 50 participants using Spearman correlation analysis. 1 month Spearman Correlation Analysis is a statistical technique in evaluating the correlation between clinical and morphometric parameters and is used to evaluate the relationship between variables. Variables GT, KGW, PH, CW, CL in 1200 teeth of 50 participants were measured in "mm" with a digital caliper with a precision of 0.001 mm. Spearman correlation coefficient takes a value between -1 and +1. +1 indicates a perfect positive monotonic relationship, -1 indicates a perfect negative monotonic relationship, and 0 indicates no relationship.
Evaluation of the effect of GT on keratinized gingival width, measured in "mm" by digital caliper with a precision of 0.001 mm, both by binary logistic regression analysis of 50 participants. From September 2022 to May 2023 In this study, GT, KGW are parametric variables and were measured in mm with a digital caliper with a precision of 0.001 mm. Binary logistic regression analysis is a statistical technique used to model the relationship of a dependent variable between two categorical classes. A significant p-value (\<0.05) indicates that the independent variable (GT for this study) has a significant effect in the model. Binary logistic regression analysis expresses the effect of independent variables on the dependent variable in terms of log-odds. The coefficients of the model determine the magnitude and direction of the effect of the independent variables.
Examining the effect of age and gender of 50 participants on the gingival thickness measured in mm using binary logistic regression analysis. 1 month In this study, GT is a parametric variable and is measured in mm. The effect of age and gender on GT of 50 participants over the age of 18 was examined with binary logistic regression analysis. Binary logistic regression analysis is a statistical technique used to model the relationship of a dependent variable between two categorical classes. A significant p value (\<0.05) indicates that the independent variable (GT for this study) has a significant effect in the model. Binary logistic regression analysis expresses the effect of independent variables on the dependent variable in log-odds terms. The coefficients of the model determine the magnitude and direction of the effect of the independent variables.
- Secondary Outcome Measures
Name Time Method
Trial Locations
- Locations (1)
Ondokuz Mayis University Faculty of Dentistry Department of Periodonthology
🇹🇷Samsun, Turkey