ABSTRACT
BACKGROUND: The gingival biotype (GB) influences treatment planning and clinical outcomes in several dental specialties. This study aimed to investigate the associations between the GB and various clinical crown and periodontal parameters, such as probing depth (PD), papillary height (PH), keratinized tissue width (KTW), crown width/crown length ratio (CW/CL), and gingival thickness (GT). The secondary objective was to evaluate the optimal cutoff values for all parameters to determine the GB in both the maxillary and mandibular anterior teeth. METHODS: This cross-sectional study included 50 healthy individuals (26 men and 24 women) aged between 20 and 35 years. The GB was determined as a binary variable based on the transparency of a periodontal probe through the buccal gingival margin (TRAN). The clinical crown and periodontal parameters, such as PH, PD, KTW, GT (free gingival thickness [FGT] and attached gingival thickness [AGT]), and the CW/CL ratio were measured. The associations between different variables were evaluated by the chi-square test. Correlations between various clinical parameters and GB were assessed using point-biserial correlation analyses. Receiver operating characteristic (ROC) analysis and the Youden index were used to calculate the optimal cutoff values for the PH, PD, KTW, FGT, AGT, and CW/CL ratio to discriminate GB. The statistical significance level was set at p < 0.05. RESULTS: The mean age of the males was 28.23 ± 2.81 years, while that of the females was 27.08 ± 2.85 years. Thick GB was present in 56% of individuals, and thin GB was present in 44% of individuals. Compared with females, males had a predilection for thick GB compared with females. According to the ROC analysis, the cutoff values to discriminate GB for mandibular anterior teeth were 3.4 mm for PH, 1.96 mm for PD, 4.21 mm for KTW, 0.98 mm for FGT, 0.43 mm for AGT, and 0.91 for the CW/CL ratio. Similarly, the cutoff values for discriminating the GB for maxillary anterior teeth were 4.02 mm for PH, 1.92 mm for PD, 3.89 mm for KTW, 1.02 mm for FGT, 0.42 mm for AGT, and 0.83 for the CW/CL ratio. PH, PD, and FGT showed strong positive correlations with GB, whereas KTW, AGT, and the CW/CL ratio showed weak positive correlation with GB. CONCLUSION: Within the limitations of the present study, a significant association between all clinical crown and periodontal parameters with the GB has been confirmed. FGT for mandibular anterior teeth and PH for the mandibular anterior teeth have emerged as the most reliable measurements to differentiate between thick and thin GB based on ROC analysis. KEY POINTS: All the clinical parameters such as papillary height, probing depth, width of keratinized gingiva, gingival thickness, and crown width/height ratio were significantly associated with gingival biotype. Free gingival thickness for mandibular anterior teeth and papillary height for the maxillary anterior teeth have emerged as the most reliable measurement to differentiate between thick and thin gingival biotypes.
ABSTRACT
INTRODUCTION: The utilization of artificial intelligence (AI) and machine learning (ML) models has brought about a significant transformation in the manner in which periodontists gather information, evaluate associated risks, develop diverse treatment alternatives, anticipate and diagnose dental conditions that compromise periodontal health. The principal objective of this prospective study was to examine periodontists' understanding and acceptance of the application of AI in the realm of periodontology. MATERIALS AND METHODS: This observational study was conducted on 275 participants based on questionnaire using Google Forms. These forms were pre-validated and subsequently circulated among periodontists in Maharashtra via various social media platforms. The study, in its entirety, comprised four open-ended questions on participants' demographics and 14 closed-ended questions, all of which were presented to the participants in English. These questions aimed to elicit participants' awareness, knowledge, attitudes, and perspectives regarding emerging applications of AI in the field of periodontology. To analyze the collected data, researchers employed the widely utilized Statistical Package for Social Sciences (SPSS) version 22.0. RESULT: A 75% response rate was achieved and 68% of the respondents were female. 62% periodontists were aware of AI; however, only 24% were aware of its working principles. Most respondents agreed with the use of AI in periodontal diagnosis; however, they disagreed with the use of AI in predicting clinical attachment loss (69%). 80-82% respondents felt that AI should be a part of postgraduate training and should be implemented in clinical practice. However, most periodontists do not use AI for diagnostic or research purposes. 49% periodontists felt that AI does not have better diagnostic accuracy than periodontists, and therefore cannot replace them in the future. CONCLUSION: Most periodontists possessed a reasonable level of understanding regarding the utilization of AI in the domain of periodontology and expressed a desire to incorporate it into their diagnostic and treatment planning processes for periodontal conditions. Additional endeavors must be undertaken to enhance periodontists' awareness concerning the effective implementation of AI within their professional practice, with the aim of facilitating personalized treatment planning for their respective patients. It is postulated that the integration of AI will augment the likelihood of achieving favorable outcomes within the realm of periodontology.
ABSTRACT
Mutilation of a portion of a face can cause a heavy impact on the self-image and personality of an individual. Acceptable cosmetic results usually can be obtained with a facial prosthesis. This paper describes prosthetic rehabilitation of a 60-year-old male patient having a left ocular defect. A technique to fabricate heat polymerizing polymethyl methacrylate was illustrated. The resultant prosthesis was structurally durable and aesthetically acceptable with satisfactory retention. The importance of meticulous treatment planning to tackle the challenges faced in fabricating an ocular prosthesis is explained with the relevant literature.
