Publications by authors named "S Ayilavarapu"
Background: There is limited evidence on the effect of osseodensification drilling (OD) on alveolar ridge dimension changes and implant stability compared to standard drilling (SD). The purpose of this study was to compare the effect of both drilling protocols on ridge dimensional changes and implant stability.
Methods: Fifteen patients were recruited for a total of 20 pairs of implants.
Using precision periodontal health care chart (PPHCC) to improve periodontal health.
Clin Oral Investig
September 2024
Objectives: Developing a Precision Periodontal Health Care Chart (PPHCC) in the electronic dental record (EDR) system and evaluating its clinical usability and effects on clinical outcomes.
Materials And Methods: A survey with ten questions based on the System Usability Scale (SUS) and six questions about assessing clinical impact was used to evaluate the satisfaction of periodontitis patients and care providers with PPHCC before and after non-surgical periodontal therapy (NSPT). The clinical outcomes, including probing depth (PD), interdental clinical attachment loss (CAL), and bleeding on probing (BOP), in patients who used PPHCC (PC) were compared to those in patients without using PPHCC (control).
Aim: This randomized controlled trial aimed to investigate the efficacy of soft-tissue augmentation (STA) with a subepithelial connective tissue graft (SCTG) or an acellular dermal matrix (ADM) on reducing tissue alterations at an immediate implant site.
Materials And Methods: This trial had three groups: (i) immediate implant with SCTG (ICT group); (ii) immediate implant with ADM (IAD group); (iii) immediate implant without STA (control group). Forty-six patients were randomly assigned to each group.
Article Synopsis
- Deep machine learning can significantly streamline the process of calculating radiographic bone loss (RBL), making it easier to diagnose and plan treatment for periodontitis.
- In a study involving 236 patients, a multitasking InceptionV3 model achieved an accuracy of 87% in classifying RBL, with solid performance metrics such as sensitivity and specificity around 86-88%.
- The study concludes that while the results are promising, increasing the amount of clinical data will improve the model's performance and enhance its clinical utility.
Background: In 2017, the American Academy of Periodontology and the European Federation of Periodontology updated the classification of periodontal and peri-implant diseases and conditions. The goal of the present crossover study was to develop straightforward, illustrative flowcharts and determine their impact on the accuracy and speed of diagnosing periodontal conditions by predoctoral dental students (DS) and dental hygiene students (DHS).
Methods: Two flowcharts (a decision-tree flowchart and one based on the periodontal disease/condition entity) were developed using updated diagnostic determinants proposed by the 2017 classification.