1. What data in particular will be shared?
   Response - Individual participant data that underlie the results reported in this article, after de-identification (text, tables, figures, and appendices).
   


2. What additional supporting information will be shared?
   Response -  Study Protocol
   Response -  Statistical Analysis Plan
   Response - Clinical Study Report
   Response -  Analytic Code
   
   
3. Who will be able to view these files?
   Response - Researchers whose proposed use of the data has been approved by an independent review committee identified for this purpose.
   


4. For what types of analyses will this data be available?
   Response - For individual participant data meta-analysis.
   


5. By what mechanism will data be made available?
   Response - Proposals should be directed to [anubhasingh08031997@gmail.com].
   


6. For how long will this data be available start date provided 02-01-1970 and end date provided 02-01-1970?
   Response - Immediately following publication. No end date.
   


7. Any URL or additional information regarding plan/policy for sharing IPD? 
   Additional Information - NIL

The periodontium consists of tissues that support the dentition, including the gingiva, periodontal ligament, and alveolar bone. Periodontal health relies on maintaining host-microbe homeostasis, which is disrupted in diabetes mellitus, leading to accelerated periodontal destruction and impaired wound healing. The initial step in periodontal disease treatment involves professional cleaning through scaling and root planing (SRP) to remove supra- and subgingival plaque and calculus, followed by evaluation. Various therapeutic approaches have been suggested to enhance SRP outcomes and minimize surgical interventions. Advanced Platelet-Rich Fibrin (A-PRF) has shown promising potential in wound healing and tissue regeneration through the sustained release of growth factors. The fibrin structure in A-PRF, characterized by thick fibers, branch points, porosity, and permeability, enhances wound stabilization. This randomized split-mouth study will evaluate the efficacy of A-PRF as an adjunct to SRP in diabetic patients, with test sites receiving A-PRF while control sites undergo SRP alone.

The study aims to compare the effectiveness of A-PRF in conjunction with SRP in Type II diabetic patients with periodontitis. The objectives include assessing the effectiveness of A-PRF combined with SRP, evaluating SRP alone, and comparing the outcomes of both treatments. Inclusion criteria include patients aged 30-60 years with Type II diabetes and diagnosed with stage III periodontitis (5-7mm probing pocket depth and attachment loss). Patients must require periodontal treatment for at least two single-rooted teeth in different quadrants and have periodontal destruction at two non-adjacent interproximal sites. Exclusion criteria include pregnancy, smoking, systemic diseases, medications affecting wound healing, recent periodontal treatment, and a history of radiotherapy or chemotherapy. The study follows a randomized split-mouth design with 50 test and 50 control teeth. The sample size is calculated as 110, considering a 10% attrition rate, with a 95% confidence level and pooled standard deviation estimates of 0.66 (Group I) and 0.54 (Group II).

The methodology includes fabricating acrylic stents, conducting blood tests, preparing A-PRF, and documenting periodontal clinical parameters such as the Gingival Index, probing pocket depth (PPD), and clinical attachment level (CAL) using a UNC-15 probe and acrylic stent for standardization. A Visual Analogue Scale (VAS) will be recorded for pain assessment. All patients will undergo full-mouth SRP, with test sites receiving subgingival A-PRF and both test and control sites covered with COE-PAK periodontal dressing. Periodontal assessments will be conducted at 1 week, 3 months, and 6 months. Data will be analyzed using SPSS version 22.0, with ANOVA and Independent ’t’ tests used for group comparisons. A p-value of <0.05 will be considered statistically significant, and Karl Pearson correlation will assess relationships between variables.