Background: The postoperative period is crucial for the initiation of healing and prevention of complications after any surgical procedure. Due to factors such as poor compliance, comprehension, and retention of instructions, and other unaccounted factors, the objectives of postoperative care are not always achieved. Therefore, an Android-based mobile health app (ExoDont) was developed to ensure a smooth postoperative period for patients after a dental extraction. The ExoDont app delivers reminders for postoperative instructions and drug intake at defined intervals, thus fostering self-reliance among patients in taking their prescribed dose of medication. Objective: The aim of this study is to design, develop, and validate ExoDont, an innovative app for improved adherence to postoperative instructions after tooth extraction. Methods: A postoperative treatment protocol was developed by a team of oral and maxillofacial surgeons and general dentists, following which the clinical and technological requirements of the app were determined along with the software engineers, graphic designers, and applications architect in the team. ExoDont was developed to provide timely reminders for medication and postoperative care. The app was field tested and validated using the User Version of the Mobile Application Rating Scale. Results: The ExoDont software design was divided into a 3-level architecture comprising a user interface application, logical layer, and database layer. The software architecture consists of an Android-based ExoDont app for patients and a web version of the admin panel. The testing and validation of the ExoDont app revealed that Perceived Impact received the highest mean score of all rated components (mean 4.6, SD 0.5), while Engagement received the lowest mean score (mean 3.5, SD 0.8). Conclusions: The testing and validation of the app support its usability and functionality, as well as its impact on users. The ExoDont app has been designed, keeping the welfare of patients in view, in a user-friendly manner that will help patients adhere to the prescribed drug regimen and ensure easy and efficient dissemination of postoperative instructions. It could play an instrumental role in fostering compliance among patients and significantly decrease the complication rate following dental extractions.

Background: Artificial Intelligence (AI) powered tools have transformed the field of healthcare. A recently launched large language model, ChatGPT has gained significant traction due to its communicative interface and relevance of the responses generated. This tool could be utilized in dentistry for dental education, and possibly as a clinical decision support system. Hence, it is imperative to evaluate the accuracy of the model in relation to the responses generated for dental-related queries. Methods: This multi-centric study involved 27 subject experts from nine dental specialties of various institutions and 2 heads of institutions. A total of 243 questions were formulated and the answers generated by ChatGPT (version: 3.5) were rated in terms of accuracy (6-point Likert), completeness (4-point Likert), and relevance (5-point Likert). Results: The mean accuracy of the ChatGPT-generated answers was 4.61 (SD 1.575), with a median of 5.33. For completeness, mean score was 2.01 (SD 0.793), and the median was 2.33. Regarding relevance, a mean of 3.13 (SD 1.590) and median of 3.67 were obtained. The highest ratings were observed for answers related to Oral Medicine and Radiology, as well as for open-ended questions, and questions labelled as easy in terms of difficulty. Conclusion: The promising results observed in the study promote the application of ChatGPT for retrieving dental information. However, it is crucial to exercise caution and seek advice from a qualified healthcare for dental health-related queries. Further large-scale testing of the model is necessary before incorporating it into dental clinical practice.

Background: Postoperative care is influenced by various factors such as compliance, comprehension, retention of instructions, and other unaccounted elements. It is imperative that patients adhere to the instructions and prescribed regimen for smooth and placid healing. ExoDont, an Android-based mobile health app, was designed to ensure a smooth postoperative period for patients after a dental extraction. Besides providing postoperative instructions at defined intervals, the app also sends drug reminders as an added advantage over other available, conventional methods. Objective: The aim of this study was to compare the compliance rate of individuals with respect to the prescribed regimen and postoperative instructions. Additionally, we aimed to assess any changes in the postoperative complication rate of patients assigned to 3 categories: the verbal, verbal plus written, and ExoDont app-based delivery groups. Methods: We conducted a pilot, nonrandomized, and prospective comparative study in which patients after tooth extraction were assigned to 3 groups—verbal (Group A), verbal plus written (Group B), and ExoDont app-based delivery (Group C)—based on the eligibility criteria, and a 1-week follow-up was planned to obtain the responses regarding compliance and postoperative complications from the participants. Results: In total, 90 patients were recruited and equally divided into 3 groups. Compliance to prescribed drug was found to be the highest in Group C, where of the 30 participants, 25 (83%) and 28 (93%) followed the entire course of antibiotics and analgesics, respectively. For postoperative instructions, higher compliance was observed in Group C in relation to compliance to diet restrictions (P=.001), not rinsing for 24 hours (P<.001), and warm saline rinses after 24 hours (P=.001). However, the difference was not significant for smoking restrictions (P=.07) and avoiding alcohol (P=.16). Moreover, the difference in postoperative complication rate was not statistically significant among the 3 groups (P=.31). Conclusions: As evident from the results, it is anticipated that the ExoDont app will be helpful in circumventing the unaccounted possibilities of missing the prescribed dosage and postoperative instructions and ensuring the smooth recovery of patients after dental extraction. However, future studies are required to establish this app-based method of delivery of postoperative instructions as a viable option in routine clinical practice.

Background. Platelet-rich fibrin (PRF) enhances tissue healing by releasing essential growth factors. Surgical extraction of deeply impacted mandibular third molars poses a common challenge, often leading to significant defects at the distal root of the second molar. This study explored the role of PRF in soft and hard tissue healing after surgical extraction. Methods. This triple-blind, split-mouth, randomized controlled trial involved patients with bilateral impacted mandibular third molars. Single-stage surgical extraction was performed, and PRF was applied at one site while the other served as the control. Plaque index (PI), sulcus bleeding index (SBI), clinical attachment levels (CALs), postoperative pain, edema, tenderness, sensitivity, and bone level were assessed on day 1, day 3, first week, and first, third, and sixth months. Results. Sixty-four (34 males and 30 females) patients were found eligible for assessment. The test group exhibited a significant decrease in mean pain scores compared to controls (P<0.001), notably resolving by one month. Edema scores were significantly lower in the test group at all intervals up to one month (P=0.045). Tenderness showed a significant difference at one week (P=0.001), resolving by three months. No significant hard tissue changes were noted (P=0.825). Conclusion. Significant benefits over postoperative pain, bleeding, tenderness, and initial sensitivity underscored the importance of PRF in soft tissue healing following impacted mandibular third molar extraction. However, no improvement in bone height outlined its limited potential in hard tissue regeneration over exposed root surfaces of the mandibular second molar.