The Impact of Topical Application of Platelet-Rich Fibrin on Graft Survival in Surgeries for Chronic Otitis Media.

OBJECTIVE: This study aims to evaluate the efficacy of platelet-rich fibrin (PRF) application in tympanoplasty procedures for patients with chronic otitis media (COM), assessing its influence on graft survival and healing time. METHODS: In this prospective interventional study, conducted between January 2022 and June 2023, 80 patients diagnosed with COM were enrolled and divided into two groups. Group A underwent standard tympanic membrane repair using temporal fascia grafts (TFG), while Group B received TFG with adjunctive PRF application. The patients were observed and assessed over a 20-week postoperative period. RESULTS: The study showed a significant enhancement in graft survival rates in Group B (TFG+PRF), with only one residual perforation compared to seven in Group A (TFG alone) at 20 weeks (p=0.02534). Furthermore, Group B patients experienced faster healing, achieving 97.5% graft integrity at 10 and 20 weeks, in contrast to Group A's 87.5%. CONCLUSION: The application of PRF in tympanoplasty procedures for COM notably enhances graft stability and expedites the healing process. These findings suggest that PRF can be a valuable adjunct in otolaryngological surgeries, offering potential improvements in patient outcomes and surgical efficacy.

Navigating Drug-Induced Adversities: A Python-Based Console Application for Causality Assessment Using the Naranjo Algorithm.

The timely and accurate adverse drug reactions (ADR) assessment is vital for effective patient management and healthcare delivery. The Naranjo Algorithm is a widely recognized tool for determining the probability that a drug induces a given ADR. However, the process can be time-consuming and susceptible to human error. This study introduces a Python-based console application (Python Software Foundation, Wilmington, Delaware, United States) designed to automate the Naranjo Algorithm for ADR causality assessment. The application was developed using Python 3.11.4 on a Windows 11 system (Microsoft Corporation, Redmond, Washington, United States) and compiled in Notepad (Microsoft Corporation), a basic text editor, highlighting its accessibility and ease of use in various settings. User input is solicited for each question in the Naranjo Algorithm, validated for acceptable entries, and subsequently scored. The final score categorizes the reaction into Doubtful, Possible, Probable, or Definite ADR, facilitating rapid clinical decision-making. Preliminary validation shows promising reliability and effectiveness, making it a valuable asset in research and clinical settings for assessment.