WoS İndeksli Yayınlar Koleksiyonu

Permanent URI for this collectionhttps://hdl.handle.net/20.500.14627/6

Browse

Search Results

Now showing 1 - 2 of 2
  • Article
    Citation - WoS: 2
    Citation - Scopus: 2
    Twenty-Year Course of Antifungal Resistance in Candida Albicans in Türkiye: A Systematic Review and Meta-Analysis
    (MDPI, 2025) Kilbas, Imdat; Kahraman Kilbas, Elmas Pinar; Horhat, Florin George; Ciftci, Ihsan Hakki
    This study aimed to systematically evaluate the resistance rates of Candida albicans to various antifungals based on studies conducted in Turkiye and published between 2005 and 2025 and to analyze the factors contributing to resistance. A systematic literature search was conducted using various keywords in electronic databases (PubMed, Embase, Web of Science, EBSCO, Scopus, Turk Medline and Google Scholar). A total of 42 studies were included in the meta-analysis according to the determined criteria. The quality of the studies was assessed using the Joanna Briggs Institute checklist, and the analyses were performed using appropriate statistical software. The highest resistance rates for fluconazole, itraconazole, and voriconazole were observed in the Aegean and Marmara regions. In the analyses performed with the random-effects model, heterogeneity was found to be high for itraconazole, fluconazole, posaconazole, voriconazole, and caspofungin, and the strongest explanatory variable of this heterogeneity was the geographical region variable. In our study, we determined that antifungal resistance in C. albicans strains in Turkiye is generally low; however, an increasing trend has been observed over the years, especially in amphotericin B resistance. Although the low resistance rates to major antifungal agents such as fluconazole, voriconazole and echinocandins are promising, regional differences and methodological heterogeneity necessitate the development of treatment strategies based on local data.
  • Review
    Citation - WoS: 101
    Appraising Systematic Reviews: a Comprehensive Guide To Ensuring Validity and Reliability
    (Frontiers Media Sa, 2023) Shaheen, Nour; Shaheen, Ahmed; Ramadan, Alaa; Hefnawy, Mahmoud Tarek; Ramadan, Abdelraouf; Ibrahim, Ismail A.; Flouty, Oliver
    Systematic reviews play a crucial role in evidence-based practices as they consolidate research findings to inform decision-making. However, it is essential to assess the quality of systematic reviews to prevent biased or inaccurate conclusions. This paper underscores the importance of adhering to recognized guidelines, such as the PRISMA statement and Cochrane Handbook. These recommendations advocate for systematic approaches and emphasize the documentation of critical components, including the search strategy and study selection. A thorough evaluation of methodologies, research quality, and overall evidence strength is essential during the appraisal process. Identifying potential sources of bias and review limitations, such as selective reporting or trial heterogeneity, is facilitated by tools like the Cochrane Risk of Bias and the AMSTAR 2 checklist. The assessment of included studies emphasizes formulating clear research questions and employing appropriate search strategies to construct robust reviews. Relevance and bias reduction are ensured through meticulous selection of inclusion and exclusion criteria. Accurate data synthesis, including appropriate data extraction and analysis, is necessary for drawing reliable conclusions. Meta-analysis, a statistical method for aggregating trial findings, improves the precision of treatment impact estimates. Systematic reviews should consider crucial factors such as addressing biases, disclosing conflicts of interest, and acknowledging review and methodological limitations. This paper aims to enhance the reliability of systematic reviews, ultimately improving decision-making in healthcare, public policy, and other domains. It provides academics, practitioners, and policymakers with a comprehensive understanding of the evaluation process, empowering them to make well-informed decisions based on robust data.