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    Analysing YouTube as a health resource: quality and reliability of videos on pediatric appendicitis
    (BMC, 2025) Coşkun, N; Demir, E
    Background This study aims to assess the content, quality, and reliability of YouTube videos related to appendicitis in children. It analyzes the extent to which these videos provide accurate information to parents and healthcare professionals and evaluates their potential contribution to improving the quality of medical education. Methods The keywords appendicitis and appendectomy, along with pediatrics, child, and children, were searched both individually and in all possible combinations. Videos were ranked according to the number of views and the first 60 videos with the highest number of views were included in the analysis. The videos were evaluated by two independent pediatric surgeons using the Global Quality Scale (GQS), Modified DISCERN (mDISCERN) and American Medical Association (JAMA) scales. Video Power Index (VPI) values were calculated for each video to assess popularity. Inter-rater agreement was assessed with intraclass correlation coefficient (ICC), group comparisons with Mann-Whitney U and Kruskal-Wallis tests, and correlations with Spearman's coefficient. Results Of the analyzed videos, 46 (76.7%) were informational, and 14 (23.3%) were surgical. Videos uploaded by hospitals and doctors scored higher on mDISCERN, GQS, and JAMA scales than those by individuals or private channels (P < 0.001). Animation-containing videos had higher views, likes, and VPI scores than non-animated ones (P = 0.015, P = 0.003, P = 0.006). Surgical videos had significantly higher JAMA scores (P = 0.024) and longer durations (P = 0.021). No significant correlation was observed between quality scores and engagement metrics such as views or likes (P > 0.05). Conclusions This study demonstrated that YouTube videos on pediatric appendicitis are generally of low-to-moderate quality, with no significant correlation between content quality and popularity metrics such as view count or likes. Videos by hospitals and doctors were more reliable, while visual elements like animations increased engagement but not content quality. Findings highlight the need for scientifically accurate and informative content by healthcare professionals to better educate patients, families, and medical students. Clinical trial number Not applicable.
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    Artificial intelligence in otorhinolaryngology: current trends and application areas
    (SPRINGER, 2025) Demir, E; Uğurlu, BN; Uğurlu, GA; Aydoğdu, G
    PurposeThis study aims to perform a bibliometric analysis of scientific research on the use of artificial intelligence (AI) in the field of Otorhinolaryngology (ORL), with a specific focus on identifying emerging AI trend topics within this discipline.MethodsA total of 498 articles on AI in ORL, published between 1982 and 2024, were retrieved from the Web of Science database. Various bibliometric techniques, including trend keyword analysis and factor analysis, were applied to analyze the data.ResultsThe most prolific journal was the European Archives of Oto-Rhino-Laryngology (n = 67). The USA (n = 200) and China (n = 61) were the most productive countries in AI-related ORL research. The most productive institutions were Harvard University / Harvard Medical School (n = 71). The leading authors in this field were Lechien JR. (n = 18) and Rameau A. (n = 17). The most frequently used keywords in the AI research were cochlear implant, head and neck cancer, magnetic resonance imaging (MRI), hearing loss, patient education, diagnosis, radiomics, surgery, hearing aids, laryngology ve otitis media. Recent trends in otorhinolaryngology research reflect a dynamic focus, progressing from hearing-related technologies such as hearing aids and cochlear implants in earlier years, to diagnostic innovations like audiometry, psychoacoustics, and narrow band imaging. The emphasis has recently shifted toward advanced applications of MRI, radiomics, and computed tomography (CT) for conditions such as head and neck cancer, chronic rhinosinusitis, laryngology, and otitis media. Additionally, increasing attention has been given to patient education, quality of life, and prognosis, underscoring a holistic approach to diagnosis, surgery, and treatment in otorhinolaryngology.ConclusionAI has significantly impacted the field of ORL, especially in diagnostic imaging and therapeutic planning. With advancements in MRI and CT-based technologies, AI has proven to enhance disease detection and management. The future of AI in ORL suggests a promising path toward improving clinical decision-making, patient care, and healthcare efficiency.
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    Current trends in pain management: A bibliometric analysis for the 1980-to-2023 period
    (LIPPINCOTT WILLIAMS & WILKINS, 2025) Demir, E; Doğan, G; Kiraz, M; Ekici, AA; Kayır, S; Ekici, M; Aydoğdu, G; Doğan, G; Kayır, T
    There is currently no bibliometric analysis available regarding pain management (PM). The aim of this study was to monitor the advancement of the PM research field, demonstrate global productivity, identify the most highly cited studies, delineate collaborations between research areas and countries, and uncover new research topics and intriguing trends. A total of 16,216 articles on the subject of PM published between 1980 and 2023 were downloaded from the Web of Science database and analyzed using various bibliometric analysis methods. Trend keyword analysis, thematic evolution analysis, conceptual structure analysis, factor analysis, citation and co-citation analyses, and international collaboration analyses were conducted. The top 3 most active countries were the United States of America (n = 4021), the United Kingdom (n = 791), and Canada (n = 602). The most prolific author was Christine Miaskowski (n = 47). The most researched topics from the past to the present were chronic pain, opioids, analgesia/analgesics, cancer pain, postoperative pain, low back pain, opioid, cancer, acute pain, and self-management. Factor analysis identified key topics such as analgesia and various types of pain in the central factor, with additional subfactors including low back pain and physiotherapy, nursing, and postoperative anxiety and depression. In recent years, starting in 2020, trending research topics have shifted towards e-health, telemedicine, virtual reality, digital health, mental health, peripheral nerve blocks, erector spinae plane blocks, quadratus lumborum blocks, opioid use disorder, buprenorphine, musculoskeletal pain, COVID-19, cervicalgia, and interprofessional collaboration. In addition to Western countries with major economies in the field of PM (USA, Canada, Australia, and European countries), we identified China, India, and Turkey as research leaders. Our bibliometric analysis of 10,566 articles on PM reveals a significant growth in research, with recent trends focusing on e-health, telemedicine, virtual reality, and peripheral nerve blocks. These emerging technologies and personalized treatment approaches are shaping the future of PM.
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    PAN-Immune inflammation value: a new biomarker for diagnosing appendicitis in children??
    (BMC, 2025) Coşkun, N; Metin, M; Doğan, G; İpek, H; Demir, E; Afşarlar, ÇE
    BackgroundThis study investigates the potential of the pan-immune-inflammation values (PIV) index as a biomarker for diagnosing acute appendicitis in children and compares its performance with other systemic inflammatory markers.MethodsA retrospective analysis of 1,514 pediatric patients aged 0-18 years with abdominal pain admitted between 2019 and 2023 was conducted. Patients were categorized into complicated, non-complicated appendicitis, negative appendectomy, and non-surgical treatment groups. Demographic and laboratory data were recorded, and PIV, Systemic Inflammation Index (SII), Systemic Inflammation Response Index (SIRI), Neutrophil-to-Lymphocyte Ratio (NLR), and Platelet-to-Lymphocyte Ratio (PLR) indices were calculated. Receiver Operating Characteristic (ROC) analysis was used to assess predictive performance, with optimal cut-offs evaluated for sensitivity, specificity, and multiple logistic regression (MLR) analyses.ResultsBased on Area Under the Curve (AUC), C-reactive Protein (CRP), lymphocyte, and PLR showed weak predictive value, while White Blood Cell Count (WBC), neutrophil, monocyte, NLR, SII, SIRI, and PIV demonstrated poor predictive value for appendicitis. Optimal cut-offs were 3.40 for NLR, 134.5 for PLR, 1010.3 for SII, 3.47 for SIRI, and 919.3 for PIV, with sensitivity and specificity values of 78.7%, 47.1% for NLR; 64.7%, 47.5% for PLR; 75.6%, 52% for SII; 71.5%, 57.3% for SIRI; and 72.2%, 54.1% for PIV. In the MLR model, PIV above 919.3 increased appendicitis likelihood 2.67-fold (95% Confidence Interval: 2.16-3.37).ConclusionAlthough PIV demonstrated potential as a novel biomarker for pediatric appendicitis, its diagnostic utility remains limited without supplementary clinical and radiological data. Larger prospective studies are recommended to validate these findings and improve clinical decision-making. PIV may serve as a supplementary tool in diagnosing pediatric appendicitis when used alongside other markers and diagnostic methods.Trial registration'retrospectively registered'.