Background: Inflammatory markers association with many diseases is the subject of many articles and reviews. This study presents a comprehensive bibliometric review and visualization analysis of inflammatory biomarkers (IB) in the context of febrile seizure (FS) patients. Methods: The study focused on IB in FS using (1) bibliometric analysis specific indicators and maps in order to analyze and present the network of authors, journals, universities, and countries, and (2) automated literature screening and unsupervised clustering approach for filtering and topic cluster identification. Results: We conducted a literature mining search on FS research, specifically IB in the context of FS, using the automated tools VOSviewer and Bibliometrix. Indices of the inflammatory response (in the context of febrile seizures) identified by the literature mining are (pro/anti-inflammatory) cytokines, such as interleukin IL-1β, IL-6, IL-8, I-10, IL-22, tumor necrosis factor (TNF-α), neutrophil-to-lymphocyte ratio (NLR), mean platelet volume (MPV), platelet count (PLT), and red blood cell distribution width (RDW). The resulted bibliometric maps and topic clusters offer a comprehensive overview, the status and leading trends on existing research of inflammatory biomarkers in FS. Conclusion: The analysis using bibliometrics and review with graphical presentations can be useful in investigating and (better) understanding the relationship between FS and IB.

The literature on the COVID-19 landscape has rapidly expanded in the pandemic period. The current study undertakes a bibliometric analysis of research in the topic of the clinical and laboratory characteristics of pediatric COVID-19 cases. Our aim is to perform a comprehensive bibliometric review of current research trends and patterns of this research domain. Publications retrieved from the Web of Science Core Collection and VOSviewer were used for analysis and network visualization. We analyzed geographical distribution and temporal trends, collaboration and citation patterns of authors, institutions, and countries, and core research themes from co-occurrence of keywords and terms. The analysis showed that contributions in the research field were from 302 publications, 1104 institutions, 62 countries, and 172 journals. Many publications were authored by American and Chinese authors, and many were published in the Pediatric Infectious Disease Journal, Pediatric Pulmonology, and Frontiers in Pediatrics. The top cited and co-cited journals were the New England Journal of Medicine, Nature, JAMA, Lancet Infectious Diseases, and BMJ. The network visualization maps of keywords and terms offered a global overview of the clinical and laboratory characteristics of pediatric COVID-19 patients. The bibliometric profile of the researched domain, based on analyzing a large collection of publications/data, could (i) enrich the researchers and non-researchers understanding of the field existing patterns and trends, and (ii) be useful in clinical practice (diagnostic and management) and public health policy.

The characteristics, dynamics and mechanisms/determinants of the immune response to SARS-CoV-2 infection are not fully understood. We performed a bibliometric review of studies that have assessed SARS-CoV-2 antibody responses in the pediatric population using Web of Science online databases, VOSviewer and Bibliometrix tools. The analysis was conducted on 84 publications, from 310 institutions located in 29 countries and published in 57 journals. The results showed the collaboration of scientists and organizations, international research interactions and summarized the findings on (i) the measured titers of antibodies (total antibody and/or individual antibody classes IgG, IgM, IgA) against different antigens (C-terminal region of N (N CT), full-length N protein (N FL), RBD, RBD Alpha, RBD Beta, RBD Gamma, RBD Delta, spike (S), S1, S2) in the case of different clinical forms of the disease; and (ii) the correlations between SARS-CoV-2 antibodies and cytokines, chemokines, neutrophils, C-reactive protein, ferritin, and the erythrocyte sedimentation rate. The presented study offers insights regarding research directions to be explored in the studied field and may provide a starting point for future research.

Background: Teledentistry constitutes a key component of digital health, enabling remote oral healthcare delivery through information and communication technologies (ICT). The COVID-19 pandemic accelerated its global adoption; however, data regarding its implementation within Romanian dental practice remain limited. Understanding usage patterns, perceived benefits, and implementation barriers is essential for effective integration. Objectives: This study examined the adoption of teledentistry among dental practitioners in Sibiu County, Romania, identified its main applications, assessed professional perceptions, and explored barriers and their interrelations using association rule mining (ARM). Methods: A cross-sectional online survey was distributed in 2025 to all 630 registered dentists in Sibiu County. The questionnaire collected demographic data, usage patterns, perceived benefits, and barriers. A total of 197 valid responses were obtained (response rate: 31.2%). Descriptive statistics, Chi-square tests, and ARM were used to identify associations between usage contexts and recorded obstacles. Results: Overall, 44.6% of respondents reported using teledentistry tools, primarily for interdisciplinary consultations (29.4%), postoperative counseling (26.4%), and treatment monitoring (25.3%). The most frequently cited barriers were the inability to perform direct clinical examinations (71.5%), practitioner reluctance (37.1%), insufficient infrastructure (29.9%), and the lack of a clear legislative framework (27.4%). ARM revealed frequent co-occurrence patterns among these barriers. Practitioners with prior experience in teledentistry reported significantly higher perceived utility (58% vs. 22.1%) and greater interest in training (58% vs. 38.5%, p < 0.05). Conclusions: Teledentistry shows moderate but increasing adoption among Romanian dentists. Addressing current barriers, through legislative clarification, infrastructure development, targeted professional training, and public education, is essential for achieving sustainable integration into modern dental practice.

Background: The associations between inflammatory markers and many diseases have been the subject of many articles and reviews. This study presents a comprehensive bibliometric, review and visualization analysis of inflammatory biomarkers (IB) in the context of febrile seizure (FS) patients. Methods: The study focused on the IB in FS using (1) bibliometric analysis-specific indicators and maps in order to analyze and present the network of authors, journals, universities and countries, (2) automated literature screening and unsupervised clustering approach for filtering and topic cluster identification. Results: We conducted a literature mining search on FS research, specifically IB in the context of FS, using automated tool VOSViewer. The presentation and discussions on the resulted bibliometric maps and topic clusters offer a comprehensive overview, status and leading trends in existing research on inflammatory biomarkers in FS. Conclusion. The analysis using bibliometric methods and review with graphical presentations can be very useful in investigating and better understanding the relationship between FS and IB.

Background: The COVID-19 pandemic has put other infectious diseases, especially in children, into a new perspective. Our study focuses on two important viral infections: COVID-19 and influenza, which often present with similar clinical symptoms. Taking into consideration that the pathophysiology and systemic impact of the two viruses are distinct, which can lead to measurable differences in laboratory values, this study aimed to analyze laboratory features that differentiate between COVID-19 and influenza virus infections in pediatric patients. Methods: We statistically analyzed the routinely available laboratory data of 98 patients with influenza virus and 78 patients with COVID-19. Afterwards, the classification and regression tree (CART) method was performed to identify specific clinical scenarios, based on multilevel interactions of different features that could assist clinicians in evidence-based differentiation. Results: Significant differences between the two groups were observed in ALT, eosinophils, hemoglobin, and creatinine. Influenza-infected infants presented significantly higher leukocyte, neutrophil, and basophil counts compared to infants infected with COVID-19. Regarding children (over 12 months), significantly lower levels of ALT and eosinophil counts were observed in those with influenza compared to those with COVID-19. Furthermore, the CART decision tree model identified distinct profiles based on a combination of features such as age, leukocytes, lymphocytes, platelets, and neutrophils. Conclusions: After further refinement and application, such machine learning-based, evidence-driven models, considering the large scale of clinical and laboratory variables, might help to improve, support, and sustain healthcare practices. The differential decision tree may contribute to enhanced clinical risk assessment and decision making.