Background/Objectives: Sepsis and septic shock remain significant contributors to high early mortality rates among patients admitted to the emergency department (ED). The objective of this study was to identify among newer biomarkers those with the highest sensitivity in early mortality prediction. Methods: This prospective, unicentric, observational study enrolled 47 adult patients admitted to the ED between November 2020 and December 2022. This study monitored the kinetics of the older and newer biomarkers, including azurocidin (AZU1), soluble triggering receptor expressed on myeloid cells (sTREM), soluble urokinase-type plasminogen activator receptor (suPAR), high-sensitivity C-reactive protein (hsCRP), procalcitonin (PCT), and interleukin-6 (IL-6), and their capacity in predicting mortality. Results: SuPAR showed the most significant predictive utility for early prognosis of mortality in the ED, with an area under the curve (AUC) of 0.813 (95% CI: 0.672 to 0.912), a cutoff value > 8168 ng/mL, sensitivity of 75%, and specificity of 81.48% (p < 0.001). IL-6 and PCT showed comparable prognostic accuracy, whereas hsCRP and AZU1 demonstrated lower predictive performance. Conclusions: In our study, suPAR, IL-6, and PCT showed good predictive value for short-term mortality in sepsis and septic shock patients.

Background: Owing to the infrequent emergence of disasters and the challenges associated with their management, responders need appropriate training beyond doubt. Ensuring the highest standard of disaster management (DM) training is of paramount importance for high-quality DM. However, the literature concerning DM training monitoring and evaluation (M&E) is scarce. The primary objective of this review was to document the existing M&E strategies for DM training. Methods: The authors conducted a systematic literature search on June 28, 2023, on the PubMed, Scopus, Embase and Cochrane databases, including studies that described the learning objectives and the M&E strategy of DM training. The authors categorized the learning objectives and the evaluation methodology according to the revised Bloom’s Taxonomy and the New World Kirkpatrick model, respectively. Results: Fifty-seven articles met the inclusion and exclusion criteria, described DM training targeting healthcare and non-healthcare professionals and employed diverse teaching methods and topics. Five studies reported using monitoring, while all reported an evaluation methodology. The learning objectives focused on students’ ability to “Remember” (N = 50) and “Apply”(N = 44). The evaluations centred around the second level of the New World Kirkpatrick model (N = 57), with only 7 articles investigating the third level. Sixteen authors used existing, validated M&E frameworks. When corelating the learning objectives with the evaluation methodology, the authors observed a mismatch, as skills like the students’ ability to “Apply” and “Create” were evaluated using the second level of the New World Kirkpatrick model. Conclusions: The great heterogeneity in DM training highlights the particularity of these educational programs. The lack of monitoring and the low usage of existing M&E frameworks highlighted a lack of awareness and standardization in the field. The mismatch between the learning objectives and the evaluation process led to deceptive evaluations, which may have resulted in graduates being deemed ready to deploy despite facing hardships in real-world settings, potentially leading to unprepared responders.

Background: There has been a significant increase in the use of e-learning for global and public health education recently, especially following the COVID-19 pandemic. e-Learning holds the potential to offer equal opportunities, overcoming barriers like physical limitations and training costs. However, its effectiveness remains debated, with institutions unprepared for the sudden shift during the pandemic. To effectively evaluate the outcomes of e-learning, a standardized and rigorous approach is necessary. However, the existing literature on this subject often lacks standardized assessment tools and theoretical foundations, leading to ambiguity in the evaluation process. Consequently, it becomes imperative to identify a clear theoretical foundation and practical approach for evaluating global and public health e-learning outcomes. Objective: This protocol for a scoping review aims to map the state of e-learning evaluation in global and public health education to determine the existing theoretical evaluation frameworks, methods, tools, and domains and the gaps in research and practice. Methods: The scoping review will be conducted following the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews) guidelines. The initial search was performed in PubMed, Education Resource Information Center, Web of Science, and Scopus to identify peer-reviewed articles that report on the use of evaluation and assessment for e-learning training. The search strings combined the concepts of e-learning, public health, and health science education, along with evaluation and frameworks. After the initial search, a screening process will be carried out to determine the relevance of the identified studies to the research question. Data related to the characteristics of the included studies, the characteristics of the e-learning technology used in the studies, and the study outcomes will be extracted from the eligible articles. The extracted data will then undergo a structured, descriptive, quantitative, and qualitative content analysis to synthesize the information from the selected studies. Results: Initial database searches yielded a total of 980 results. Duplicates have been removed, and title and abstract screening of the 805 remaining extracted articles are underway. Quantitative and qualitative findings from the reviewed articles will be presented to answer the study objective. Conclusions: This scoping review will provide global and public health educators with a comprehensive overview of the current state of e-learning evaluation. By identifying existing e-learning frameworks and tools, the findings will offer valuable guidance for further advancements in global and public health e-learning evaluation. The study will also enable the creation of a comprehensive, evidence-based e-learning evaluation framework and tools, which will improve the quality and accountability of global health and public health education. Ultimately, this will contribute to better health outcomes. International Registered Report Identifier (IRRID): DERR1-10.2196/49955

This systematic review explores the application of Raman spectroscopy (RS) in traumatic brain injury (TBI) research, emphasizing the need for innovative and efficient diagnostic tools. The development of such techniques aims to alleviate healthcare costs while providing timely assessment of injury severity. A systematic literature search for the use of RS in TBI was conducted in PubMed, Scopus, and Web of Science from inception to July 28, 2025, following PRISMA guidelines. We included only original English-language studies (animals and humans) in free full-text format. Risk of bias was assessed using specific tools for both animal and human models. Findings were classified according to the cohorts, and spectroscopic technique alongside their particularities. The initial search found 261 articles, with 26 studies meeting the inclusion criteria. Among them: 15 were animal studies and 11 translational/human-relevant studies. Among animal studies, 3 focused on in-situ monitoring and TBI classification, 2 on blast-induced models, 5 on blood biomarker analysis, 2 on retinal-based point-of-care diagnostics, and 3 on Raman microscopy. The translational research studies aimed to identify and validate TBI biomarkers for developing future diagnostic strategies in human patients. RS distinguished injured from control tissue through spectral changes reflecting protein and lipid alterations and differentiated lesion areas by revealing astrogliosis-related reorganization. Instantaneous in-situ RS devices achieved >92% accuracy in severity classification and detected biomarker-related molecular changes. Point-of-care RS platforms using lateral flow strips enabled rapid detection of specific TBI biomarkers (GFAP, NAA, NSE, S100B, UCH-L1), showing performance comparable to ELISA while offering faster, simpler, and cost-efficient testing.