Search Results (880)

Background/Objectives: Violence is a significant occupational health issue for paramedics, yet underreporting limits efforts to identify and mitigate risk. Leveraging a novel, point-of-event violence reporting system, we aimed to identify characteristics of 9-1-1 calls associated with an increased risk of violence in a single paramedic service in Ontario, Canada. Methods: We retrospectively analyzed all electronic violence and patient care reports filed by paramedics in Peel Region and used logistic regression to identify call-level predictors of any violence and, more specifically, physical or sexual assault. Results: In total, 374 paramedics filed 974 violence reports, 40% of which documented an assault, corresponding to a rate of 4.18 violent encounters per 1000 9-1-1 calls. In adjusted models, the risk of violence was elevated for calls originating from non-residential locations (e.g., streets, hotels, bars), occurring during afternoon or overnight shifts, and involving young or working-age males. Presenting problems related to intoxication, mental health, or altered mental status were strongly associated with increased risk, with particularly high adjusted odds ratios for assault. Conclusions: These findings support the utility of near-miss and violence surveillance systems and highlight the need for multidisciplinary crisis response to high-risk calls, especially those involving mental health or substance use. Full article

Background: Among all ambulatory antibiotic prescriptions, about 20% are non-visit-based (ordered outside of an in-person clinical encounter), and about 30% are not associated with an infection-related diagnosis code. Objective/Methods: To identify the rationale for ambulatory antibiotic prescribing, we queried the electronic health record (EHR) of a single, large health system in the Midwest United States to identify all oral antibiotics prescribed from November 2018 to February 2019 and examined visit, procedure, lab, department, and diagnosis codes. For the remaining antibiotic prescriptions—mostly non-visit-based, no-infectious-diagnosis-documented—we randomly selected and manually reviewed the EHR to identify a prescribing rationale and, if none was present, surveyed prescribers for their rationale. Results: During the study period, there were 47,619 antibiotic prescriptions from 1177 clinicians to 41,935 patients, of which 2608 (6%) were eligible non-visit-based, no-infectious-diagnosis-documented. We randomly selected 2298. There was a documented rationale for 2116 (92%) prescriptions. The most common documented reasons—not mutually exclusive—were patient-reported symptoms (71%), persistence of symptoms after initial management (18%), travel (17%), and responding to lab or imaging results (11%). We contacted 160 clinicians who did not document any prescribing rationale in the EHR and received responses from 62 (39%). Clinicians’ stated reasons included upcoming or current patient travel (19%), the antibiotic was for the prescriber’s own family member (19%), or the clinician made a diagnosis but did not document it in the EHR (18%). Conclusions: Non-visit-based, no-infectious-diagnosis-documented antibiotic prescriptions were most often in response to patient-reported symptoms, though they also occur for a variety of other reasons, some problematic, like in the absence of documentation or for a family member. Full article

Background/Objectives: This study examines the effectiveness of train-time computation, test-time computation, and their combination on the performance of large language modeling applied to an electronic medical record quality management system. It identifies the most effective combination of models to enhance clinical documentation performance and efficiency. Methods: A total of 597 clinical medical records were selected from the MEDEC-MS dataset, 10 of which were used for prompt engineering to guide model training. Eight large language models were employed for training, focusing on train-time computation and test-time computation. Model performance on specific error types was assessed using precision, recall, F1 score, and error correction accuracy. The dataset was divided into training and testing sets in a 7:3 ratio. The assembly model was created using binary logistic regression for assembly analysis of the top-performing models. Its performance was evaluated using area under the curve values and model weights. Results: GPT-4 and Deepseek R1 demonstrated higher overall accuracy in detecting errors. Models that focus on train-time computation exhibited shorter reasoning times and stricter error detection, while models emphasizing test-time computation achieved higher error correction accuracy. The GPT-4 model was particularly effective in addressing issues related to causal organisms, management, and pharmacotherapy, whereas models focusing on test-time computation performed better in tasks involving diagnosis and treatment. The assembly model, focusing on both train-time computation and test-time computation, outperformed any single large language model (Assembly model accuracy: 0.690 vs. GPT-4 accuracy: 0.477). Conclusions: Models focusing on train-time computation demonstrated greater efficiency in processing speed, while models focusing on test-time computation showed higher accuracy and interpretability in identifying and detecting quality issues in electronic medical records. Assembling the train-time and test-time computation strategies may strike a balance between high accuracy and model efficiency, thereby enhancing the development of electronic medical records and improving medical care. Full article

The respiratory consequences of brachycephalic airway obstructive syndrome (BAOS) are well known; however, brachycephalic dogs may also present with alimentary tract signs. The electronic medical records of 176 French bulldogs with BAOS were reviewed to classify the gastrointestinal endoscopic findings, and to evaluate the associations between clinicopathological data, endoscopic respiratory, and digestive findings. Dogs that did not undergo endoscopic examination of both airways and the upper digestive tract were excluded. The type and frequency of respiratory and digestive signs were assessed according to a previously described grading system, in addition to gastrointestinal histopathological findings. Video documentation was reviewed to assign a score to each gastrointestinal endoscopic finding (EGF) and to obtain a total EGF score. All dogs showed at least one EGF. The median total EGF score was 5 (range 1–9). A significant association between the score from digestive signs and the total EGF score was found. In addition, laryngeal granulomas were significantly associated with regurgitation. No associations were found between gastrointestinal histopathological findings and the scores from respiratory or digestive signs. Overall, gastrointestinal endoscopic findings and laryngeal granulomas are common among French bulldogs with BAOS. Therefore, a systematic endoscopic approach to alimentary signs is desirable to determine the most appropriate treatment. Full article

The Shenduntou Site, a significant Zhou Dynasty settlement in Anhui Province, provides rare insights into early Chinese woodcraft. This study examines exceptionally preserved wooden structures from Well J1, dating to the Western Zhou period (9th–8th c. BCE). Anatomical analysis identified the timber as Firmiana simplex (L.), indicating ancient selection of this locally available species for its water resistance and mechanical suitability in well construction. Comprehensive degradation assessment revealed severe structural deterioration: maximum water content (1100% ± 85% vs. modern 120% ± 8%) demonstrated extreme porosity from hydrolysis; X-ray diffraction (XRD) showed a 69.5% reduction in cellulose crystallinity (16.1% vs. modern 52.8%); Fourier Transform Infrared Spectroscopy (FTIR) spectroscopy confirmed near-total hemicellulose degradation, partial cellulose loss, and lignin enrichment due to chemical recalcitrance; Scanning Electron Microscopy (SEM) imaging documented multiscale damage including vessel thinning, pit membrane loss, and cell wall delamination from hydrolytic, microbial, and mineral degradation. These findings reflect Western Zhou inhabitants’ pragmatic resource utilisation while highlighting advanced material deterioration that poses significant conservation challenges, providing critical insights into Zhou-era woodcraft and human–environment interactions in the lower Yangtze region. Full article

Among the craft recipes for artisans collected in the 4th-century Egyptian documents the Leyden and Stockholm papyri, there is one calling for adding animal milk to orchil for wool dyeing. To understand the rationale for this practice, wool yarns were dyed with and without goat milk added to orchil dyebaths, each made using lichens from three different sources. The results showed orchil containing milk dyed yarns a noticeably deeper red hue. The colorants extracted from the dyed yarns were analyzed by liquid chromatography-diode-array-detector-mass spectrometry to assess the relative amounts of nine identifiable orceins. The data showed that the yarns dyed with milk gave extracts exhibiting several fold more α-aminoorcein and α-hydroxyorcein, with only small differences in the other seven. Scanning electron microscopic analysis of a representative pair of dyed yarns showed that milk promoted surface changes in the fiber that may indicate increased cutaneous damage. Hypotheses for the milk’s effects on orchil dyeing were proposed that included the formation of milk–protein complexes with the two enriched orceins that possibly enhanced wool binding and/or better wool uptake of free and/or complexed orceins due to biodegradation of the wool’s surface cuticle caused by microbial growth promoted by the addition of milk. Full article

Background: The effective use of electronic health records (EHRs) is an essential clinical skill, but medical schools have traditionally provided limited systematic teaching on the topic. Inefficient use of EHRs results in delays in diagnosis, fragmented care, and clinician burnout. This study investigates the impact on medical students’ confidence, efficiency, and proficiency in extracting clinically pertinent information from patient records following an organised EHR teaching programme. Methods: This observational cohort involved 60 final-year medical students from three London medical schools. Participants received a structured three-phase intervention involving an introductory workshop, case-based hands-on practice, and guided reflection on EHR navigation habits. Pre- and post-intervention testing involved mixed-method surveys, simulated case tasks, and faculty-assessed data retrieval exercises to measure changes in students’ confidence, efficiency, and ability to synthesise patient information. Quantitative data were analysed using paired t-tests, while qualitative reflections were theme-analysed to identify shifts in clinical reasoning. Results: All 60 students successfully finished the intervention and assessments. Pre-intervention, only 28% students reported feeling confident in using EHRs effectively, with a confidence rating of 3.0. Post-intervention, 87% reported confidence with a rating of 4.5 (p < 0.01). Efficiency in the recovery of critical patient information improved from 3.2 to 4.6 (p < 0.01). Students also demonstrated enhanced awareness regarding system-related issues, such as information overload and fragmented documentation, and provided recommendations on enhancing data synthesis for clinical decision making. Conclusions: This study emphasises the value of structured EHR instruction in enhancing the confidence and proficiency of medical students in using electronic records. The integration of structured EHR education to medical curricula can better prepare future physicians in managing information overload, improve diagnostic accuracy, and enhance the quality of patient care. Future research should explore the long-term impact of structured EHR training on clinical performance, diagnostic accuracy, and patient outcomes during real-world clinical placements and postgraduate training. Full article

This paper proposes a KeyBERT-based method for constructing a knowledge graph of the electronic information curriculum system, aiming to enhance the structured representation and relational analysis of educational content. Electronic Information Engineering curricula encompass diverse and rapidly evolving topics; however, existing knowledge graphs often overlook multi-word concepts and more nuanced semantic relationships. To address this gap, this paper presents a KeyBERT-enhanced method for constructing a knowledge graph of the electronic information curriculum system. Utilizing teaching plans, syllabi, and approximately 500,000 words of course materials from 17 courses, we first extracted 500 knowledge points via the Term Frequency–Inverse Document Frequency (TF-IDF) algorithm to build a baseline course–knowledge matrix and visualize the preliminary graph using Graph Convolutional Networks (GCN) and Neo4j. We then applied KeyBERT to extract about 1000 knowledge points—approximately 65% of extracted terms were multi-word phrases—and augment the graph with co-occurrence and semantic-similarity edges. Comparative experiments demonstrate a ~20% increase in non-zero matrix coverage and a ~40% boost in edge count (from 5100 to 7100), significantly enhancing graph connectivity. Moreover, we performed sensitivity analysis on extraction thresholds (co-occurrence ≥ 5, similarity ≥ 0.7), revealing that (5, 0.7) maximizes the F1-score at 0.83. Hyperparameter ablation over n-gram ranges [(1,1),(1,2),(1,3)] and top_n [5, 10, 15] identifies (1,3) + top_n = 10 as optimal (Precision = 0.86, Recall = 0.81, F1 = 0.83). Finally, GCN downstream tests show that, despite higher sparsity (KeyBERT 64% vs. TF-IDF 40%), KeyBERT features achieve Accuracy = 0.78 and F1 = 0.75, outperforming TF-IDF’s 0.66/0.69. This approach offers a novel, rigorously evaluated solution for optimizing the electronic information curriculum system and can be extended through terminology standardization or larger data integration. Full article

Accessibility in web systems is essential to ensure everyone can obtain information equally. Based on the Web Content Accessibility Guidelines (WCAGs), the Electronic Government Accessibility Model (eMAG) was established in Brazil to guide the accessibility of federal government web systems. Based on these guidelines, this research sought to understand the reasons behind the persistent gaps in web accessibility in Brazil, even after 20 years of eMAG. To this end, the accessibility of the Integrated Academic Activities Management System (SIGAA), used by 39 higher education institutions in Brazil, was evaluated. The living lab methodology was used to carry out accessibility and usability tests based on students’ experiences with visual impairments during interaction with the system. Furthermore, IT professionals’ knowledge of eMAG/WCAG guidelines, the use of accessibility tools, and their beliefs about accessible systems were investigated through an online questionnaire. Additionally, the syllabuses of training courses for IT professionals at 20 universities were analyzed through document analysis. The research confirmed non-compliance with the guidelines in the software researched, gaps in the knowledge of IT professionals regarding software accessibility practices, and inadequacy of accessibility content within training courses. It is concluded, therefore, that universities should incorporate mandatory courses related to software accessibility into the training programs for IT professionals and that organizations should provide continuous training for IT professionals in software accessibility practices. Furthermore, the current accessibility legislation should be updated, and its compliance should be required within all organizations, whether public or private. Full article

Background: Immunization information systems (IISs) in the United States forecast vaccine due dates, which can inform when providers recommend vaccines to patients. IIS forecasting for HPV vaccination at 9 years, the minimum age of licensure, and when vaccination is likely most effective is not documented or well-understood. Methods: We documented characteristics of HPV vaccination forecasts in jurisdictional IISs through Internet searches and requests to immunization program managers. Next, we conducted focus groups with stakeholders from seven jurisdictions to elucidate their processes for determining and implementing HPV vaccination forecasts. Results: Forecast data were available from 49 out of 64 CDC-funded jurisdictions, of which 14 (29%) recommended HPV vaccination at age 9 and 35 (71%) recommended HPV vaccination starting at ages 11 through to 15. Jurisdictions that recommended HPV vaccination at age 9 cited the positions of the American Cancer Society and American Academy of Pediatrics and reported little or no provider opposition to this recommendation. Jurisdictions reported variable flexibility in programming their forecasts. Those that changed their HPV vaccination forecast from 11 to 9 years did so easily while some experienced limitations. Other jurisdictions adhered strictly to the CDC’s routine recommendation at age 11–12 years and would only update the forecast in tandem with updated CDC guidance. The impact of IISs and electronic health record interoperability on how providers view and utilize IIS forecasting is unclear. Conclusions: Jurisdictions can share best practices for forecasting at 9 and future studies can evaluate the effects of forecasting age on the vaccination rates, providing evidence for nationwide vaccination recommendations. Full article

The paper titled “Methods for a Non-Targeted Qualitative Analysis and Quantification of Benzene, Toluene, and Xylenes by Gas Chromatography-Mass Spectrometry of E-Liquids and Aerosols in Commercially Available Electronic Cigarettes in Mexico” was submitted in compliance with all the requirements of the editorial and journal in question, as evidenced by the dates and the respective backup documentation [...] Full article

Background/Objectives: The presence of Ehlers–Danlos Syndromes (EDSs) has significant effects on overall health and results in varying levels of pain and disability. The effects of sleep are not well documented in this population. The purpose of this study is to report the sleep characteristics of people with EDS. Methods: An electronic survey regarding sleep characteristics was created and distributed through the EDS website. Results: Sleep disturbance is common in people with EDS, with 65.3% of respondents sleeping fewer than 8 h and 26.2% averaging fewer than 6 h. Those who slept fewer than 6 h reported more days of poor mental and physical health days. Sleep aids were commonly used with 41.40% of patients regularly taking prescription medication to get to sleep. Sleep latency of greater than 30 min was also found in 67.5% of subjects. Conclusions: The results demonstrate an association between people with EDS and poorer sleep duration, increased sleep latency, and increased use of sleep aids including prescription sleep medication compared to the general population. While more research needs to be completed in this area, sleep may be an important aspect to address in the management of EDS. Full article

Background: The Patient Outcome Assessment and Decision Support (PADS) model is a real-time framework designed to predict both mortality and the likelihood of discharge within 48 h in critically ill patients. By combining these predictions, PADS enables clinically meaningful stratification of patient trajectories, supporting bedside decision-making and the planning of critical care resources such as nursing allocation and surgical scheduling. Methods: PADS integrates routinely collected clinical data: SOFA variables, age, gender, admission type, and comorbidities. It consists of two Long Short-Term Memory (LSTM) neural networks—one predicting the probability of death and the other the probability of discharge within 48 h. The combination places each patient into one of four states: alive/discharged within 48 h, alive/not discharged, dead within 48 h, or dead later. The model was trained using MIMIC-IV data, emphasizing ease of implementation in units with electronic health records. Out of the 76,540 stays present in MIMIC-IV (53,150 patients), 32,875 (25,555 patients) were used after excluding those with short stays (<48 h) or life support treatment limitations. The code is open, well-documented, and designed for reproducibility and external validation. Results: The model achieved strong performance: AUCROC of 0.94 (±0.03) for mortality and 0.89 (±0.07) for discharge on training data, and 0.87 (±0.02) and 0.88 (±0.03), respectively, on the test set. As a comparison, benchmark models obtain worse accuracy (−13.4% for APS III, −19% for OASIS, and −7.4% for SAPS II). Predictions are visualized in an intuitive format to support clinical interpretation. Conclusions: PADS offers a transparent, reproducible, and practical tool that supports both individual patient care and the strategic organization of intensive care resources by anticipating short-term outcomes. Full article

Background/Objectives: Numerous studies have documented the effect of human chronotypes on psychological well-being. This study aimed to examine the associations of chronotype subtypes and mental health among Spanish university students. Methods: Sociodemographic data were collected electronically using a self-administered questionnaire with Google Forms. In addition, participants completed The Morningness-Eveningness Questionnaire (MEQ) by Horne and Östberg, the Goldberg Anxiety and Depression Scale (GADS), and the Perceived Stress Scale (PSS). Results: Two hundred and eighty-nine students participated in the study. The most prevalent chronotype in the study sample was the intermediate (64.4%), followed by the evening (19.4%) and the morning (16.3%) chronotypes. Based on cut-off scores of the instruments used, the percentage of students with relevant symptoms of anxiety, depression and stress was high, 45.3%, 46.4% and 79.6%, respectively. Statistical analysis showed statistically significant differences between the total score of the Goldberg scale and the three chronotype categories, with higher scores in the evening group. A multivariate regression model analysis also identified a statistically significant correlation between the depression subscale and chronotype (R squared = 0.287) and between evening vs. morning chronotype (OR = 0.48; IC 95% [0.23–0.98]) and evening vs. intermediate chronotype (OR = 2.60; 95% CI [1.00–5.08]). In turn, the depression subscale showed a statistically significant correlation with the variables gender (OR = 2.22; 95% CI [1.03–4.76] being more frequent in women) and daily consumption of stimulant drinks (OR = 0.54; 95% CI [0.31–0.94]; being higher in people with lower consumption). The anxiety subscale showed a statistically significant correlation with chronotype (R squared = 0.309) and with evening vs. morning chronotype (OR = 0.46, 95% CI [0.22–0.94]). With respect to stress, there was a statistically significant correlation with gender (OR = 3.08, 95% CI [1.40–6.79], being more frequent in women), with chronotype (R squared = 0.141), and with evening vs. morning chronotype (OR = 0.34, 95% CI [0.16–0.72]). Conclusions: Our results suggest that students with an evening chronotype are more likely to suffer from mental health problems, and interventions to improve their mental health are necessary. Full article

Background: Soft liners offer a cushioning effect that aids in the healing of inflamed mucosa and allocates the relevant load in the support area of prostheses, enhancing their fit and stability. This study looks at how strontium-infused phosphate bioactive glass affects a heat-cured acrylic-based soft liner, focusing on the surface hardness and the surface roughness of the material. Methods: One hundred soft liner specimens were produced, with fifty specimens being designated for surface hardness testing and fifty specimens for surface roughness testing. PBG*Sr was incorporated into the soft liner at the concentrations of 1 wt.%, 3 wt.%, 5 wt.%, and 7 wt.%. Surface hardness and surface roughness were evaluated with a digital durometer for Shore A hardness and a profilometer, respectively. Fourier transform infrared spectroscopy analysis and field emission scanning electron microscopy were employed. Results: The Shapiro–Wilk test demonstrated that the data adhered to a normal distribution, as the p-values were not statistically significant. Subsequently, for statistical analyses following the one-way ANOVA, Dunnett’s T3 post hoc test was employed for surface hardness, while Tukey’s post hoc test was used for surface roughness. The lowest hardness value was documented in the 7 wt.% subgroup (29.040 ± 0.070), followed by the 5 wt.% subgroup (30.97 ± 0.231), and the control (40.880 ± 0.473) had the highest hardness mean value. The 7 wt.% subgroup displayed the lowest value of Ra recorded, 0.489 ± 0.077 μm, while the control subgroup showed the highest, 1.994 ± 0.168 μm. FTIR analysis suggested that the domination of physical interactions according to the analyses with the FESEM led to improved surface morphology for the 7 wt.% PBG*Sr specimens. Conclusions: The 7 wt.% PBG*Sr specimens exhibited the lowest surface hardness, suitable for soft lining material, and improved the surface morphology of acrylic soft liners compared with the control and other concentrations. Full article