bluuebunny/crossref_metadata_2025_split huggingface dataset:
Rabies epidemiology in the central of Tunisia: A Call for a One-Health Approach
Authors: Ben Nasrallah C , Abroug H , Ghoul M , Grira S , Ben Fredj M , Kacem M , Dhouib W , Zemni I , Bouanene I , Belguith Sriha A 
Published: October 2024

Abstract

Background
Advocating for a One-Health approach is crucial for ensuring effective rabies surveillance in Africa, including Tunisia. Collecting information is essential to evaluate the prevalence of dog bites and rabies in Tunisia. To address this, we conducted an analysis of reported incidents in the central region of Tunisia from 2019 to 2022. This analysis aimed to generate valuable insights that can inform strategies for rabies elimination in Tunisia, highlighting the importance of the One-Health approach.

Methods
We carried out a descriptive study using surveillance data from Monastir governorate in Central Tunisia. All humans exposed to animals, residents in Monastir Governorate and declared to the regional directorate of primary health care from January 1, 2019 to December 31, 2022 were included in our study. Data were entered, cleaned, and analyzed using Excel.

Results
During the studied period, 7789 cases of human exposures to animals were reported with an annual average of 1969 ± 207 exposures per year. The annual incidence rate of exposure to animal bites was 324 per 100,000 population. The sex-ratio was 2.07 and almost one third of exposed humans were aged less than 15 years-old. The most listed offending animals were dogs (65.2%), followed by cats (24.4%). The number of exposures by unvaccinated dogs increased significantly during our study period. Post-exposure prophylaxis (PEP) was applied among 99% (n = 7772) of declared exposures. Among them, 2.5% (n = 202) did not complete the PEP recommended protocol. During our study period, rabies was confirmed in 39 animals. Two fatal human rabies cases were declared respectively in 2021 and 2022.

Conclusions
Rabies remains a worrying health problem in Tunisia with a high percentage reported among youth and males. Targeting children and adolescents by education and information campaigns about preventive measures and mass dog vaccination are the key to ending this scourge.

Key messages
• It is crucial to reinforce preventive strategies, such as mass dog vaccination programs.
• Public awareness about rabies prevention should be enforced in order to decrease Human rabies risks.
Beneficial clinical effects of honey from bees fed with specific plant extracts
Authors: Hajzer Z , Oláh C , Oláh B , Váradi C , Shaikh A , Daróczi L , Prokisch J 
Published: October 2024

Abstract

Background
Our team has demonstrated in a number of pre-clinical studies that special bees fed with syrups containing natural plant extracts contain a number of active substances that have beneficial effects on the human body. We have previously reported that bees fed with green walnut have beneficial effects on sugar metabolism, lowering serum glucose levels and reducing insulin resistance.

Methods
We conducted a prospective double-blind functional food study with 45 healthy volunteers using a strict inclusion and exclusion criteria with ethical approval. Participants ate 30 gramms of honey layered under 150 ml of yoghurt twice a day for 3 weeks. Fifteen participants consumed honey from bees fed with green walnut extract, while 15 participants consumed honey from bees fed with sea buckthorn extract, and 15 participants in the control group consumed acacia honey. Sleep quality was assessed with the SQS questionnaire, and quality of life with the SF-36, EORTC Q-C30 and EQ-5D tests on days 0 and 22 of the study.

Results
Consumption of both specific honey resulted improvements in the life quality parameters and in the sleep quality. ‘Buckthorn honey’ showed significant differences after the 3rd week: physical function improved (25.3±0.5 vs 27.4±2.8; p = 0.04), anxiety-depression decreased (1.4±3.6 vs 1±0.3; p = 0.03), complex physical status (84.1±9.7 vs 88.7±6.9; p = 0. 04), while ‘green walnut honey’ improved EQ-5D complex quality of life (84.1±9.7 vs 88.9±6.9; p = 0.01), overall quality of life functioning (90.6±14.9 vs 99.2±4.2; p = 0.03), EORTC Q-C30 total score (467.1±30.6 vs 487.4±21.4; p = 0.03).No such positive effects were confirmed in the control group.

Conclusions
Honey from bees fed with sea buckthorn extract has many beneficial physiological effects on the human body, improving physical well-being and reducing anxiety and depression. Honey from bees fed with green walnut extract improves the complex quality of life.

Key messages
• Improving the quality of life with nutrition is an increasingly important research field, playing a key role in our life.
• Our research has shown that honey from bees fed with green walnut and sea buckthorn extract improves several parameters in the quality of life.
Risk factors for bicycle-related overtaking, rear-end, and door crashes in the United Kingdom
Authors: Chao C C , Widodo A F , Pai C W 
Published: October 2024

Abstract

Background
Prior studies have offered valuable insights into risk factors associated with bicycle crashes at intersections. Nevertheless, limited research focuses on investigating three types of bicycle crashes that commonly occur on road segments: overtaking, rear-end, and door crashes.

Methods
In the present research, risk factors for these three types of crashes on road segments were examined by analyzing British STATS19 reports of crashes from 1991 to 2020. We calculated adjusted odds ratios (AORs) with 95% confidence intervals (CIs) for multiple risk factors using multivariate logistic regression models. The analysis included 127,637 bicycle crashes, categorized into 18,350 overtaking, 44,962 rear-end, 6,363 door, and 57,962 other crashes.

Results
Speed limits of ≥ 40 miles per hour (mph) (AOR = 2.238, 95% CI = 2.159-2.320), heavy goods vehicles (HGVs) as crash partners (AOR = 2.867, 95% CI 2.473-3.323), and elderly crash partners (AOR = 2.013, 95% CI = 1.937-2.092) were significant risk factors for overtaking crashes. Notable risk factors for rear-end crashes included midnight hours (AOR = 1.269, 95% CI = 1.190-1.354) and unlit darkness (AOR = 1.486, 95% CI = 1.404-1.573). Speed limits 20-30 mph (AOR = 16.185, 95% CI = 13.514-19.382), as well as taxis and private rental automobiles (AOR = 2.695, 95% CI = 2.310-3.145), were factors associated with door crashes. Further intriguing findings from our joint-effect analysis included higher probabilities for overtaking crashes in rural regions when older drivers and HGVs were crash partners (AOR = 2.93, 95% CI = 2.79-3.08 and AOR = 2.62, 95% CI = 2.46-2.78).

Conclusions
The mentioned risk factors have remained mostly consistent since our previous study was conducted in 2011. However, current research elucidated that certain factors have become more significant under specific circumstances. For instance, in rural areas, cyclists were more likely to be involved in overtaking crashes with heavy goods vehicles as crash partners.

Key messages
• Bicycle crash; Road segment; Door crash; Overtaking crash; Rear-end crash
Prediction of overweight/obesity risk in adolescence using static and dynamic multi-exposure models
Authors: Santos S , Oliveira MIT , Pereira R , Oliveira A , Barros H , Gaio R 
Published: October 2024

Abstract

Background
Studying the risk factors for obesity development and timely identification of individuals at increased risk are key for obesity prevention. We aimed to assess the associations of multiple prenatal, infancy and childhood exposures with overweight/obesity at 13 years (y) and develop static and dynamic multiple-exposure prediction models.

Methods
In 4232 mother-child pairs from the Generation XXI birth cohort, we assessed, during pregnancy/infancy and childhood, 55 sociodemographic factors, anthropometric measures, lifestyle behaviors, and clinical exposures related to the mother and the child and categorized body mass index z-scores as normal weight and overweight/obesity at 13y. Static models for pregnancy/infancy, 4, 7 and 10y, and a dynamic model were fitted using Elastic Net and logistic regression and were compared in terms of predictive performance.

Results
Mothers with lower educational level and household income, no partner, overweight/obesity before and after pregnancy, excessive gestational weight gain, pregnancy complications and who were smokers during pregnancy had children with a higher risk of overweight/obesity at 13y. Children with higher BMI during infancy, overweight/obesity during childhood, an early introduction of solid foods (before 4 months), a higher consumption of soft drinks at 4y and females had a higher risk of overweight/obesity at 13y. We observed the lowest predictive performance for the pregnancy/infancy model (prediction error of 36%) and the highest predictive performance for the 10y and dynamic models (prediction errors of 17%).

Conclusions
We identified the most important predictors of overweight/obesity in adolescence, most of them modifiable, and able to be targeted in prevention strategies. Predicting overweight/obesity risk in adolescence might be suboptimal if only considering pregnancy/infancy data and improves as closer to the age of the outcome, with no additional benefit in using a complex dynamic model.

Key messages
• Prevention of overweight/obesity should start during prenatal life.
• Children at higher risk of overweight/obesity may be identified years earlier using prediction models in clinical practice.
Health care and social benefits among long-term unemployed
Authors: Kärkkäinen S , Laaksonen J , Mesiäislehto M 
Published: October 2024

Abstract

Background
There is limited knowledge on the diverse pathways behind long-term unemployment. It is considered that impaired health may lead to exclusion from working life, and that unemployment together with financial difficulties may impair health. In this study, we identify different pathways behind long-term unemployment, and analyse differences in health care and social benefits use based on the diverse pathways. This study contributes to the early identification and supportive efforts for those in risk of labour market marginalisation.

Methods
Those who had been mainly unemployed in years 2020 and 2021 were identified among all working age (18 to 64 years) Finnish citizens. Register data from Statistics Finland, the Social Insurance Institution of Finland and THL were combined for the analysis. Sequence analysis was conducted for individuals with main activity information for each observation years from 2013 until 2021 (n = 72,485, age 26 to 64 in year 2021).

Results
Those unemployed for two years were on average 49 years of age (38% women). Five clusters were identified based on the main activity over the nine observation years: unemployed (54%), students (3%), employed (23%), inactive (10%) and those returned to unemployment (10%). Health care attendance was most frequent among those in cluster inactive. Mental health diagnoses were most common among those in clusters inactive and students. Share of those with musculoskeletal diagnoses doubled from 2013 until 2021 among the previously employed. Yearly percentage of those with sickness absence (&gt;10 days) varied from 5 to 13% based on a cluster and a year. Share of recipients of basic social assistance was relatively stable throughout the years in all clusters being highest among inactive (50 to 60%) and lowest among students (6 to 18%).

Conclusions
Information on labour market background might be useful for preventive efforts and while developing services and social security for those in long-term unemployment.

Key messages
• There exists diverse backgrounds behind long-term unemployment.
• Labour market background should be considered while developing services for those in long-term unemployment.
Marketing or health promotion? A citizen science study of social media influencers’ health content
Authors: Gell S , Engel E , Heiss R , Karsay K , Schmidhofer J 
Published: October 2024

Abstract

Background
Social media influencers (SMI) became the dominant source of health information among adolescents, exerting influence through appealing content and para-social relationships. Personalized social media feeds of adolescents paired with latent platform algorithms result in myriads of individual information environments, which remain closed to researchers. Citizen science offers a solution to peek inside this black box and identify: What health content is disseminated by social media influencers and consumed by adolescents?

Methods
The citizen science study adopted a contributive approach, where adolescents collected and categorized SMI profiles and posts from their own feeds with a pre-tested survey tool which was available on Google Tabs. Data collection was conducted on Instagram, TikTok, and YouTube between April and May 2023 and subsequently analyzed by the research team.

Results
The study involved 19 school classes, containing 326 students, aged 12 to 19 years. They documented 255 SMI profiles and 2147 posts, primarily on Instagram and TikTok. Key topics included fitness, beauty ideals, and nutrition, while mental and sexual health received less attention. Although 41.5% of the posts contained advertising, the citizen scientists classified 63.5% as health-promoting. Topics relating to dietary supplements (84.1%), addictive substances (55.6%), nutrition (53.8%) and sport (47.2%) were particularly ad-heavy. Despite mental and sexual health having the lowest advertising rates at 35.4% and 37.7% respectively, this still accounts for over one third of the documented posts.

Conclusions
SMI present a distorted image of health that emphasizes nutrition, fitness and beauty ideals, while topics such as mental and sexual health are neglected. The positive reception of posts containing ads indicates a lack of critical reflection. Policies for advertising practices and balanced health education, including media literacy, are necessary to address these trends.

Key messages
• Social media influencers propagate a distorted health image, defined by nutrition, fitness, and beauty ideals.
• Adolescents lack the necessary skills to critically reflect on ad littered social media influencer health content.
Managing a 4000-participant cohort with a novel mobile app: data from the RisCoin study in Germany
Authors: Zhelyazkova A , Adorjan K , Koletzko L , Schrimf A , Koletzko S , Völk S , Fabry-Said A , Osterman A , Wichert S , Giang Le Thi T 
Published: October 2024

Abstract

Issue
RisCoin, a prospective monocentric longitudinal observational study, aimed to identify risk factors for COVID-19 vaccine failure. Secondary aim is to monitor symptoms, SARS-CoV-2 infection, vaccination status of 3816 enrolled healthcare workers (HCW) and 180 patients with inflammatory bowel disease (IBD). Since the LMU University Hospital Munich served both as study sponsor and employer of the HCW, a secured approach was required.

Description of the solution
Participants accessed the study app (CentraXX, KAIROS GmbH, Germany) via pseudonymized Contact-ID with irreversible anonymization after 6 months. Key app features were the serological results report, bidirectional messaging, and weekly survey for self-reported data on vaccinations, infections, and symptoms. Active app use was defined as submitting &gt;1 weekly survey during the study period 10.2021-12.2022.

Results
Over 15 months, our study team maintained 1964 two-way communications with 958 participants via the app. Of 3979 participants with app access, 3622 (91%) were active users, 2606 (65%) submitted 1 to 11 surveys, 1016 (26%) made ≥12 submissions (P75, “frequent users”). Frequent users were more likely to be IBD patients (p = 0.001), female (p &lt; 0.001), aged 60 or older (p &lt; 0.001). Staff in administration and nurses were more likely to be frequent users compared to physicians (p &lt; 0.001). Main problems included the initial operational system disparities resulting in app crashes and continuous need for app reactivation. Both led to loss of active participants and required substantial staff resources to onboard and support participants during the study.

Lessons
The study app enabled secure, flexible, bidirectional communication with all participants. Despite technical issues, the majority actively used the app and provided valuable longitudinal data through weekly survey submissions.

Key messages
• A study-specific app provides a flexible and secure bidirectional anonymous communication for the study team and participants.
• Adherence to app-based communication and data collection for pandemic monitoring was particularly high among patients, nurses and administrative staff.
Dual-tiered insights: cross-examining entities in free text electronic health records
Authors: ElHassan S , Sdralias A , Hamilton R , Shamsizadeh A 
Published: October 2024

Abstract

Background
Poor determination and processing of actions at the primary care level are found to be associated with unstructured and cluttered electronic health records (EHRs). Physicians recommend that EHRs must highlight entities, such as action items, findings, follow-ups, and reasons for medication changes. There’s consensus around the success of large language models (LLMs) in detecting clinical and non-clinical entities in EHRs. However, end-to-end systems make limited efforts to go beyond entity and relationship detection to support clinical decision-making.

Methods
We propose a two-tier system that generates case-based comparative reports for entities highlighted by physicians in EHRs. First, we fine-tuned a custom Bidirectional Encoder Representations from Transformers (BERT) model that detects the required entities within the EHRs. Second, a clustering-based service generates a report comparing the detected entities of a specific EHR with other EHRs sharing the same conditions determined by the healthcare professional.

Results
The system leverages the MIMIC IV deidentified free-text clinical notes dataset. The first-tier successfully classified entities with a macro-score average range of [0.87 - 0.94]. For the second tier, preliminary simulations on a set of test samples were made to cluster the entities. The simulations leverage a custom statistical tests engine offering a suite of entity-type specific tests. The results of these tests are used to generate the case-based detected entities comparative report.

Conclusions
Highlighting clinical and non-clinical entities bridges the communication gap between primary and secondary care. Clustering these entities extends the capability of LLMs in clinical support decision systems by providing healthcare professionals with the ability to run comparative analyses between EHRs. The comparative analysis reports provide a factual comparison between a selected number of detected entities and their thresholds.

Key messages
• Clustering clinical and non-clinical entities extends the capacity of named entity recognition in clinical decision-making systems.
• Ability to generate a comparative analysis report based on figures extracted from recognised entities in free-text electronic health records.
The physician-AI relationship: partnering for precision medicine via clinical decision support
Authors: Samuel H , Norman T , Vaknin S , Saban M 
Published: October 2024

Abstract

Background
Clinical decision support systems (CDSSs) can enhance physician decision-making, but successful adoption depends on positive user attitudes. Understanding Israeli physicians’ attitudes toward CDSSs is crucial for overcoming implementation barriers and refining training.

Methods
Semi-structured interviews explored knowledge, experiences, perceived benefits/drawbacks, and potential barriers/facilitators to CDSS use among 25 Israeli physicians across specialties, roles, settings, and experience levels selected via stratified sampling. Individual 45-minute video interviews were conducted in January-July 2023.

Results
Familiarity and CDSS experience varied substantially across medical specialties. While risk calculators, information systems, and expert systems disseminating contemporary research insights are widespread, AI-based system adoption is relatively low outside radiology. Physicians expressed positive attitudes, recognizing CDSSs’ potential to enhance clinical work, reduce errors, and alleviate burdens. However, concerns included AI systems’ impact on workload, patient relationships, skill erosion, and overreliance. Key implementation barriers involved technological infrastructure, organizational processes, physician perceptions, and system features. Facilitating factors included tailored design, focused training, continuous accuracy/reliability validation, and clear autonomy/liability guidelines.

Conclusions
Addressing key concerns around transparency, trustworthiness and responsible use is crucial for AI-CDSS to fulfill its promise of enhancing quality and outcomes. Insights from Israeli clinicians provide guidance on priorities like transparency of data and algorithms as well as ensuring AI behaves ethically. Collaboration among technology designers, healthcare professionals and stakeholders can help develop systems that physicians trust to improve care while safeguarding patients. Ongoing evaluation is also needed to optimize AI-CDSS over time.

Key messages
• Understanding physician attitudes is key to overcoming barriers to clinical decision support system adoption and optimizing training protocols.
• Addressing transparency, trustworthiness, and ethical considerations around AI clinical decision support systems is crucial for enhancing quality care.
Guidelines to practice in hospitals at home: penicillin infusion pumps in erysipelas treatment
Authors: Metsä-Simola N , Saarenketo J , Lehtonen H , Broman N , Häggblom T , Björklöf P , Sariola S , Valta M 
Published: October 2024

Abstract

Background
Hospitals at home are increasingly offering outpatient parenteral antimicrobial therapy (OPAT) in an attempt to reduce costly inpatient care, but these settings favor broad-spectrum antibiotics that require less frequent dosing than penicillin. Benzyl penicillin could be delivered via continuous infusion pumps (eCIP), but studies on their safety and efficacy in OPAT are scarce, and it remains unclear how much the availability of eCIPs increases penicillin use in real-life settings.

Methods
We examined 462 electronic healthcare records of erysipelas patients treated between January 2018 and January 2022 in a large Finnish OPAT clinic. Average marginal effects from logistic models were estimated to assess how the introduction of eCIPs in December 2020 affected penicillin use, and to compare clinical outcomes between patients with and without eCIPs.

Results
Introduction of eCIPs increased the predicted probability of penicillin treatment by 36.0 percentage points (95% confidence interval 25.5-46.5). During eCIP implementation, patients who received an eCIP had 73.1 (58.0-88.2) percentage points higher probability than patients without an eCIP to receive penicillin treatment. They also had about 20 percentage points higher probability to be cured at the time of discharge and three months after it. Patient and nurse satisfaction regarding eCIPs was very high.

Conclusions
Benzyl penicillin eCIP treatment is effective and safe, and substantially increases the use of penicillin instead of broad-spectrum antibiotics. To reduce the risk of antimicrobial resistance, eCIPs could increasingly be promoted for use in OPAT clinics, and there should be adequate education and support in their implementation.

Key messages
• Continuous infusion of benzyl penicillin via elastomeric infusors substantially decreases broad-spectrum antibiotic use among erysipelas patients treated at home.
• When erysipelas patients can be treated with outpatient parenteral antibiotic therapy, the use of elastomeric benzyl penicillin infusors is safe and effective and should thus be increasingly promoted.