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The Education Against Tobacco (EAT) network delivers smoking prevention advice in secondary schools, typically using the mirroring approach (i.e., a "selfie" altered with a face-aging app and shared with a class). In November 2017, however, the German assembly of EAT opted to expand its remit to include nursing students. To assess the transferability of the existing approach, we implemented it with the self-developed face-aging app "Smokerface" (=mixed − methods approach) in six nursing schools. Anonymous questionnaires were used to assess the perceptions of 197 students (age 18–40 years; 83.8% female; 26.4% smokers; 23.3% daily smokers) collecting qualitative and quantitative data for our cross-sectional study. Most students perceived the intervention to be fun (73.3%), but a minority disagreed that their own animated selfie (25.9%) or the reaction of their peers (29.5%) had motivated them to stop smoking. The impact on motivation not to smoke was considerably lower than experienced with seventh graders (63.2% vs. 42.0%; notably, more smokers also disagreed (45.1%) than agreed (23.5%) with this statement. Agreement rates on the motivation not to smoke item were higher in females than in males and in year 2–3 than in year 1 students. Potential improvements included greater focus on pathology (29%) and discussing external factors (26%). Overall, the intervention seemed to be appealing for nursing students
Background: Biological psychiatry aims to understand mental disorders in terms of altered neurobiological pathways. However, for one of the most prevalent and disabling mental disorders, Major Depressive Disorder (MDD), patients only marginally differ from healthy individuals on the group-level. Whether Precision Psychiatry can solve this discrepancy and provide specific, reliable biomarkers remains unclear as current Machine Learning (ML) studies suffer from shortcomings pertaining to methods and data, which lead to substantial over-as well as underestimation of true model accuracy.
Methods: Addressing these issues, we quantify classification accuracy on a single-subject level in N=1,801 patients with MDD and healthy controls employing an extensive multivariate approach across a comprehensive range of neuroimaging modalities in a well-curated cohort, including structural and functional Magnetic Resonance Imaging, Diffusion Tensor Imaging as well as a polygenic risk score for depression.
Findings Training and testing a total of 2.4 million ML models, we find accuracies for diagnostic classification between 48.1% and 62.0%. Multimodal data integration of all neuroimaging modalities does not improve model performance. Similarly, training ML models on individuals stratified based on age, sex, or remission status does not lead to better classification. Even under simulated conditions of perfect reliability, performance does not substantially improve. Importantly, model error analysis identifies symptom severity as one potential target for MDD subgroup identification.
Interpretation: Although multivariate neuroimaging markers increase predictive power compared to univariate analyses, single-subject classification – even under conditions of extensive, best-practice Machine Learning optimization in a large, harmonized sample of patients diagnosed using state-of-the-art clinical assessments – does not reach clinically relevant performance. Based on this evidence, we sketch a course of action for Precision Psychiatry and future MDD biomarker research.
Systematic reviews represent the core and backbone of evidence-based medicine (EBM) strategies in all fields of medicine. In order to depict a first global sketch of the international efforts in the Cochrane database systematic reviews (CDSR), we analyzed the systematic reviews of the Cochrane database. Our global maps of systematic reviewing offer intriguing structural insights into the world of EBM strategies. They demonstrate that for the CDSR, the UK and Commonwealth countries take the lead position. Since patients, care providers and health systems all over the world benefit from systematic reviewing, institutions in other countries should increase their commitment.
Purpose: The coronavirus disease 2019 (COVID-19) poses major challenges to health-care systems worldwide. This pandemic demonstrates the importance of timely access to intensive care and, therefore, this study aims to explore the accessibility of intensive care beds in 14 European countries and its impact on the COVID-19 case fatality ratio (CFR).
Methods: We examined access to intensive care beds by deriving (1) a regional ratio of intensive care beds to 100,000 population capita (accessibility index, AI) and (2) the distance to the closest intensive care unit. The cross-sectional analysis was performed at a 5-by-5 km spatial resolution and results were summarized nationally for 14 European countries. The relationship between AI and CFR was analyzed at the regional level.
Results: We found national-level differences in the levels of access to intensive care beds. The AI was highest in Germany (AI = 35.3), followed by Estonia (AI = 33.5) and Austria (AI = 26.4), and lowest in Sweden (AI = 5) and Denmark (AI = 6.4). The average travel distance to the closest hospital was highest in Croatia (25.3 min by car) and lowest in Luxembourg (9.1 min). Subnational results illustrate that capacity was associated with population density and national-level inventories. The correlation analysis revealed a negative correlation of ICU accessibility and COVID-19 CFR (r = − 0.57; p < 0.001).
Conclusion: Geographical access to intensive care beds varies significantly across European countries and low ICU accessibility was associated with a higher proportion of COVID-19 deaths to cases (CFR). Important differences in access are due to the sizes of national resource inventories and the distribution of health-care facilities relative to the human population. Our findings provide a resource for officials planning public health responses beyond the current COVID-19 pandemic, such as identifying potential locations suitable for temporary facilities or establishing logistical plans for moving severely ill patients to facilities with available beds.
Background: Health care accessibility is known to differ geographically. With this study we focused on analysing accessibility of general and specialized obstetric units in England and Germany with regard to urbanity, area deprivation and neonatal outcome using routine data.
Methods: We used a floating catchment area method to measure obstetric care accessibility, the degree of urbanization (DEGURBA) to measure urbanity and the index of multiple deprivation to measure area deprivation.
Results: Accessibility of general obstetric units was significantly higher in Germany compared to England (accessibility index of 16.2 vs. 11.6; p < 0.001), whereas accessibility of specialized obstetric units was higher in England (accessibility index for highest level of care of 0.235 vs. 0.002; p < 0.001). We further demonstrated higher obstetric accessibility for people living in less deprived areas in Germany (r = − 0.31; p < 0.001) whereas no correlation was present in England. There were also urban–rural disparities present, with higher accessibility in urban areas in both countries (r = 0.37–0.39; p < 0.001). The analysis did not show that accessibility affected neonatal outcomes. Finally, our computer generated model for obstetric care provider demand in terms of birth counts showed a very strong correlation with actual birth counts at obstetric units (r = 0.91–0.95; p < 0.001).
Conclusion: In Germany the focus of obstetric care seemed to be put on general obstetric units leading to higher accessibility compared to England. Regarding specialized obstetric care the focus in Germany was put on high level units whereas in England obstetric care seems to be more balanced between the different levels of care with larger units on average leading to higher accessibility.
Background: There are several ways to conduct a job task analysis in medical work environments including pencil-paper observations, interviews and questionnaires. However these methods implicate bias problems such as high inter-individual deviations and risks of misjudgement. Computer-based observation helps to reduce these problems. The aim of this paper is to give an overview of the development process of a computer-based job task analysis instrument for real-time observations to quantify the job tasks performed by physicians working in different medical settings. In addition reliability and validity data of this instrument will be demonstrated.
Methods: This instrument was developed in consequential steps. First, lists comprising tasks performed by physicians in different care settings were classified. Afterwards content validity of task lists was proved. After establishing the final task categories, computer software was programmed and implemented in a mobile personal computer. At least inter-observer reliability was evaluated. Two trained observers recorded simultaneously tasks of the same physician.
Results: Content validity of the task lists was confirmed by observations and experienced specialists of each medical area. Development process of the job task analysis instrument was completed successfully. Simultaneous records showed adequate interrater reliability.
Conclusion: Initial results of this analysis supported the validity and reliability of this developed method for assessing physicians' working routines as well as organizational context factors. Based on results using this method, possible improvements for health professionals' work organisation can be identified.
Objectives This study wants to assess the cost-effectiveness of unmanned aerial vehicles (UAV) equipped with automated external defibrillators (AED) in out-of-hospital cardiac arrests (OHCA). Especially in rural areas with longer response times of emergency medical services (EMS) early lay defibrillation could lead to a significant higher survival in OHCA.
Participants 3296 emergency medical stations in Germany.
Setting Rural areas in Germany.
Primary and secondary outcome measures Three UAV networks providing 80%, 90% or 100% coverage for rural areas lacking timely access to EMS (ie, time-to-defibrillation: >10 min) were developed using a location allocation analysis. For each UAV network, primary outcome was the cost-effectiveness using the incremental cost-effectiveness ratio (ICER) calculated by the ratio of financial costs to additional life years gained compared with current EMS.
Results Current EMS with 3926 emergency stations was able to gain 1224 life years on annual average in the study area. The UAV network providing 100% coverage consisted of 1933 UAV with average annual costs of €43.5 million and 1845 additional life years gained on annual average (ICER: €23 568). The UAV network providing 90% coverage consisted of 1074 UAV with average annual costs of €24.2 million and 1661 additional life years gained on annual average (ICER: €14 548). The UAV network providing 80% coverage consisted of 798 UAV with average annual costs of €18.0 million and 1477 additional life years gained on annual average (ICER: €12 158).
Conclusion These results reveal the relevant life-saving potential of all modelled UAV networks. Furthermore, all analysed UAV networks could be deemed cost-effective. However, real-life applications are needed to validate the findings.
Background: Ever since it was discovered that zoophilic vectors can transmit malaria, zooprophylaxis has been used to prevent the disease. However, zoopotentiation has also been observed. Thus, the presence of livestock has been widely accepted as an important variable for the prevalence and risk of malaria, but the effectiveness of zooprophylaxis remained subject to debate. This study aims to critically analyse the effects of the presence of livestock on malaria prevalence using a large dataset from Indonesia.
Methods: This study is based on data from the Indonesia Basic Health Research ("Riskesdas") cross-sectional survey of 2007 organized by the National Institute of Health Research and Development of Indonesia’s Ministry of Health. The subset of data used in the present study included 259,885 research participants who reside in the rural areas of 176 regencies throughout the 15 provinces of Indonesia where the prevalence of malaria is higher than the national average. The variable "existence of livestock" and other independent demographic, social and behavioural variables were tested as potential determinants for malaria prevalence by multivariate logistic regressions.
Results: Raising medium-sized animals in the house was a significant predictor of malaria prevalence (OR = 2.980; 95% CI 2.348–3.782, P < 0.001) when compared to keeping such animals outside of the house (OR = 1.713; 95% CI 1.515–1.937, P < 0.001). After adjusting for gender, age, access to community health facility, sewage canal condition, use of mosquito nets and insecticide-treated bed nets, the participants who raised medium-sized animals inside their homes were 2.8 times more likely to contract malaria than respondents who did not (adjusted odds ratio = 2.809; 95% CI 2.207–3.575; P < 0.001).
Conclusions: The results of this study highlight the importance of livestock for malaria transmission, suggesting that keeping livestock in the house contributes to malaria risk rather than prophylaxis in Indonesia. Livestock-based interventions should therefore play a significant role in the implementation of malaria control programmes, and focus on households with a high proportion of medium-sized animals in rural areas. The implementation of a "One Health" strategy to eliminate malaria in Indonesia by 2030 is strongly recommended.
Limbic encephalitis (LE) is an autoimmune syndrome often associated with temporal lobe epilepsy. Recent research suggests that particular structural changes in LE depend on the type of the associated antibody and occur in both mesiotemporal gray matter and white matter regions. However, it remains questionable to what degree conventional diffusion tensor imaging (DTI)-methods reflect alterations in white matter microstructure, since these methods do not account for crossing fibers. To address this methodological shortcoming, we applied fixel-based analysis as a novel technique modeling distinct fiber populations. For our study, 19 patients with LE associated with autoantibodies against glutamic acid decarboxylase 65 (GAD-LE, mean age = 35.9 years, 11 females), 4 patients with LE associated with autoantibodies against leucine-rich glioma-inactivated 1 (LGI1-LE, mean age = 63.3 years, 2 females), 5 patients with LE associated with contactin-associated protein-like 2 (CASPR2, mean age = 57.4, 0 females), 20 age- and gender-matched control patients with hippocampal sclerosis (19 GAD-LE control patients: mean age = 35.1 years, 11 females; 4 LGI1-LE control patients: mean age = 52.6 years, 2 females; 5 CASPR2-LE control patients: mean age = 42.7 years, 0 females; 10 patients are included in more than one group) and 33 age- and gender-matched healthy control subjects (19 GAD-LE healthy controls: mean age = 34.6 years, 11 females; 8 LGI1-LE healthy controls: mean age = 57.0 years, 4 females, 10 CASPR2-LE healthy controls: mean age = 57.2 years, 0 females; 4 subjects are included in more than one group) underwent structural imaging and DTI at 3 T and neuropsychological testing. Patient images were oriented according to lateralization in EEG resulting in an affected and unaffected hemisphere. Fixel-based metrics fiber density (FD), fiber cross-section (FC), and fiber density and cross-section (FDC = FD · FC) were calculated to retrieve information about white matter integrity both on the micro- and the macroscale. As compared to healthy controls, patients with GAD-LE showed significantly (family-wise error-corrected, p < 0.05) lower FDC in the superior longitudinal fascicle bilaterally and in the isthmus of the corpus callosum. In CASPR2-LE, lower FDC in the superior longitudinal fascicle was only present in the affected hemisphere. In LGI1-LE, we did not find any white matter alteration of the superior longitudinal fascicle. In an explorative tract-based correlation analysis within the GAD-LE group, only a correlation between the left/right ratio of FC values of the superior longitudinal fascicle and verbal memory performance (R = 0.64, Holm-Bonferroni corrected p < 0.048) remained significant after correcting for multiple comparisons. Our results underscore the concept of LE as a disease comprising a broad and heterogeneous group of entities and contribute novel aspects to the pathomechanistic understanding of this disease that may strengthen the role of MRI in the diagnosis of LE.
URPOSE: Today, the majority of medical graduates in countries such as the UK, the US or Germany are female. This poses a major problem for workforce planning especially in urology. We here use first the first time the previously established Brüggmann Groneberg (BG) index to assess if female academic career options advance in urology.
METHODS: Different operating parameters (student population, urology specialist population, urology chair female:male (f:m) ratio) were collected from the Federal Office of Statistics, the Federal Chamber of Physicians and the medical faculties of 36 German universities. Four time points were monitored (2000, 2005, 2010 and 2015). From these data, female to male (f:m) ratios and the recently established career advancement (BG) index have been calculated.
RESULTS: The German hospital urology specialists' f:m ratios were 0.257 (499 female vs. 1944 male) for 2015, 0.195 for 2010, 0.133 for 2005 and 0.12 for 2000. The career advancement (BG) index was 0.0007 for 2000, 0,0005 for 2005, 0.094 for 2010 and 0.073 for 2015. The decrease from 2010 to 2015 was due to an increase in the f:m ratio of hospital urologists and female medical students.
CONCLUSION: The BG index clearly illustrated that there is an urgent need for special academic career funding programs to counteract gender problems in urology. The BG index has been shown to be an excellent tool to assess female academic career options and will be very helpful to assess and document positive or negative changes in the next decades.