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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.
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: Bipolar disorder is associated with circadian disruption and a high risk of suicidal behavior. In a previous exploratory study of patients with bipolar I disorder, we found that a history of suicide attempts was associated with differences between winter and summer levels of solar insolation. The purpose of this study was to confirm this finding using international data from 42% more collection sites and 25% more countries. Methods: Data analyzed were from 71 prior and new collection sites in 40 countries at a wide range of latitudes. The analysis included 4876 patients with bipolar I disorder, 45% more data than previously analyzed. Of the patients, 1496 (30.7%) had a history of suicide attempt. Solar insolation data, the amount of the sun’s electromagnetic energy striking the surface of the earth, was obtained for each onset location (479 locations in 64 countries). Results: This analysis confirmed the results of the exploratory study with the same best model and slightly better statistical significance. There was a significant inverse association between a history of suicide attempts and the ratio of mean winter insolation to mean summer insolation (mean winter insolation/mean summer insolation). This ratio is largest near the equator which has little change in solar insolation over the year, and smallest near the poles where the winter insolation is very small compared to the summer insolation. Other variables in the model associated with an increased risk of suicide attempts were a history of alcohol or substance abuse, female gender, and younger birth cohort. The winter/summer insolation ratio was also replaced with the ratio of minimum mean monthly insolation to the maximum mean monthly insolation to accommodate insolation patterns in the tropics, and nearly identical results were found. All estimated coefficients were significant at p < 0.01. Conclusion: A large change in solar insolation, both between winter and summer and between the minimum and maximum monthly values, may increase the risk of suicide attempts in bipolar I disorder. With frequent circadian rhythm dysfunction and suicidal behavior in bipolar disorder, greater understanding of the optimal roles of daylight and electric lighting in circadian entrainment is needed.
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.
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.
Improving spatial accessibility to hospitals is a major task for health care systems which can be facilitated using recent methodological improvements of spatial accessibility measures. We used the integrated floating catchment area (iFCA) method to analyze spatial accessibility of general inpatient care (internal medicine, surgery and neurology) on national level in Germany determining an accessibility index (AI) by integrating distances, hospital beds and morbidity data. The analysis of 358 million distances between hospitals and population locations revealed clusters of lower accessibility indices in areas in north east Germany. There was a correlation of urbanity and accessibility up to r = 0.31 (p < 0.001). Furthermore, 10% of the population lived in areas with significant clusters of low spatial accessibility for internal medicine and surgery (neurology: 20%). The analysis revealed the highest accessibility for heart failure (AI = 7.33) and the lowest accessibility for stroke (AI = 0.69). The method applied proofed to reveal important aspects of spatial accessibility i.e. geographic variations that need to be addressed. However, for the majority of the German population, accessibility of general inpatient care was either high or at least not significantly low, which suggests rather adequate allocation of hospital resources for most parts of Germany.
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.
Background: The adequate allocation of inpatient care resources requires assumptions about the need for health care and how this need will be met. However, in current practice, these assumptions are often based on outdated methods (e.g. Hill-Burton Formula). This study evaluated floating catchment area (FCA) methods, which have been applied as measures of spatial accessibility, focusing on their ability to predict the need for health care in the inpatient sector in Germany.
Methods: We tested three FCA methods (enhanced (E2SFCA), modified (M2SFCA) and integrated (iFCA)) for their accuracy in predicting hospital visits regarding six medical diagnoses (atrial flutter/fibrillation, heart failure, femoral fracture, gonarthrosis, stroke, and epilepsy) on national level in Germany. We further used the closest provider approach for benchmark purposes. The predicted visits were compared with the actual visits for all six diagnoses using a correlation analysis and a maximum error from the actual visits of ± 5%, ± 10% and ± 15%.
Results: The analysis of 229 million distances between hospitals and population locations revealed a high and significant correlation of predicted with actual visits for all three FCA methods across all six diagnoses up to ρ = 0.79 (p < 0.001). Overall, all FCA methods showed a substantially higher correlation with actual hospital visits compared to the closest provider approach (up to ρ = 0.51; p < 0.001). Allowing a 5% error of the absolute values, the analysis revealed up to 13.4% correctly predicted hospital visits using the FCA methods (15% error: up to 32.5% correctly predicted hospital). Finally, the potential of the FCA methods could be revealed by using the actual hospital visits as the measure of hospital attractiveness, which returned very strong correlations with the actual hospital visits up to ρ = 0.99 (p < 0.001).
Conclusion: We were able to demonstrate the impact of FCA measures regarding the prediction of hospital visits in non-emergency settings, and their superiority over commonly used methods (i.e. closest provider). However, hospital beds were inadequate as the measure of hospital attractiveness resulting in low accuracy of predicted hospital visits. More reliable measures must be integrated within the proposed methods. Still, this study strengthens the possibilities of FCA methods in health care planning beyond their original application in measuring spatial accessibility.
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.
Background: Immigration has a strong impact on the development of health systems, medicine and science worldwide. Therefore, this article provides a descriptive study on the overall research output.
Methods: Utilizing the scientific database Web of Science, data research was performed. The gathered bibliometric data was analyzed using the established platform NewQIS, a benchmarking system to visualize research quantity and quality indices.
Findings: Between 1900 and 2016 a total of 6763 articles on immigration were retrieved and analyzed. 86 different countries participated in the publications. Quantitatively the United States followed by Canada and Spain were prominent regarding the article numbers. On comparing by additionally taking the population size into account, Israel followed by Sweden and Norway showed the highest performance. The main releasing journals are the Public Health Reports, the Journal of Immigrant and Minority Health and Social Science & Medicine. Over the decades, an increasing number of Public, Environmental & Occupational Health articles can be recognized which finally forms the mainly used subject area.
Conclusion: Considerably increasing scientific work on immigration cannot only be explained by the general increase of scientific work but is also owed to the latest development with increased mobility, worldwide crises and the need of flight and migration. Especially countries with a good economic situation are highly affected by immigrants and prominent in their publication output on immigration, since the countries’ publication effort is connected with the appointed expenditures for research and development. Remarkable numbers of immigrants throughout Europe compel medical professionals to consider neglected diseases, requires the public health system to restructure itself and finally promotes science.