Background Non-publication, incomplete publication and excessively slow publication of clinical trial outcomes contribute to research waste and can harm patients. While research waste in German academic trials is well documented, research waste in Germany related to a specific disease area across non-commercial and commercial sponsors has not previously been assessed. Methods In this cohort study, we used public records from three clinical trial registries to identify 70 completed or terminated clinical trials involving women with metastatic breast cancer with trial sites in Germany. We then searched registries and the literature for trial outcomes and contacted sponsors about unreported studies. Results We found that 66/70 trials (94.3%) had made their results public. Only 13/70 (18.6%) trials had reported results within one year of completion as recommended by the World Health Organisation (WHO). The outcomes of 4/70 trials (5.7%) had not been made public at all, but only one of those trials had recruited a significant number of patients. Conclusions Discussions about research waste in clinical trials commonly focus on weakly designed or unreported trials. We believe that late reporting of results is another important form of research waste. In addition, a discussion regarding the appropriate ethical and legal rules for reporting the results of terminated trials might add value. German legislation now requires sponsors to upload the results of some clinical trials onto a trial registry within one year of trial completion, but these laws only cover around half of all trials. Our findings highlight the potential benefits of extending the scope of national legislation to cover all interventional clinical trials involving German patients.

Solvents prepared from natural terpenes (menthol and thymol), as H-bond acceptors, and a series of organic acids (chain lengths of 8, 10, and 14 C atoms), as H-bond donors, were characterized and tested as reaction media for liquid–liquid extraction purposes. Due to their high hydrophobicity, they seem to be promising alternatives to conventional (nonpolar and toxic) solvents, since they possess relatively less toxic, less volatile, and consequently, more environmentally friendly characteristics. Assuming that the equilibrium is established between solvent and analyte during a ligandless procedure, it can be concluded that those nonpolar solvents can efficiently extract nonpolar analytes from the aqueous environment. Previous investigations showed a wide range of applications, including their use as solvents in extractions of metal cations, small molecules, and bioactive compounds for food and pharmaceutical applications. In this work, hydrophobic solvents based on natural terpenes, which showed chemical stability and desirable physicochemical and thermal properties, were chosen as potential reaction media in the liquid–liquid extraction (LLE) procedure for Pb(II) removal from aqueous solutions. Low viscosities and high hydrophobicities of prepared solvents were confirmed as desirable properties for their application. Extraction parameters were optimized, and chosen solvents were applied. The results showed satisfactory extraction efficiencies in simple and fast procedures, followed by low solvent consumption. The best results (98%) were obtained by the thymol-based solvent, thymol–decanoic acid (Thy-DecA) 1:1, followed by L-menthol-based solvents: menthol–octanoic acid (Men-OctA) 1:1 with 97% and menthol–decanoic acid (Men-DecA) 1:1 with 94.3% efficiency.

An increasing number of countries are investigating options to stop the spread of the emerging zoonotic infection Salmonella (S.) Dublin, which mainly spreads among bovines and with cattle manure. Detailed surveillance and cattle movement data from an 11-year period in Denmark provided an opportunity to gain new knowledge for mitigation options through a combined social network and simulation modeling approach. The analysis revealed similar network trends for non-infected and infected cattle farms despite stringent cattle movement restrictions imposed on infected farms in the national control program. The strongest predictive factor for farms becoming infected was their cattle movement activities in the previous month, with twice the effect of local transmission. The simulation model indicated an endemic S. Dublin occurrence, with peaks in outbreak probabilities and sizes around observed cattle movement activities. Therefore, pre- and post-movement measures within a 1-mo time-window may help reduce S. Dublin spread.

ABSTRACT Context: Since beginning of the coronavirus disease (COVID-19) it became clear that severe forms of this infection have primarily affected patients with chronic conditions. Aims: The aim of the study was to explore clinical and epidemiological characteristics associated with COVID 19 outcomes. Settings and Design: The retrospective observational study included 40,692 citizens of Banja Luka County, Bosnia and Herzegovina, who were confirmed as reverse transcriptase polymerase chain reaction (RT-PCR) positive on COVID-19 at a primary healthcare centre from March 2020 to September 2022. Methods and Materials: Epidemiological data were obtained from Web-Medic medical records of patients. The COVID-19 data were obtained from COVID-19 data sheets comprised of patients’ RT-PCR testing forms, surveillance forms for severe acute respiratory syndrome coronavirus-2 status, and a map of their positive and isolated contacts. Statistical Analysis Used: Differences regarding the distributions of patients between groups were analysed using the Pearson chi-square test and Mantel-Haenszel chi-square test for trends, while differences in mean values were compared using an independent sample t-test. Results: The average age of hospitalised patients was significantly higher compared to the age of non-hospitalised patients (P < 0.001). The average age of patients with lethal outcomes was nearly twice as high in comparison to patients with non-lethal outcomes (P < 0.001). Male patients had a higher hospitalization and mortality rate (P < 0.001). The highest hospitalization rate was in patients with chronic renal failure (CRF), diabetes and cardiovascular diseases (CVDs), while the death rate was the highest among patients with CRF and hearth comorbidities. Patients with fatigue and appetite loss had a higher percentage of lethal outcomes. Vaccinated patients had a significantly lower rate of lethal outcome. Conclusions: Clinical symptoms, signs and outcomes, are posing as predictive parameters for further management of COVID-19. Vaccination has an important role in the clinical outcomes of COVID-19.

Prediction of short-term mortality in patients with acute decompensation of liver cirrhosis could be improved. We aimed to develop and validate two machine learning (ML) models for predicting 28-day and 90-day mortality in patients hospitalized with acute decompensated liver cirrhosis. We trained two artificial neural network (ANN)-based ML models using a training sample of 165 out of 290 (56.9%) patients, and then tested their predictive performance against Model of End-stage Liver Disease-Sodium (MELD-Na) and MELD 3.0 scores using a different validation sample of 125 out of 290 (43.1%) patients. The area under the ROC curve (AUC) for predicting 28-day mortality for the ML model was 0.811 (95%CI: 0.714- 0.907; p < 0.001), while the AUC for the MELD-Na score was 0.577 (95%CI: 0.435–0.720; p = 0.226) and for MELD 3.0 was 0.600 (95%CI: 0.462–0.739; p = 0.117). The area under the ROC curve (AUC) for predicting 90-day mortality for the ML model was 0.839 (95%CI: 0.776- 0.884; p < 0.001), while the AUC for the MELD-Na score was 0.682 (95%CI: 0.575–0.790; p = 0.002) and for MELD 3.0 was 0.703 (95%CI: 0.590–0.816; p < 0.001). Our study demonstrates that ML-based models for predicting short-term mortality in patients with acute decompensation of liver cirrhosis perform significantly better than MELD-Na and MELD 3.0 scores in a validation cohort.