Treatment with tocilizumab or corticosteroids for COVID-19 patients with hyperinflammatory state: a multicentre cohort study (SAM-COVID-19)

Objectives: The objective of this study was to estimate the association between tocilizumab or corticosteroids and the risk of intubation or death in patients with coronavirus disease 19 (COVID-19) with a hyperinflammatory state according to clinical and laboratory parameters. Methods: A cohort study was performed in 60 Spanish hospitals including 778 patients with COVID-19 and clinical and laboratory data indicative of a hyperinflammatory state. Treatment was mainly with tocilizumab, an intermediate-high dose of corticosteroids (IHDC), a pulse dose of corticosteroids (PDC), combination therapy, or no treatment. Primary outcome was intubation or death; follow-up was 21 days. Propensity score-adjusted estimations using Cox regression (logistic regression if needed) were calculated. Propensity scores were used as confounders, matching variables and for the inverse probability of treatment weights (IPTWs). Results: In all, 88, 117, 78 and 151 patients treated with tocilizumab, IHDC, PDC, and combination therapy, respectively, were compared with 344 untreated patients. The primary endpoint occurred in 10 (11.4%), 27 (23.1%), 12 (15.4%), 40 (25.6%) and 69 (21.1%), respectively. The IPTW-based hazard ratios (odds ratio for combination therapy) for the primary endpoint were 0.32 (95%CI 0.22-0.47; p < 0.001) for tocilizumab, 0.82 (0.71-1.30; p 0.82) for IHDC, 0.61 (0.43-0.86; p 0.006) for PDC, and 1.17 (0.86-1.58; p 0.30) for combination therapy. Other applications of the propensity score provided similar results, but were not significant for PDC. Tocilizumab was also associated with lower hazard of death alone in IPTW analysis (0.07; 0.02-0.17; p < 0.001). Conclusions: Tocilizumab might be useful in COVID-19 patients with a hyperinflammatory state and should be prioritized for randomized trials in this situatio

Pharmaceutical residues in stranded dolphins in the Bay of Biscay

There is a growing concern about the presence of pharmaceuticals on all trophic levels of the 3 aquatic environment. The presence of pharmaceuticals in the marine environment, which is the 4 final receiver of the continental water including treated wastewater, has been much less 5 investigated than in freshwater. Marine mammals are very suitable sentinel species of the 6 marine environment because they often feed at high trophic levels, have unique fat stores and 7 long lifespan. Small delphinids in particular serve as excellent sentinel species for contamination 8 in the marine environment worldwide. To the best of our knowledge, no pharmaceuticals have 9 been detected or reported in dolphins so far. 10 In the present study, muscle, liver and blubbler samples from four common dolphins (Delphinus 11 delphis) and six striped dolphins (Stenella coeruleoalba) stranded along the Basque Coast were 12 collected. A total of 95 pharmaceuticals based on detectability and predicted ability to 13 bioaccumulate in fish were included in the analysis. 14 At least one pharmaceutical was found in 70% of the individuals. Only three of the 95 monitored 15 pharmaceuticals (orphenadrine, pizotifen, and promethazine) were detected in dolphin ́s tissues 16 (liver or blubber) at very low concentrations (<1ng/g). 17 In this study we also highlight the gap in the knowledge regarding the study organisms and 18 marine environments with respect to pharmaceutical pollution, which demands further 19 research to understand the threat pharmaceuticals might pose for these apex predators.Funding support from Fundación Vital & Ayuntamiento de Vitoria-Gasteiz to GO and the Swedish Research Council Formas 2020-01052 to D.C. and the Basque Government through Consolidated Research Group GIC IT1743-22 to X.L

Discovering HIV related information by means of association rules and machine learning

Acquired immunodeficiency syndrome (AIDS) is still one of the main health problems worldwide. It is therefore essential to keep making progress in improving the prognosis and quality of life of affected patients. One way to advance along this pathway is to uncover connections between other disorders associated with HIV/AIDS-so that they can be anticipated and possibly mitigated. We propose to achieve this by using Association Rules (ARs). They allow us to represent the dependencies between a number of diseases and other specific diseases. However, classical techniques systematically generate every AR meeting some minimal conditions on data frequency, hence generating a vast amount of uninteresting ARs, which need to be filtered out. The lack of manually annotated ARs has favored unsupervised filtering, even though they produce limited results. In this paper, we propose a semi-supervised system, able to identify relevant ARs among HIV-related diseases with a minimal amount of annotated training data. Our system has been able to extract a good number of relationships between HIV-related diseases that have been previously detected in the literature but are scattered and are often little known. Furthermore, a number of plausible new relationships have shown up which deserve further investigation by qualified medical experts