Dimethyl fumarate in patients admitted to hospital with COVID-19 (RECOVERY): a randomised, controlled, open-label, platform trial

Dimethyl fumarate (DMF) inhibits inflammasome-mediated inflammation and has been proposed as a treatment for patients hospitalised with COVID-19. This randomised, controlled, open-label platform trial (Randomised Evaluation of COVID-19 Therapy [RECOVERY]), is assessing multiple treatments in patients hospitalised for COVID-19 (NCT04381936, ISRCTN50189673). In this assessment of DMF performed at 27 UK hospitals, adults were randomly allocated (1:1) to either usual standard of care alone or usual standard of care plus DMF. The primary outcome was clinical status on day 5 measured on a seven-point ordinal scale. Secondary outcomes were time to sustained improvement in clinical status, time to discharge, day 5 peripheral blood oxygenation, day 5 C-reactive protein, and improvement in day 10 clinical status. Between 2 March 2021 and 18 November 2021, 713 patients were enroled in the DMF evaluation, of whom 356 were randomly allocated to receive usual care plus DMF, and 357 to usual care alone. 95% of patients received corticosteroids as part of routine care. There was no evidence of a beneficial effect of DMF on clinical status at day 5 (common odds ratio of unfavourable outcome 1.12; 95% CI 0.86-1.47; p = 0.40). There was no significant effect of DMF on any secondary outcome

Models for zero-inflated count data using the Neyman type A distribution

We explore the possibility of modelling zero-inflated count data using the Neyman type A distribution. We extend three parameterisations of the Neyman type A distribution to allow their parameters to depend on covariates. We develop models which relate counts of Leadbeater's possums to various habitat variables to illustrate the methodology. Half-normal plots (Vieira et al, 2000) are constructed for each model to explore the quality fo the fit. We then formally compare the Neyman type A models using the method of Cox (1961, 1962) to test nonnested hypotheses. Finally we compare each of the Neyman type A models with a model from a competing family, the conditional Poisson mode

Eight new T4.5-T7.5 dwarfs discovered in the UKIDSS large area survey data release 1

The definitive version is available at www.blackwell-synergy.com Copyright Blackwell Publishing DOI : 10.1111/j.1365-2966.2007.12023.xPeer reviewe

Supplementary Material for: Critically Ill Patients Requiring Acute Renal Replacement Therapy Are at an Increased Risk of Long-Term Renal Dysfunction, but Rarely Receive Specialist Nephrology Follow-Up

<b><i>Background:</i></b> Episodes of acute kidney injury (AKI) have been associated with the development of chronic kidney disease (CKD). However, follow-up pathways for patients who have survived AKI complicating critical illness are not well established. We hypothesised that patients who had AKI requiring renal replacement therapy (RRT) in intensive care are at risk of CKD, but are rarely referred for nephrology follow-up at hospital discharge. <b><i>Methods:</i></b> We performed a retrospective analysis of all patients who survived AKI requiring renal replacement therapy in intensive care units (ICUs) in the East London region, examining renal function at baseline, hospital discharge and 3-6 months follow-up. We excluded patients who were known to renal services prior to index admission. <b><i>Results:</i></b> From 5,544 critical care admissions, we identified 219 patients who survived to be discharged, having undergone RRT for AKI, that were not previously known to renal services. Of these, 124 (57%) had creatinine measured within 3-6 months after discharge, 104 having a pre-morbid baseline for comparison. Only 26 patients (12%) received specialist nephrology follow-up. At 3-6 months follow-up, the estimated glomerular filtration rate was significantly lower than baseline (48 vs. 60 ml/min/1.73 m²; p < 0.001), with the prevalence of CKD stage III-V rising from 49 to 70% (p < 0.001). <b><i>Conclusions:</i></b> Follow-up of patients who required RRT for AKI in ICU is inconsistent despite evidence of a significant increase in the prevalence of CKD. There is strong justification for the development of robust pathways to identify survivors of AKI in order to detect and manage CKD and its complications