Intravenous anakinra can achieve experimentally effective concentrations in the central nervous system within a therapeutic time window: results of a dose-ranging study

The naturally occurring antagonist of interleukin-1, IL-1RA, is highly neuroprotective experimentally, shows few adverse effects, and inhibits the systemic acute phase response to stroke. A single regime pilot study showed slow penetration into cerebrospinal fluid (CSF) at experimentally therapeutic concentrations. Twenty-five patients with subarachnoid hemorrhage (SAH) and external ventricular drains were sequentially allocated to five administration regimes, using intravenous bolus doses of 100 to 500 mg and 4 hours intravenous infusions of IL-1RA ranging from 1 to 10 mg per kg per hour. Choice of regimes and timing of plasma and CSF sampling was informed by pharmacometric analysis of pilot study data. Data were analyzed using nonlinear mixed effects modeling. Plasma and CSF concentrations of IL-1RA in all regimes were within the predicted intervals. A 500-mg bolus followed by an intravenous infusion of IL-1RA at 10 mg per kg per hour achieved experimentally therapeutic CSF concentrations of IL-1RA within 45 minutes. Experimentally, neuroprotective CSF concentrations in patients with SAH can be safely achieved within a therapeutic time window. Pharmacokinetic analysis suggests that IL-1RA transport across the blood–CSF barrier in SAH is passive. Identification of the practicality of this delivery regime allows further studies of efficacy of IL-1RA in acute cerebrovascular disease

The relationship between sea surface temperature anomalies, wind and translation speed and North Atlantic tropical cyclone rainfall over ocean and land

There have been increasing losses from freshwater flooding associated with United States (US) landfalling hurricanes in recent years. This study analyses the relationship between sea surface temperature anomalies (SSTA), wind and translation speed and North Atlantic tropical cyclone precipitation (TCP) for the period 1998-2017. Based on our statistical analysis of observation data, for a 1 °C SST increase in the main development region (MDR), there is a 6% increase (not statistically significant) in the TCP rate (mmhr−1) over the Atlantic, which rises to over 40% over land (US states) and appears linked not only to the Clausius-Clapeyron relationship but also to the increase in tropical cyclone (TC) intensity associated with increasing SSTA. Total annual TCP is significantly correlated with the SST in the MDR. Over the Atlantic there is an increase of 116% and over land there is an increase of 140% in total TCP for a 1 °C rise in SST in the MDR. Again, this is linked to the increase in windspeed and the number of TC tracks which also rises with positive SSTAs in the MDR. Our analysis of landfalling TC tracks for nine US states provides a systematic review and highlights how TCP varies by US state. The highest number of landfalls per year are found in Florida, North Carolina and Texas. The median tropical cyclone translation speed is 20.3kmhr−1, although this falls to 16.5 kmhr−1 over land and there is a latitudinal dependence on translation speed. Overall, we find a different TCP response to rising SST over the ocean and land, with the response over land over four times more than the Clausius-Clapeyron rate. The links between SSTA in the MDR and both TCP rate and annual total TCP provide useful insights for seasonal to decadal US flood prediction from TCs

Progress and challenges of demand-led co-produced sub-seasonal-to-seasonal (S2S) climate forecasts in Nigeria

This paper identifies fundamental issues which prevent the effective uptake of climate information services in Nigeria. We propose solutions which involve the extension of short-range (1 to 5 days) forecasts beyond that of medium-range (7 to 15 days) timescales through the operational use of current forecast data as well as improve collaboration and communication with forecast users. Using newly available data to provide seamless operational forecasts from short-term to sub-seasonal timescales, we examine evidence to determine if effective demand-led sub-seasonal-to-seasonal (S2S) climate forecasts can be co-produced. This evidence involves: itemization of forecast products delivered to stakeholders, with their development methodology; enumeration of inferences of forecast products and their influences on decisions taken by stakeholders; user-focused discussions of improvements on co-produced products; and the methods of evaluating the performance of the forecast products. We find that extending the production pipeline of short-range forecast timescales beyond the medium-range, such that the medium-range forecast timescales can be fed into existing tools for applying short-range forecasts, assisted in mitigating the risks of sub-seasonal climate variability on socio-economic activities in Nigeria. We also find that enhancing of collaboration and communication channels between the producers and the forecast product users helps to: enhance the development of user-tailored impact-based forecasts; increases users’ trusts in the forecasts; and, seamlessly improves forecast evaluations. In general, these measures lead to more smooth delivery and increase in uptake of climate information services in Nigeria

Effect of angiotensin-converting enzyme inhibitor and angiotensin receptor blocker initiation on organ support-free days in patients hospitalized with COVID-19

IMPORTANCE Overactivation of the renin-angiotensin system (RAS) may contribute to poor clinical outcomes in patients with COVID-19. Objective To determine whether angiotensin-converting enzyme (ACE) inhibitor or angiotensin receptor blocker (ARB) initiation improves outcomes in patients hospitalized for COVID-19. DESIGN, SETTING, AND PARTICIPANTS In an ongoing, adaptive platform randomized clinical trial, 721 critically ill and 58 non–critically ill hospitalized adults were randomized to receive an RAS inhibitor or control between March 16, 2021, and February 25, 2022, at 69 sites in 7 countries (final follow-up on June 1, 2022). INTERVENTIONS Patients were randomized to receive open-label initiation of an ACE inhibitor (n = 257), ARB (n = 248), ARB in combination with DMX-200 (a chemokine receptor-2 inhibitor; n = 10), or no RAS inhibitor (control; n = 264) for up to 10 days. MAIN OUTCOMES AND MEASURES The primary outcome was organ support–free days, a composite of hospital survival and days alive without cardiovascular or respiratory organ support through 21 days. The primary analysis was a bayesian cumulative logistic model. Odds ratios (ORs) greater than 1 represent improved outcomes. RESULTS On February 25, 2022, enrollment was discontinued due to safety concerns. Among 679 critically ill patients with available primary outcome data, the median age was 56 years and 239 participants (35.2%) were women. Median (IQR) organ support–free days among critically ill patients was 10 (–1 to 16) in the ACE inhibitor group (n = 231), 8 (–1 to 17) in the ARB group (n = 217), and 12 (0 to 17) in the control group (n = 231) (median adjusted odds ratios of 0.77 [95% bayesian credible interval, 0.58-1.06] for improvement for ACE inhibitor and 0.76 [95% credible interval, 0.56-1.05] for ARB compared with control). The posterior probabilities that ACE inhibitors and ARBs worsened organ support–free days compared with control were 94.9% and 95.4%, respectively. Hospital survival occurred in 166 of 231 critically ill participants (71.9%) in the ACE inhibitor group, 152 of 217 (70.0%) in the ARB group, and 182 of 231 (78.8%) in the control group (posterior probabilities that ACE inhibitor and ARB worsened hospital survival compared with control were 95.3% and 98.1%, respectively). CONCLUSIONS AND RELEVANCE In this trial, among critically ill adults with COVID-19, initiation of an ACE inhibitor or ARB did not improve, and likely worsened, clinical outcomes. TRIAL REGISTRATION ClinicalTrials.gov Identifier: NCT0273570

Rainfall distribution and change detection across climatic zones in Nigeria

Nigerian agriculture is mainly rain-fed and basically dependent on the vagaries of weather especially rainfall. Nigeria today has about forty-four (44) weather observation stations which provide measurement of rainfall amount for different locations across the country. Hence, this study investigates change detection in rainfall pattern over each climatic zone of Nigeria. Data were collected for 90 years (1910–1999) period for all the weather observation stations in Nigeria, while a subdivision was made to three (3) non-overlapping climate period of 30 years i.e. 1910–1939, 1940–1969 and 1970–1999. Statistical methods were utilized to justify any change in the average monthly and annual rainfall trend using probability density function and non-parametric tests such as the Pettitt test, Wilcoxon signed-rank test and paired sample test. Results show common change points and transitions from dry to wet (upward shift) in all climatic zones. Statistical tests performed on the data show that rainfall variation over each climatic zone is significant (p<0.05) between pairs of climate periods. Suggestions were therefore made at the end of the study on the use of the contained information for socio-economic improvement and agricultural development of the zones

Methods and software tools for design evaluation in population pharmacokinetics-pharmacodynamics studies.

International audience: Population Pharmacokinetic (PK)-Pharmacodynamic (PD) (PKPD) models are increasingly used in drug development and in academic research. Hence designing efficient studies is an important task. Following the first theoretical work on optimal design for nonlinear mixed effect models, this research theme has grown rapidly. There are now several different software tools that implement an evaluation of the Fisher information matrix for population PKPD. We compared and evaluated five software tools: PFIM, PkStaMP, PopDes, PopED, and POPT. The comparisons were performed using two models: i) a simple one compartment warfarin PK model; ii) a more complex PKPD model for Pegylated-interferon (peg-interferon) with both concentration and response of viral load of hepatitis C virus (HCV) data. The results of the software were compared in terms of the standard error values of the parameters (SE) predicted from the software and the empirical SE values obtained via replicated clinical trial simulation and estimation. For the warfarin PK model and the peg-interferon PKPD model all software gave similar results. Of interest it was seen, for all software, that the simpler approximation to the Fisher information matrix, using the block diagonal matrix, provided predicted SE values that were closer to the empirical SE values than when the more complicated approximation was used (the full matrix). For most PKPD models, using any of the available software tools will provide meaningful results, avoiding cumbersome simulation and allowing design optimisation

The relationship between sea surface temperature anomalies, wind and translation speed and North Atlantic tropical cyclone rainfall over ocean and land

There have been increasing losses from freshwater flooding associated with United States (US) landfalling hurricanes in recent years. This study analyses the relationship between sea surface temperature anomalies (SSTA), wind and translation speed and North Atlantic tropical cyclone precipitation (TCP) for the period 1998-2017. Based on our statistical analysis of observation data, for a 1 °C SST increase in the main development region (MDR), there is a 6% increase (not statistically significant) in the TCP rate (mmhr−1) over the Atlantic, which rises to over 40% over land (US states) and appears linked not only to the Clausius-Clapeyron relationship but also to the increase in tropical cyclone (TC) intensity associated with increasing SSTA. Total annual TCP is significantly correlated with the SST in the MDR. Over the Atlantic there is an increase of 116% and over land there is an increase of 140% in total TCP for a 1 °C rise in SST in the MDR. Again, this is linked to the increase in windspeed and the number of TC tracks which also rises with positive SSTAs in the MDR. Our analysis of landfalling TC tracks for nine US states provides a systematic review and highlights how TCP varies by US state. The highest number of landfalls per year are found in Florida, North Carolina and Texas. The median tropical cyclone translation speed is 20.3kmhr−1, although this falls to 16.5 kmhr−1 over land and there is a latitudinal dependence on translation speed. Overall, we find a different TCP response to rising SST over the ocean and land, with the response over land over four times more than the Clausius-Clapeyron rate. The links between SSTA in the MDR and both TCP rate and annual total TCP provide useful insights for seasonal to decadal US flood prediction from TCs

Verification of multiresolution model forecasts of heavy rainfall events from 23 to 26 August 2017 over Nigeria

The study uses numerical weather prediction models to predict the occurrence of heavy convective rainfall associated with the passage of the African Easterly Wave (AEW) during the period 23–26 August 2017 over Nigeria. Fraction skill score (FSS) and method for object-based diagnostic evaluation (MODE) verification techniques were applied to verify how well the models predict the high-impact event and to demonstrate how these tools can support operational forecasting. Ensemble model forecasts at a convective scale from UK Met Office Unified Model (MetUM) and a one-way nested weather research and forecasting (WRF) model were compared with the integrated multisatellite retrievals for global precipitation measurement (IMERG GPM). The purpose is to examine skills of improved model resolution and ensemble in reproducing rainfall forecasts on useful scales and how the skill varies with spatial scale. WRF 2 and 6 km model forecasts show comparable skill at smaller grid scales. The skill of MetUM improves dramatically when the verification statistics are applied to the ensemble mean of the binary fields of the individual member forecast. The object-based analysis reveals a similar structure as observed, although displaced eastwards. Most improvement occurred for heavier rainfall events associated with the passage of the AEW. WRF 6 km compares reasonably well with WRF 2 km in terms of shape and structure of rainfall underscoring the ability of the model to reasonably represent convection at 6 km horizontal resolution. The ensemble members in MetUM explicitly reproduce convection at 4 km resolution but are displaced at about 166 km behind observed rainfall

Evaluation of the pre-posterior distribution of optimized sampling times for the design of pharmacokinetic studies

Information theoretic methods are often used to design studies that aim to learn about pharmacokinetic and linked pharmacokinetic–pharmacodynamic systems. These design techniques, such as D-optimality, provide the optimum experimental conditions. The performance of the optimum design will depend on the ability of the investigator to comply with the proposed study conditions. However, in clinical settings it is not possible to comply exactly with the optimum design and hence some degree of unplanned suboptimality occurs due to error in the execution of the study. In addition, due to the nonlinear relationship of the parameters of these models to the data, the designs are also locally dependent on an arbitrary choice of a nominal set of parameter values. A design that is robust to both study conditions and uncertainty in the nominal set of parameter values is likely to be of use clinically. We propose an adaptive design strategy to account for both execution error and uncertainty in the parameter values. In this study we investigate designs for a one-compartment first-order pharmacokinetic model. We do this in a Bayesian framework using Markov-chain Monte Carlo (MCMC) methods. We consider log-normal prior distributions on the parameters and investigate several prior distributions on the sampling times. An adaptive design was used to find the sampling window for the current sampling time conditional on the actual times of all previous samples