Mapping Potential Timing of Ice Algal Blooms From Satellite

As Arctic sea ice and its overlying snow cover thin, more light penetrates into the ice and upper ocean, shifting the phenology of algal growth within the bottom of sea ice, with cascading impacts on higher trophic levels of the Arctic marine ecosystem. While field data or autonomous observatories provide direct measurements of the coupled sea ice-algal system, they are limited in space and time. Satellite observations of key sea ice variables that control the amount of light penetrating through sea ice offer the possibility to map the under-ice light field across the entire Arctic basin. This study provides the first satellite-based estimates of potential sea ice-associated algal bloom onset dates since the launch of CryoSat-2 and explores how a changing snowpack may have shifted bloom onset timings over the last four decades

The role of platelet rich plasma in musculoskeletal science

The idea of using platelet rich plasma (PRP) in medicine has been around since the 1970s. It is only more recently that its use has been employed in the area of musculoskeletal science. Platelet rich plasma in this area has received much media attention being used by many celebrity sports athletes for musculoskeletal injuries. Therefore it is important for the musculoskeletal practitioner to be aware of the concepts surrounding its use and application. In this article we cover what platelet rich plasma is, how it is prepared and administered, its potential clinical application, and what the current literature discusses in the various areas of musculoskeletal science

Comparative effectiveness of sotrovimab and molnupiravir for preventing severe COVID-19 outcomes in patients on kidney replacement therapy:observational study using OpenSAFELY-UKRR and SRR databases

Background: Due to limited inclusion of patients on kidney replacement therapy (KRT) in clinical trials, the effectiveness of COVID-19 therapies in this population remains unclear. We sought to address this by comparing the effectiveness of sotrovimab against molnupiravir, two commonly used treatments for non-hospitalised KRT patients with COVID-19 in the UK.Methods: With the approval of NHS England we used routine clinical data from 24 million patients in England within the OpenSAFELY-TPP platform linked to the UK Renal Registry (UKRR) to identify patients on KRT. Cox proportional hazards model was used to estimate hazard ratios of sotrovimab vs. molnupiravir with regards to COVID-19 related hospitalisation or deaths in the subsequent 28 days. We also conducted a complementary analysis using data from the Scottish Renal Registry (SRR).Results: Among the 2367 kidney patients treated with sotrovimab (n=1852) or molnupiravir (n=515) between December 16, 2021 and August 1, 2022 in England, 38 cases (1.6%) of COVID-19 related hospitalisations/deaths were observed. Sotrovimab was associated with substantially lower outcome risk than molnupiravir (adjusted hazard ratio, HR=0.35, 95% CI: 0.17-0.71; P=0.004), with results remaining robust in multiple sensitivity analyses. In the SRR cohort, sotrovimab showed a trend toward lower outcome risk than molnupiravir (HR=0.39, 95% CI: 0.13-1.21; P=0.106). In both datasets, sotrovimab had no evidence of association with other hospitalisation/death compared with molnupiravir (HRs ranging from 0.73-1.29; P>0.05).Conclusions: In routine care of non-hospitalised patients with COVID-19 on KRT, sotrovimab was associated with lower risk of severe COVID-19 outcomes compared with molnupiravir during Omicron waves

Ethnic differences in the indirect effects of the COVID-19 pandemic on clinical monitoring and hospitalisations for non-COVID conditions in England: a population-based, observational cohort study using the OpenSAFELY platform

BACKGROUND: The COVID-19 pandemic disrupted healthcare and may have impacted ethnic inequalities in healthcare. We aimed to describe the impact of pandemic-related disruption on ethnic differences in clinical monitoring and hospital admissions for non-COVID conditions in England. METHODS: In this population-based, observational cohort study we used primary care electronic health record data with linkage to hospital episode statistics data and mortality data within OpenSAFELY, a data analytics platform created, with approval of NHS England, to address urgent COVID-19 research questions. We included adults aged 18 years and over registered with a TPP practice between March 1, 2018, and April 30, 2022. We excluded those with missing age, sex, geographic region, or Index of Multiple Deprivation. We grouped ethnicity (exposure), into five categories: White, Asian, Black, Other, and Mixed. We used interrupted time-series regression to estimate ethnic differences in clinical monitoring frequency (blood pressure and Hba1c measurements, chronic obstructive pulmonary disease and asthma annual reviews) before and after March 23, 2020. We used multivariable Cox regression to quantify ethnic differences in hospitalisations related to diabetes, cardiovascular disease, respiratory disease, and mental health before and after March 23, 2020. FINDINGS: Of 33,510,937 registered with a GP as of 1st January 2020, 19,064,019 were adults, alive and registered for at least 3 months, 3,010,751 met the exclusion criteria and 1,122,912 were missing ethnicity. This resulted in 14,930,356 adults with known ethnicity (92% of sample): 86.6% were White, 7.3% Asian, 2.6% Black, 1.4% Mixed ethnicity, and 2.2% Other ethnicities. Clinical monitoring did not return to pre-pandemic levels for any ethnic group. Ethnic differences were apparent pre-pandemic, except for diabetes monitoring, and remained unchanged, except for blood pressure monitoring in those with mental health conditions where differences narrowed during the pandemic. For those of Black ethnicity, there were seven additional admissions for diabetic ketoacidosis per month during the pandemic, and relative ethnic differences narrowed during the pandemic compared to the White ethnic group (Pre-pandemic hazard ratio (HR): 0.50, 95% confidence interval (CI) 0.41, 0.60, Pandemic HR: 0.75, 95% CI: 0.65, 0.87). There was increased admissions for heart failure during the pandemic for all ethnic groups, though highest in those of White ethnicity (heart failure risk difference: 5.4). Relatively, ethnic differences narrowed for heart failure admission in those of Asian (Pre-pandemic HR 1.56, 95% CI 1.49, 1.64, Pandemic HR 1.24, 95% CI 1.19, 1.29) and Black ethnicity (Pre-pandemic HR 1.41, 95% CI: 1.30, 1.53, Pandemic HR: 1.16, 95% CI 1.09, 1.25) compared with White ethnicity. For other outcomes the pandemic had minimal impact on ethnic differences. INTERPRETATION: Our study suggests that ethnic differences in clinical monitoring and hospitalisations remained largely unchanged during the pandemic for most conditions. Key exceptions were hospitalisations for diabetic ketoacidosis and heart failure, which warrant further investigation to understand the causes. FUNDING: LSHTM COVID-19 Response Grant (DONAT15912)