nnResting state fMRI scanner instabilities revealed by longitud inal phantom scans in a multi-center study

Quality assurance (QA) is crucial in longitudinal and/or multi-site studies, which involve the collection of data from a group of subjects over time and/or at different locations. It is important to regularly monitor the performance of the scanners over time and at different locations to detect and control for intrinsic differences (e.g., due to manufacturers) and changes in scanner performance (e.g., due to gradual component aging, software and/or hardware upgrades, etc.). As part of the Ontario Neurodegenerative Disease Research Initiative (ONDRI) and the Canadian Biomarker Integration Network in Depression (CAN-BIND), QA phantom scans were conducted approximately monthly for three to four years at 13 sites across Canada with 3T research MRI scanners. QA parameters were calculated for each scan using the functional Biomarker Imaging Research Network\u27s (fBIRN) QA phantom and pipeline to capture between- and within-scanner variability. We also describe a QA protocol to measure the full-width-at-half-maximum (FWHM) of slice-wise point spread functions (PSF), used in conjunction with the fBIRN QA parameters. Variations in image resolution measured by the FWHM are a primary source of variance over time for many sites, as well as between sites and between manufacturers. We also identify an unexpected range of instabilities affecting individual slices in a number of scanners, which may amount to a substantial contribution of unexplained signal variance to their data. Finally, we identify a preliminary preprocessing approach to reduce this variance and/or alleviate the slice anomalies, and in a small human data set show that this change in preprocessing can have a significant impact on seed-based connectivity measurements for some individual subjects. We expect that other fMRI centres will find this approach to identifying and controlling scanner instabilities useful in similar studies

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

SummaryBackground Azithromycin has been proposed as a treatment for COVID-19 on the basis of its immunomodulatoryactions. We aimed to evaluate the safety and efficacy of azithromycin in patients admitted to hospital with COVID-19.Methods In this randomised, controlled, open-label, adaptive platform trial (Randomised Evaluation of COVID-19Therapy [RECOVERY]), several possible treatments were compared with usual care in patients admitted to hospitalwith COVID-19 in the UK. The trial is underway at 176 hospitals in the UK. Eligible and consenting patients wererandomly allocated to either usual standard of care alone or usual standard of care plus azithromycin 500 mg once perday by mouth or intravenously for 10 days or until discharge (or allocation to one of the other RECOVERY treatmentgroups). Patients were assigned via web-based simple (unstratified) randomisation with allocation concealment andwere twice as likely to be randomly assigned to usual care than to any of the active treatment groups. Participants andlocal study staff were not masked to the allocated treatment, but all others involved in the trial were masked to theoutcome data during the trial. The primary outcome was 28-day all-cause mortality, assessed in the intention-to-treatpopulation. The trial is registered with ISRCTN, 50189673, and ClinicalTrials.gov, NCT04381936.Findings Between April 7 and Nov 27, 2020, of 16 442 patients enrolled in the RECOVERY trial, 9433 (57%) wereeligible and 7763 were included in the assessment of azithromycin. The mean age of these study participants was65·3 years (SD 15·7) and approximately a third were women (2944 [38%] of 7763). 2582 patients were randomlyallocated to receive azithromycin and 5181 patients were randomly allocated to usual care alone. Overall,561 (22%) patients allocated to azithromycin and 1162 (22%) patients allocated to usual care died within 28 days(rate ratio 0·97, 95% CI 0·87–1·07; p=0·50). No significant difference was seen in duration of hospital stay (median10 days [IQR 5 to >28] vs 11 days [5 to >28]) or the proportion of patients discharged from hospital alive within 28 days(rate ratio 1·04, 95% CI 0·98–1·10; p=0·19). Among those not on invasive mechanical ventilation at baseline, nosignificant difference was seen in the proportion meeting the composite endpoint of invasive mechanical ventilationor death (risk ratio 0·95, 95% CI 0·87–1·03; p=0·24).Interpretation In patients admitted to hospital with COVID-19, azithromycin did not improve survival or otherprespecified clinical outcomes. Azithromycin use in patients admitted to hospital with COVID-19 should be restrictedto patients in whom there is a clear antimicrobial indication

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

The microbiome and gene expression of honey bee workers are affected by a diet containing pollen substitutes.

Pollen is the primary source of dietary protein for honey bees. It also includes complex polysaccharides in its outer coat, which are largely indigestible by bees but can be metabolized by bacterial species within the gut microbiota. During periods of reduced availability of floral pollen, supplemental protein sources are frequently provided to managed honey bee colonies. The crude proteins in these supplemental feeds are typically byproducts from food manufacturing processes and are rarely derived from pollen. Our experiments on the impact of different diets showed that a simplified pollen-free diet formulated to resemble the macronutrient profile of a monofloral pollen source resulted in larger microbial communities with reduced diversity, reduced evenness, and reduced levels of potentially beneficial hive-associated bacteria. Furthermore, the pollen-free diet sharply reduced the expression of genes central to honey bee development. In subsequent experiments, we showed that these shifts in gene expression may be linked to colonization by the gut microbiome. Lastly, we demonstrated that for bees inoculated with a defined gut microbiota, those raised on an artificial diet were less able to suppress infection from a bacterial pathogen than those that were fed natural pollen. Our findings demonstrate that a pollen-free diet significantly impacts the gut microbiota and gene expression of honey bees, indicating the importance of natural pollen as a primary protein source

Consumers’ and health providers’ views and perceptions of partnering to improve health services design, delivery and evaluation: a co‐produced qualitative evidence synthesis

Background: Partnering with consumers in the planning, delivery and evaluation of health services is an essential component of person-centred care. There are many ways to partner with consumers to improve health services, including formal group partnerships (such as committees, boards or steering groups). However, consumers' and health providers' views and experiences of formal group partnerships remain unclear. In this qualitative evidence synthesis (QES), we focus specifically on formal group partnerships where health providers and consumers share decision-making about planning, delivering and/or evaluating health services. Formal group partnerships were selected because they are widely used throughout the world to improve person-centred care. For the purposes of this QES, the term 'consumer' refers to a person who is a patient, carer or community member who brings their perspective to health service partnerships. 'Health provider' refers to a person with a health policy, management, administrative or clinical role who participates in formal partnerships in an advisory or representative capacity. This QES was co-produced with a Stakeholder Panel of consumers and health providers. The QES was undertaken concurrently with a Cochrane intervention review entitled Effects of consumers and health providers working in partnership on health services planning, delivery and evaluation. Objectives: 1. To synthesise the views and experiences of consumers and health providers of formal partnership approaches that aimed to improve planning, delivery or evaluation of health services. 2. To identify best practice principles for formal partnership approaches in health services by understanding consumers' and health providers' views and experiences. Search methods: We searched MEDLINE, Embase, PsycINFO and CINAHL for studies published between January 2000 and October 2018. We also searched grey literature sources including websites of relevant research and policy organisations involved in promoting person-centred care. Selection criteria: We included qualitative studies that explored consumers' and health providers' perceptions and experiences of partnering in formal group formats to improve the planning, delivery or evaluation of health services. Data collection and analysis: Following completion of abstract and full-text screening, we used purposive sampling to select a sample of eligible studies that covered a range of pre-defined criteria, including rich data, range of countries and country income level, settings, participants, and types of partnership activities. A Framework Synthesis approach was used to synthesise the findings of the sample. We appraised the quality of each study using the CASP (Critical Appraisal Skill Program) tool. We assessed our confidence in the findings using the GRADE-CERQual (Confidence in the Evidence from Reviews of Qualitative research) approach. The Stakeholder Panel was involved in each stage of the review from development of the protocol to development of the best practice principles. Main results: We found 182 studies that were eligible for inclusion. From this group, we selected 33 studies to include in the final synthesis. These studies came from a wide range of countries including 28 from high-income countries and five from low- or middle-income countries (LMICs). Each of the studies included the experiences and views of consumers and/or health providers of partnering in formal group formats. The results were divided into the following categories. Contextual factors influencing partnerships: government policy, policy implementation processes and funding, as well as the organisational context of the health service, could facilitate or impede partnering (moderate level of confidence). Consumer recruitment: consumer recruitment occurred in different ways and consumers managed the recruitment process in a minority of studies only (high level of confidence). Recruiting a range of consumers who were reflective of the clinic's demographic population was considered desirable, particularly by health providers (high level of confidence). Some health providers perceived that individual consumers' experiences were not generalisable to the broader population whereas consumers perceived it could be problematic to aim to represent a broad range of community views (high level of confidence). Partnership dynamics and processes: positive interpersonal dynamics between health providers and consumers facilitated partnerships (high level of confidence). However, formal meeting formats and lack of clarity about the consumer role could constrain consumers’ involvement (high level of confidence). Health providers’ professional status, technical knowledge and use of jargon were intimidating for some consumers (high level of confidence) and consumers could feel their experiential knowledge was not valued (moderate level of confidence). Consumers could also become frustrated when health providers dominated the meeting agenda (moderate level of confidence) and when they experienced token involvement, such as a lack of decision-making power (high level of confidence). Perceived impacts on partnership participants: partnering could affect health provider and consumer participants in both positive and negative ways (high level of confidence). Perceived impacts on health service planning, delivery and evaluation: partnering was perceived to improve the person-centredness of health service culture (high level of confidence), improve the built environment of the health service (high level of confidence), improve health service design and delivery e.g. facilitate 'out of hours' services or treatment closer to home (high level of confidence), enhance community ownership of health services, particularly in LMICs (moderate level of confidence), and improve consumer involvement in strategic decision-making, under certain conditions (moderate level of confidence). There was limited evidence suggesting partnering may improve health service evaluation (very low level of confidence). Best practice principles for formal partnering to promote person-centred care were developed from these findings. The principles were developed collaboratively with the Stakeholder Panel and included leadership and health service culture; diversity; equity; mutual respect; shared vision and regular communication; shared agendas and decision-making; influence and sustainability. Authors' conclusions: Successful formal group partnerships with consumers require health providers to continually reflect and address power imbalances that may constrain consumers' participation. Such imbalances may be particularly acute in recruitment procedures, meeting structure and content and decision-making processes. Formal group partnerships were perceived to improve the physical environment of health services, the person-centredness of health service culture and health service design and delivery. Implementing the best practice principles may help to address power imbalances, strengthen formal partnering, improve the experiences of consumers and health providers and positively affect partnership outcomes.</p