Publications

ABSTRACT Objectives During the COVID-19 pandemic, BMJ , the premier journal on evidence-based medicine worldwide, published many views by advocates of specific COVID-19 policies. We aimed to evaluate the presence and potential bias of this advocacy. Design and Methods Scopus was searched for items published until April 13, 2024 on “COVID-19 OR SARS-CoV-2”. BMJ publication numbers and types before (2016−2019) and during (2020−2023) the pandemic were compared for a group of advocates favoring aggressive measures (leaders of both the Independent Scientific Advisory Group for Emergencies (indieSAGE) and the Vaccines-Plus initiative) and four control groups: leading members of the governmental Scientific Advisory Group for Emergencies (SAGE), UK-based key signatories of the Great Barrington Declaration (GBD) (favoring more restricted measures), highly-cited UK scientists, and UK scientists who published the highest number of COVID-19-related papers in the entire scientific literature (n=16 in each group). Results 122 authors published more than 5 COVID-19-related items each in BMJ . Of those, 18 were leading members/signatories of aggressive measures advocacy groups publishing 231 COVID-19 related BMJ documents, 53 were editors/journalists, and 51 scientists were not identified as associated with any advocacy. Of 41 authors with >10 publications in BMJ , 8 were scientists advocating for aggressive measures, 7 were editors, 23 were journalists, and only 3 were non-advocate scientists. Some aggressive measures advocates already had strong BMJ presence pre-pandemic. During pandemic years, the studied indieSAGE/Vaccines-Plus advocates outperformed in BMJ presence leading SAGE members by 16.0-fold, UK-based GBD advocates by 64.2-fold, the most-cited scientists by 16.0-fold, and the authors who published most COVID-19 papers overall by 10.7-fold. The difference was driven mainly by short opinion pieces and analyses. Conclusions BMJ appears to have favored and massively promoted specific COVID-19 advocacy views during the pandemic, thereby strongly biasing the scientific picture on COVID-19. Summary box Section 1: What is already known on this topic Advocacy is intensely debated for its merits to science and policy. Many journals increasingly publish pieces by advocates and it is thus important to understand the nature, scale and impact of this phenomenon. Section 2: What this study adds This study provides a detailed quantitative assessment of journal-promoted advocacy, focusing on the world’s premier evidence-based medical journal, the BMJ . We show that BMJ had massive bias towards specific COVID-19-related advocacy favoring aggressive measures. Our study reveals a need for editorial guidelines on journal-promoted advocacy.

Objective To systematically assess credibility and certainty of associations between cannabis, cannabinoids, and cannabis based medicines and human health, from observational studies and randomised controlled trials (RCTs). Design Umbrella review. Data sources PubMed, PsychInfo, Embase, up to 9 February 2022. Eligibility criteria for selecting studies Systematic reviews with meta-analyses of observational studies and RCTs that have reported on the efficacy and safety of cannabis, cannabinoids, or cannabis based medicines were included. Credibility was graded according to convincing, highly suggestive, suggestive, weak, or not significant (observational evidence), and by GRADE (Grading of Recommendations, Assessment, Development and Evaluations) (RCTs). Quality was assessed with AMSTAR 2 (A Measurement Tool to Assess Systematic Reviews 2). Sensitivity analyses were conducted. Results 101 meta-analyses were included (observational=50, RCTs=51) (AMSTAR 2 high 33, moderate 31, low 32, or critically low 5). From RCTs supported by high to moderate certainty, cannabis based medicines increased adverse events related to the central nervous system (equivalent odds ratio 2.84 (95% confidence interval 2.16 to 3.73)), psychological effects (3.07 (1.79 to 5.26)), and vision (3.00 (1.79 to 5.03)) in people with mixed conditions (GRADE=high), improved nausea/vomit, pain, spasticity, but increased psychiatric, gastrointestinal adverse events, and somnolence among others (GRADE=moderate). Cannabidiol improved 50% reduction of seizures (0.59 (0.38 to 0.92)) and seizure events (0.59 (0.36 to 0.96)) (GRADE=high), but increased pneumonia, gastrointestinal adverse events, and somnolence (GRADE=moderate). For chronic pain, cannabis based medicines or cannabinoids reduced pain by 30% (0.59 (0.37 to 0.93), GRADE=high), across different conditions (n=7), but increased psychological distress. For epilepsy, cannabidiol increased risk of diarrhoea (2.25 (1.33 to 3.81)), had no effect on sleep disruption (GRADE=high), reduced seizures across different populations and measures (n=7), improved global impression (n=2), quality of life, and increased risk of somnolence (GRADE=moderate). In the general population, cannabis worsened positive psychotic symptoms (5.21 (3.36 to 8.01)) and total psychiatric symptoms (7.49 (5.31 to 10.42)) (GRADE=high), negative psychotic symptoms, and cognition (n=11) (GRADE=moderate). In healthy people, cannabinoids improved pain threshold (0.74 (0.59 to 0.91)), unpleasantness (0.60 (0.41 to 0.88)) (GRADE=high). For inflammatory bowel disease, cannabinoids improved quality of life (0.34 (0.22 to 0.53) (GRADE=high). For multiple sclerosis, cannabinoids improved spasticity, pain, but increased risk of dizziness, dry mouth, nausea, somnolence (GRADE=moderate). For cancer, cannabinoids improved sleep disruption, but had gastrointestinal adverse events (n=2) (GRADE=moderate). Cannabis based medicines, cannabis, and cannabinoids resulted in poor tolerability across various conditions (GRADE=moderate). Evidence was convincing from observational studies (main and sensitivity analyses) in pregnant women, small for gestational age (1.61 (1.41 to 1.83)), low birth weight (1.43 (1.27 to 1.62)); in drivers, car crash (1.27 (1.21 to 1.34)); and in the general population, psychosis (1.71 (1.47 to 2.00)). Harmful effects were noted for additional neonatal outcomes, outcomes related to car crash, outcomes in the general population including psychotic symptoms, suicide attempt, depression, and mania, and impaired cognition in healthy cannabis users (all suggestive to highly suggestive). Conclusions Convincing or converging evidence supports avoidance of cannabis during adolescence and early adulthood, in people prone to or with mental health disorders, in pregnancy and before and while driving. Cannabidiol is effective in people with epilepsy. Cannabis based medicines are effective in people with multiple sclerosis, chronic pain, inflammatory bowel disease, and in palliative medicine but not without adverse events. Study registration PROSPERO CRD42018093045. Funding None.

Building hardware prototypes for computer architecture research is challenging. Unfortunately, development of the required software tools (compilers, debuggers, runtime) is even more challenging, which means these systems rarely run real applications. To overcome this issue, when developing our prototype platform, we used the Tensilica processor generator to produce a customized processor and corresponding software tools and libraries. While this base processor was very different from the streamlined custom processor we initially imagined, it allowed us to focus on our main objective---the design of a reconfigurable CMP memory system---and to successfully tape out an 8-core CMP chip with only a small group of designers. One person was able to handle processor configuration and hardware generation, support of a complete software tool chain, as well as developing the custom runtime software to support three different programming models. Having a sophisticated software tool chain not only allowed us to run more applications on our machine, it once again pointed out the need to use optimized code to get an accurate evaluation of architectural features.

A 64-entry fully associative TLB (translation-lookaside buffer) with a pin-to-pin translation delay of 3.6 ns is described. This translation speed is achieved by using BiCMOS content-addressable memory (CAM) and SRAM arrays wherein small signal swings are maintained throughout the critical translation path. A BiCMOS CAM cell that uses a single bipolar translator to drive the match line is introduced. The TLB has been integrated as a stand-alone chip in an 0.8- mu m BiCMOS technology. The circuit operates from a 5.2-V supply with ECL-compatible input and output levels. The power dissipation (excluding the power dissipated in the physical address output buffers) is less than 600 mW.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

Machine learning, artificial intelligence, and other modern statistical methods are providing new opportunities to operationalise previously untapped and rapidly growing sources of data for patient benefit. Despite much promising research currently being undertaken, particularly in imaging, the literature as a whole lacks transparency, clear reporting to facilitate replicability, exploration for potential ethical concerns, and clear demonstrations of effectiveness. Among the many reasons why these problems exist, one of the most important (for which we provide a preliminary solution here) is the current lack of best practice guidance specific to machine learning and artificial intelligence. However, we believe that interdisciplinary groups pursuing research and impact projects involving machine learning and artificial intelligence for health would benefit from explicitly addressing a series of questions concerning transparency, reproducibility, ethics, and effectiveness (TREE). The 20 critical questions proposed here provide a framework for research groups to inform the design, conduct, and reporting; for editors and peer reviewers to evaluate contributions to the literature; and for patients, clinicians and policy makers to critically appraise where new findings may deliver patient benefit.

Eur J Clin Invest 2012; 42 (1): 1–16 Summary points Advances in laboratory techniques have led to a rapidly increasing use of biomarkers in epidemiological studies. Biomarkers of internal dose, early biological change, susceptibility and clinical outcomes are used as proxies for investigating interactions between external and/or endogenous agents and body components or processes. The need for improved reporting of scientific research led to influential statements of recommendations such as the STrengthening Reporting of OBservational studies in Epidemiology (STROBE) statement. The STROBE initiative established in 2004 aimed to provide guidance on how to report observational research. Its guidelines provide a user‐friendly checklist of 22 items to be reported in epidemiological studies, with items specific to the three main study designs: cohort studies, case–control studies and cross‐sectional studies. The present STrengthening the Reporting of OBservational studies in Epidemiology – Molecular Epidemiology (STROBE‐ME) initiative builds on the STROBE statement implementing nine existing items of STROBE and providing 17 additional items to the 22 items of STROBE checklist. The additions relate to the use of biomarkers in epidemiological studies, concerning collection, handling and storage of biological samples; laboratory methods, validity and reliability of biomarkers; specificities of study design; and ethical considerations. The STROBE‐ME recommendations are intended to complement the STROBE recommendations.