What are the long-term symptoms and complications of COVID-19: a protocol for a living systematic review

Although the majority of patients with COVID-19 will experience mild to moderate symptoms and will recover fully, there is now increasing evidence that a significant proportion will experience persistent symptoms for weeks or months after the acute phase of the illness. These symptoms include, among others, fatigue, problems in breathing, lack of smell and taste, headaches, and also depression and anxiety. It has also become clear that the virus has lasting effects not only on the respiratory system but also on other parts of the body, including the heart, liver, and the nervous system. In this paper we present a protocol for a living systematic review that aims to synthesize the evidence on the prevalence and duration of symptoms and clinical features of post-acute COVID-19 and its long-term complications. The living systematic review will be updated regularly, initially monthly with update cycles under continuous review as the pace of new evidence generated develops through the pandemic. We will include studies that follow up with COVID-19 patients who have experienced persistent mild, moderate or severe symptoms, with no restrictions regarding country, setting, or language. We will use descriptive statistics to analyse the data and our findings will be presented as infographics to facilitate transcription to lay audiences. Ultimately, we aim to support the work of policy makers, practitioners, and patients when planning rehabilitation for those recovering from COVID-19. The protocol has been registered with PROSPERO (https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=211131, CRD42020211131, 25/09/2020)

Characteristics of frequent emergency department presenters to an Australian emergency medicine network

<p>Abstract</p> <p>Background</p> <p>To describe the characteristics of emergency department (ED) patients defined as frequent presenters (FP) presenting to an Australian emergency department network and compare these with a cohort of non-frequent presenters (NFP).</p> <p>Method</p> <p>A retrospective chart review utilising an electronic emergency medicine patient medical record database was performed on patients presenting to Southern Health EDs from March 2009 to March 2010. Non-frequent presenters were defined as patients presenting less than 5 times and frequent presenters as presenting 8 or more times in the study period. Characteristics of both groups were described and compared.</p> <p>Results</p> <p>During the 12-month study period there were 540 FP patients with 4549 admissions and 73,089 NFP patients with 100,943 admissions. FP patients were slightly older with a significant increase in frequency of patients between the ages of 70 to 79 years and they were more likely to be divorced or separated than NFP patients. Frequent presenters to the emergency department were more likely to utilise the ambulance service to arrive at the hospital, or in the custody of police than NFP patients. FPs were more likely to be admitted to hospital, more likely to have an admission to a mental health bed than NFP patients and more likely to self-discharge from the emergency department while waiting for care.</p> <p>Conclusions</p> <p>There are major implications for the utilisation of limited ED resources by frequent presenters. By further understanding the characteristics of FP we may be able to address the specific health care needs of this population in more efficient and cost effective ways. Further research analysing the effectiveness of targeted multidisciplinary interventions aiming to reduce the frequency of ED attendances may be warranted.</p

Availability, scope and quality of monkeypox clinical management guidelines globally : a systematic review

This work was supported by the UK Foreign, Commonwealth and Development Office and Wellcome (215091/Z/18/Z) and the Bill & Melinda Gates Foundation (OPP1209135). The GloPID-R Secretariat is a project that receives funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 874667. SL is an MRC Clinical Research Training fellow (MR/T001151/1).Background Monkeypox (MPX) is an important human Orthopoxvirus infection. There has been an increase in MPX cases and outbreaks in endemic and non-endemic regions in recent decades. We appraised the availability, scope, quality and inclusivity of clinical management guidelines for MPX globally. Methods For this systematic review, we searched six databases from inception until 14 October 2021, augmented by a grey literature search until 17 May 2022. MPX guidelines providing treatment and supportive care recommendations were included, with no exclusions for language. Two reviewers assessed the guidelines. Quality was assessed using the Appraisal of Guidelines for Research and Evaluation II tool. Results Of 2026 records screened, 14 guidelines were included. Overall, most guidelines were of low-quality with a median score of 2 out of 7 (range: 1–7), lacked detail and covered a narrow range of topics. Most guidelines focused on adults, five (36%) provided some advice for children, three (21%) for pregnant women and three (21%) for people living with HIV. Treatment guidance was mostly limited to advice on antivirals; seven guidelines advised cidofovir (four specified for severe MPX only); 29% (4/14) tecovirimat, and 7% (1/14) brincidofovir. Only one guideline provided recommendations on supportive care and treatment of complications. All guidelines recommended vaccination as post-exposure prophylaxis (PEP). Three guidelines advised on vaccinia immune globulin as PEP for severe cases in people with immunosuppression. Conclusion Our results highlight a lack of evidence-based clinical management guidelines for MPX globally. There is a clear and urgent need for research into treatment and prophylaxis including for different risk populations. The current outbreak provides an opportunity to accelerate this research through coordinated high-quality studies. New evidence should be incorporated into globally accessible guidelines, to benefit patient and epidemic outcomes. A ‘living guideline’ framework is recommended. PROSPERO registration number CRD42020167361.Publisher PDFPeer reviewe

Characterising long COVID: a living systematic review

BACKGROUND: While it is now apparent clinical sequelae (long COVID) may persist after acute COVID-19, their nature, frequency and aetiology are poorly characterised. This study aims to regularly synthesise evidence on long COVID characteristics, to help inform clinical management, rehabilitation strategies and interventional studies to improve long-term outcomes. METHODS: A living systematic review. Medline, CINAHL (EBSCO), Global Health (Ovid), WHO Global Research on COVID-19 database, LitCovid and Google Scholar were searched till 17 March 2021. Studies including at least 100 people with confirmed or clinically suspected COVID-19 at 12 weeks or more post onset were included. Risk of bias was assessed using the tool produced by Hoy et al. Results were analysed using descriptive statistics and meta-analyses to estimate prevalence. RESULTS: A total of 39 studies were included: 32 cohort, 6 cross-sectional and 1 case-control. Most showed high or moderate risk of bias. None were set in low-income countries and few included children. Studies reported on 10 951 people (48% female) in 12 countries. Most included previously hospitalised people (78%, 8520/10 951). The longest mean follow-up time was 221.7 (SD: 10.9) days post COVID-19 onset. Over 60 physical and psychological signs and symptoms with wide prevalence were reported, most commonly weakness (41%; 95% CI 25% to 59%), general malaise (33%; 95% CI 15% to 57%), fatigue (31%; 95% CI 24% to 39%), concentration impairment (26%; 95% CI 21% to 32%) and breathlessness (25%; 95% CI 18% to 34%). 37% (95% CI 18% to 60%) of patients reported reduced quality of life; 26% (10/39) of studies presented evidence of reduced pulmonary function. CONCLUSION: Long COVID is a complex condition with prolonged heterogeneous symptoms. The nature of studies precludes a precise case definition or risk evaluation. There is an urgent need for prospective, robust, standardised, controlled studies into aetiology, risk factors and biomarkers to characterise long COVID in different at-risk populations and settings. PROSPERO REGISTRATION NUMBER: CRD42020211131

Studying the post-COVID-19 condition: research challenges, strategies, and importance of Core Outcome Set development

Background A substantial portion of people with COVID-19 subsequently experience lasting symptoms including fatigue, shortness of breath, and neurological complaints such as cognitive dysfunction many months after acute infection. Emerging evidence suggests that this condition, commonly referred to as long COVID but also known as post-acute sequelae of SARS-CoV-2 infection (PASC) or post-COVID-19 condition, could become a significant global health burden. Main text While the number of studies investigating the post-COVID-19 condition is increasing, there is no agreement on how this new disease should be defined and diagnosed in clinical practice and what relevant outcomes to measure. There is an urgent need to optimise and standardise outcome measures for this important patient group both for clinical services and for research and to allow comparing and pooling of data. Conclusions A Core Outcome Set for post-COVID-19 condition should be developed in the shortest time frame possible, for improvement in data quality, harmonisation, and comparability between different geographical locations. We call for a global initiative, involving all relevant partners, including, but not limited to, healthcare professionals, researchers, methodologists, patients, and caregivers. We urge coordinated actions aiming to develop a Core Outcome Set (COS) for post-COVID-19 condition in both the adult and paediatric populations

Success probability for selectively neutral invading species in the line model with a random fitness landscape

We consider a spatial (line) model for invasion of a population by a single mutant with a stochastically selectively neutral fitness landscape, independent from the fitness landscape for nonmutants. This model is similar to those considered earlier. We show that the probability of mutant fixation in a population of size (Formula presented.), starting from a single mutant, is greater than (Formula presented.), which would be the case if there were no variation in fitness whatsoever. In the small variation regime, we recover precise asymptotics for the success probability of the mutant. This demonstrates that the introduction of randomness provides an advantage to minority mutations in this model, and shows that the advantage increases with the system size. We further demonstrate that the mutants have an advantage in this setting only because they are better at exploiting unusually favorable environments when they arise, and not because they are any better at exploiting pockets of favorability in an environment that is selectively neutral&nbsp;overall

Accessibility, inclusivity, and implementation of COVID-19 clinical management guidelines early in the pandemic: a global survey

Background: With a rapidly changing evidence base, high-quality clinical management guidelines (CMGs) are key tools for aiding clinical decision making and increasing access to best available evidence-based care. A rapid review of COVID-19 CMGs found most lacked methodological rigour, overlooked at-risk populations, and varied in treatment recommendations. Furthermore, social science literature highlights the complexity of implementing guidelines in local contexts where they were not developed and the resulting potential to compound health inequities. This study aimed to evaluate access to, inclusivity of, and implementation of COVID-19 CMGs in different settings. Methods: A cross-sectional survey of clinicians worldwide was conducted from 15th June to 20th July 2020, to explore access to and implementation of COVID-19 CMGs, and treatment and supportive care recommendations provided. Data on accessibility, inclusivity, and implementation of CMGs were analysed by geographic location. Results: 76 clinicians from 27 countries responded: 82% from high-income countries, 17% from lower middle-income countries (LMICs). Most respondents reported access to COVID-19 CMGs and confidence in their implementation. However, many respondents, particularly from LMICs, reported barriers to implementation, including limited access to treatment and equipment. Only 20% of respondents reported having access to CMGs covering care for children, 25% for pregnant women, and 50% for older adults (>65 years). Identified themes were for CMGs to include recommendations for at-risk populations and settings, include supportive care guidance, and be updated as evidence emerges, and for clinicians to have training and access to recommended treatments to support implementation. Conclusion: Our findings highlight important gaps in COVID-19 CMG development and implementation challenges during a pandemic, particularly affecting at-risk populations and lower resourced settings. This study identifies an urgent need for an improved CMG development framework that is inclusive and adaptable to emerging evidence and considers contextual implementation support, to improve access to evidence-based care globally

Accessibility, inclusivity, and implementation of COVID-19 clinical management guidelines early in the pandemic: a global survey

&lt;h4&gt;Background&lt;/h4&gt; With a rapidly changing evidence base, high-quality clinical management guidelines (CMGs) are key tools for aiding clinical decision making and increasing access to best available evidence-based care. A rapid review of COVID-19 CMGs found that most lacked methodological rigour, overlooked many at-risk populations, and had variations in treatment recommendations. Furthermore, social science literature highlights the complexity of implementing guidelines in local contexts where they were not developed and the resulting potential to compound health inequities. The aim of this study was to evaluate access to, inclusivity of, and implementation of Covid-19 CMGs in different settings. &lt;h4&gt;Methods&lt;/h4&gt; A cross-sectional survey of clinicians worldwide from 15 June to 20 July 2020, to explore access to and implementation of Covid-19 CMGs and treatment and supportive care recommendations provided. Data on accessibility, inclusivity, and implementation of CMGs. were analyzed by geographic location. &lt;h4&gt;Results&lt;/h4&gt; Seventy-six clinicians, from 27 countries responded, 82% from high-income countries, 17% from low-middle income countries. Most respondents reported access to Covid-19 CMG and confidence in implementation of these. However, many respondents, particularly from LMICs reported barriers to implementation, including limited access to treatments and equipment. Only 20% of respondents reported having access to CMGs covering care for children, 25% for pregnant women and 50% for older adults (&gt;65 years). Themes emerging were for CMGs to include recommendations for different at-risk populations, and settings, include supportive care guidance, be readily updated as evidence emerges, and CMG implementation supported by training, and access to treatments recommended. &lt;h4&gt;Conclusion&lt;/h4&gt; Our findings highlight important gaps in Covid-19 CMG development and implementation challenges during a pandemic, particularly affecting different at-risk populations and lower resourced settings., to improve access in evidence-based care recommendations during an emergency. The findings identifies an urgent need for an improved framework for CMG development, that is inclusive and adaptable to emerging evidence and considers contextual implementation support, to improve access to evidence-based care globally

DIRECT DESIGN OF BIQUAD FILTER CASCADES WITH DEEP LEARNING BY SAMPLING RANDOM POLYNOMIALS

Designing infinite impulse response filters to match an arbitrary magnitude response requires specialized techniques. Methods like modified Yule-Walker are relatively efficient, but may not be sufficiently accurate in matching high order responses. On the other hand, iterative optimization techniques often enable superior performance, but come at the cost of longer run-times and are sensitive to initial conditions, requiring manual tuning. In this work, we address some of these limitations by learning a direct mapping from the target magnitude response to the filter coefficient space with a neural network trained on millions of random filters. We demonstrate our approach enables both fast and accurate estimation of filter coefficients given a desired response. We investigate training with different families of random filters, and find training with a variety of filter families enables better generalization when estimating real-world filters, using head-related transfer functions and guitar cabinets as case studies. We compare our method against existing methods including modified Yule-Walker and gradient descent and show our approach is, on average, both faster and more accurate