Preparing for pandemics: a systematic review of pandemic influenza clinical management guidelines.

BACKGROUND: The COVID-19 pandemic has highlighted the importance of evidence-based clinical decision-making. Clinical management guidelines (CMGs) may help reduce morbidity and mortality by improving the quality of clinical decisions. This systematic review aims to evaluate the availability, inclusivity, and quality of pandemic influenza CMGs, to identify gaps that can be addressed to strengthen pandemic preparedness in this area. METHODS: Ovid Medline, Ovid Embase, TRIP (Turning Research Into Practice), and Guideline Central were searched systematically from January 2008 to 23rd June 2022, complemented by a grey literature search till 16th June 2022. Pandemic influenza CMGs including supportive care or empirical treatment recommendations were included. Two reviewers independently extracted data from the included studies and assessed their quality using AGREE II (Appraisal of Guidelines for Research & Evaluation). The findings are presented narratively. RESULTS: Forty-eight CMGs were included. They were produced in high- (42%, 20/48), upper-middle- (40%, 19/48), and lower-middle (8%, 4/48) income countries, or by international organisations (10%, 5/48). Most CMGs (81%, 39/48) were over 5 years old. Guidelines included treatment recommendations for children (75%, 36/48), pregnant women (54%, 26/48), people with immunosuppression (33%, 16/48), and older adults (29%, 14/48). Many CMGs were of low quality (median overall score: 3 out of 7 (range 1-7). All recommended oseltamivir; recommendations for other neuraminidase inhibitors and supportive care were limited and at times contradictory. Only 56% (27/48) and 27% (13/48) addressed oxygen and fluid therapy, respectively. CONCLUSIONS: Our data highlights the limited availability of up-to-date pandemic influenza CMGs globally. Of those identified, many were limited in scope and quality and several lacked recommendations for specific at-risk populations. Recommendations on supportive care, the mainstay of treatment, were limited and heterogeneous. The most recent guideline highlighted that the evidence-base to support antiviral treatment recommendations is still limited. There is an urgent need for trials into treatment and supportive care strategies including for different risk populations. New evidence should be incorporated into globally accessible guidelines, to benefit patient outcomes. A 'living guideline' framework is recommended and further research into guideline implementation in different resourced settings, particularly low- and middle-income countries.

The Impact of an Education Intervention to Improve Blood Pressure Control among Black Non-Hispanic Patients and Hispanic Patients with Chronic Kidney Disease

This project examined the effect of an educational intervention on blood pressure control among minority patients with chronic kidney disease (CKD). Adherence to a lowsodium diet is crucial for blood pressure control. It is also vital to assess food insecurity to improve diet adherence, especially among high-risk underrepresented populations. Participants were recruited from a public hospital renal clinic. Knowledge and food access was assessed using CKD and food insecurity questionnaires. Food frequency and 24-hour 3-day food diaries were completed and analyzed. Eighteen patients were enrolled (Black, nonHispanic = 66.6%, Hispanic = 27.7%, uninsured = 33.3%, and Medicaid recipients = 27.7%). Eighty-nine percent of participants screened positive for food insecurity and received vouchers for healthy food from a food depository. Paired t tests showed statistically significant increase in knowledge (p < 0.00) and self-efficacy, and systolic blood pressure improved post-intervention. This study suggests that Black non-Hispanic and Hispanic patients with CKD have limited access to healthy food and consume higher sodium. Patient education, screening for food insecurity, and access to a food depository enhanced adherence to low sodium diet and improved blood pressure control.

A Research and Development (R&D) roadmap for influenza vaccines: Looking toward the future.

Improved influenza vaccines are urgently needed to reduce the burden of seasonal influenza and to ensure a rapid and effective public-health response to future influenza pandemics. The Influenza Vaccines Research and Development (R&D) Roadmap (IVR) was created, through an extensive international stakeholder engagement process, to promote influenza vaccine R&D. The roadmap covers a 10-year timeframe and is organized into six sections: virology; immunology; vaccinology for seasonal influenza vaccines; vaccinology for universal influenza vaccines; animal and human influenza virus infection models; and policy, finance, and regulation. Each section identifies barriers, gaps, strategic goals, milestones, and additional R&D priorities germane to that area. The roadmap includes 113 specific R&D milestones, 37 of which have been designated high priority by the IVR expert taskforce. This report summarizes the major issues and priority areas of research outlined in the IVR. By identifying the key issues and steps to address them, the roadmap not only encourages research aimed at new solutions, but also provides guidance on the use of innovative tools to drive breakthroughs in influenza vaccine R&D.

Bacteraemia variation during the COVID-19 pandemic; a multi-centre UK secondary care ecological analysis.

BACKGROUND: We investigated for change in blood stream infections (BSI) with Enterobacterales, coagulase negative staphylococci (CoNS), Streptococcus pneumoniae, and Staphylococcus aureus during the first UK wave of SARS-CoV-2 across five London hospitals. METHODS: A retrospective multicentre ecological analysis was undertaken evaluating all blood cultures taken from adults from 01 April 2017 to 30 April 2020 across five acute hospitals in London. Linear trend analysis and ARIMA models allowing for seasonality were used to look for significant variation. RESULTS: One hundred nineteen thousand five hundred eighty-four blood cultures were included. At the height of the UK SARS-CoV-2 first wave in April 2020, Enterobacterales bacteraemias were at an historic low across two London trusts (63/3814, 1.65%), whilst all CoNS BSI were at an historic high (173/3814, 4.25%). This differed significantly for both Enterobacterales (p = 0.013), CoNS central line associated BSIs (CLABSI) (p < 0.01) and CoNS non-CLABSI (p < 0.01), when compared with prior periods, even allowing for seasonal variation. S. pneumoniae (p = 0.631) and S. aureus (p = 0.617) BSI did not vary significant throughout the study period. CONCLUSIONS: Significantly fewer than expected Enterobacterales BSI occurred during the UK peak of the COVID-19 pandemic; identifying potential causes, including potential unintended consequences of national self-isolation public health messaging, is essential. High rates of CoNS BSI, with evidence of increased CLABSI, but also likely contamination associated with increased use of personal protective equipment, may result in inappropriate antimicrobial use and indicates a clear area for intervention during further waves.

Deep learning model to predict the need for mechanical ventilation using chest X-ray images in hospitalised patients with COVID-19.

OBJECTIVES: There exists a wide gap in the availability of mechanical ventilator devices and their acute need in the context of the COVID-19 pandemic. An initial triaging method that accurately identifies the need for mechanical ventilation in hospitalised patients with COVID-19 is needed. We aimed to investigate if a potentially deteriorating clinical course in hospitalised patients with COVID-19 can be detected using all X-ray images taken during hospitalisation. METHODS: We exploited the well-established DenseNet121 deep learning architecture for this purpose on 663 X-ray images acquired from 528 hospitalised patients with COVID-19. Two Pulmonary and Critical Care experts blindly and independently evaluated the same X-ray images for the purpose of validation. RESULTS: We found that our deep learning model predicted the need for mechanical ventilation with a high accuracy, sensitivity and specificity (90.06%, 86.34% and 84.38%, respectively). This prediction was done approximately 3 days ahead of the actual intubation event. Our model also outperformed two Pulmonary and Critical Care experts who evaluated the same X-ray images and provided an incremental accuracy of 7.24%-13.25%. CONCLUSIONS: Our deep learning model accurately predicted the need for mechanical ventilation early during hospitalisation of patients with COVID-19. Until effective preventive or treatment measures become widely available for patients with COVID-19, prognostic stratification as provided by our model is likely to be highly valuable.

Insights into the Use of C-Reactive Protein as a Diagnostic Index of Disease Severity in COVID-19 Infections.

Approximately 20% of patients infected with SARS-CoV-2 (COVID-19) develop potentially life-threatening pathologies involving hyperinflammation, cytokine storm, septic shock complications, coagulation dysfunction, and multiple organ failure. Blood levels of the prototypic acute phase reactant, C-reactive protein (CRP), which is hepatically synthesized and released in response to interleukin-6 stimulation, is markedly elevated in patients with COVID-19. Markedly high CRP levels correlate with poor prognosis for survival. Insights into CRP structure-function relationships have uncovered both pro- and anti-inflammatory isoforms that may be used to monitor the extent of tissue damage associated with COVID-19 pathologies and prognoses. Herein, rationale is given for interpretation of CRP blood levels as a simple, rapid, and cost-effective way to assess disease severity and help guide therapeutic options in COVID-19 patients.