One year health outcomes associated with systemic corticosteroids for COVID-19: a longitudinal cohort study (preprint)

BackgroundIn patients with COVID-19 requiring supplemental oxygen, dexamethasone reduces acute severity and improves survival, but longer-term effects are unknown. We hypothesised that systemic corticosteroid administration during acute COVID-19 would be associated with improved health-related quality of life (HRQoL) one year after discharge. MethodsAdults admitted to hospital between February 2020 and March 2021 for COVID-19 and meeting current guideline recommendations for dexamethasone treatment were included using two prospective UK cohort studies. HRQoL, assessed by EQ-5D-5L utility index, pre-hospital and one year after discharge were compared between those receiving corticosteroids or not after propensity weighting for treatment. Secondary outcomes included patient reported recovery, physical and mental health status, and measures of organ impairment. Sensitivity analyses were undertaken to account for survival and selection bias. FindingsIn 1,888 participants included in the primary analysis, 1,149 received corticosteroids. There was no between-group difference in EQ-5D-5L utility index at one year (mean difference 0.004, 95% CI: -0.026 to 0.034, p = 0.77). A similar reduction in EQ-5D-5L was seen at one year between corticosteroid exposed and non-exposed groups (mean (SD) change -0.12 (0.22) vs -0.11 (0.22), p = 0.32). Overall, there were no differences in secondary outcome measures. After sensitivity analyses modelled using a larger cohort of 109,318 patients admitted to hospital with COVID-19, EQ-5D-5L utility index at one year remained similar between the two groups. InterpretationSystemic corticosteroids for acute COVID-19 have no impact on the large reduction in HRQoL one year after hospital discharge. Treatments to address this are urgently needed. Take home messageSystemic corticosteroids given for acute COVID-19 do not affect health-related quality of life or other patient reported outcomes, physical and mental health outcomes, and organ function one year after hospital discharge

Differentiation of COVID-19 from other emergency infectious disease presentations using whole blood transcriptomics then rapid qPCR: a case-control and observational cohort study (preprint)

Background. The overlapping clinical presentations of patients with acute respiratory disease can complicate disease diagnosis. Whilst PCR diagnostic methods to identify SARS-CoV-2 are highly sensitive, they have their shortcomings including false-positive risk and slow turnaround times. Changes in host gene expression can be used to distinguish between disease groups of interest, providing a viable alternative to infectious disease diagnosis. Methods. We interrogated the whole blood gene expression profiles of patients with COVID-19 (n=87), bacterial infections (n=88), viral infections (n=36), and not-infected controls (n=27) to identify a sparse diagnostic signature for distinguishing COVID-19 from other clinically similar infectious and non-infectious conditions. The sparse diagnostic signature underwent validation in a new cohort using reverse transcription quantitative polymerase chain reaction (RT-qPCR) and then underwent further external validation in an independent in silico RNA-seq cohort. Findings. We identified a 10-gene signature (OASL, UBP1, IL1RN, ZNF684, ENTPD7, NFKBIE, CDKN1C, CD44, OTOF, MSR1) that distinguished COVID-19 from other infectious and non-infectious diseases with an AUC of 87.1% (95% CI: 82.6%-91.7%) in the discovery cohort and 88.7% and 93.6% when evaluated in the RT-qPCR validation, and in silico cohorts respectively. Interpretation. Using well-phenotyped samples collected from patients admitted acutely with a spectrum of infectious and non-infectious syndromes, we provide a detailed catalogue of blood gene expression at the time of hospital admission. The findings result in the identification of a 10-gene host diagnostic signature to accurately distinguish COVID-19 from other infection syndromes presenting to hospital. This could be developed into a rapid point-of-care diagnostic test, providing a valuable syndromic diagnostic tool for future early pandemic use.

Large scale phenotyping of long COVID inflammation reveals mechanistic subtypes of disease (preprint)

One in ten SARS-CoV-2 infections result in prolonged symptoms termed "long COVID", yet disease phenotypes and mechanisms are poorly understood. We studied the blood proteome of 719 adults, grouped by long COVID symptoms. Elevated markers of monocytic inflammation and complement activation were associated with increased likelihood of all symptoms. Elevated IL1R2, MATN2 and COLEC12 associated with cardiorespiratory symptoms, fatigue, and anxiety/depression, while elevated MATN2 and DPP10 associated with gastrointestinal (GI) symptoms, and elevated C1QA was associated with cognitive impairment (the proteome of those with cognitive impairment and GI symptoms being most distinct). Markers of neuroinflammation distinguished cognitive impairment whilst elevated SCG3, indicative of brain-gut axis disturbance, distinguished those with GI symptoms. Women had a higher incidence of long COVID and higher inflammatory markers. Symptoms did not associate with respiratory inflammation or persistent virus in sputum. Thus, persistent inflammation is evident in long COVID, distinct profiles being associated with specific symptoms.

Cohort Profile: Post-hospitalisation COVID-19 study (PHOSP-COVID) (preprint)

Abstract [bullet] PHOSP-COVID is a national UK multi-centre cohort study of patients who were hospitalised for COVID-19 and subsequently discharged. [bullet] PHOSP-COVID was established to investigate the medium- and long-term sequelae of severe COVID-19 requiring hospitalisation, understand the underlying mechanisms of these sequelae, evaluate the medium- and long-term effects of COVID-19 treatments, and to serve as a platform to enable future studies, including clinical trials. [bullet] Data collected covered a wide range of physical measures, biological samples, and Patient Reported Outcome Measures (PROMs). [bullet] Participants could join the cohort either in Tier 1 only with remote data collection using hospital records, a PROMs app and postal saliva sample for DNA, or in Tier 2 where they were invited to attend two specific research visits for further data collection and biological research sampling. These research visits occurred at five (range 2-7) months and 12 (range 10-14) months post-discharge. Participants could also participate in specific nested studies (Tier 3) at selected sites. [bullet] All participants were asked to consent to further follow-up for 25 years via linkage to their electronic healthcare records and to be re-contacted for further research. [bullet] In total, 7935 participants were recruited from 83 UK sites: 5238 to Tier 1 and 2697 to Tier 2, between August 2020 and March 2022. [bullet] Cohort data are held in a Trusted Research Environment and samples stored in a central biobank. Data and samples can be accessed upon request and subject to approvals.

Apixaban following discharge in hospitalised adults with COVID-19: Preliminary results from a multicentre, open-label, randomised controlled platform clinical trial. (preprint)

Background The role of thromboprophylaxis in the post-acute phase of COVID-19 is uncertain due to conflicting results from randomised controlled trials and observational studies. We aimed to determine the effectiveness of post-hospital apixaban in reducing the rate of death and hospital readmission of hospitalised adults with COVID-19. Methods HEAL COVID is an adaptive randomised open label multicentre platform trial recruiting participants from National Health Service Hospitals in the United Kingdom. Here we report the preliminary results of apixaban comparison of HEAL-COVID. Participants with a hospital admission related to confirmed COVID-19 and an expected date of discharge in the subsequent five days were randomised to either apixaban 2.5 mg twice daily or standard care (no anticoagulation) for 14 days. The primary outcome was hospital free survival at 12 months obtained through routine data sources. The trial was prospectively registered with ISRCTN (15851697) and Clincialtrials.gov (NCT04801940). Findings Between 19 May 2021 and 21 November 2022, 402 participants from 109 sites were randomised to apixaban and 399 to standard care. Seven participants withdrew from the apixaban group and one from the standard care group. Analysis was undertaken on an intention-to-treat basis. The apixaban arm was stopped on the recommendation of the oversight committees following an interim analysis due to no indication of benefit. Of the 402 participants randomised to apixaban, 117 experienced death or rehospitalisation during a median follow-up of 344.5 days (IQR 125 to 365), and 123 participants receiving standard care experienced death or rehospitalisation during a median follow-up of 349 days (IQR 124 to 365). There was no statistical difference in the rate of death and rehospitalisation (HR: 0.96 99%CI 0.69-1.34; p=0.75). Three participants in the apixaban arm experienced clinically significant bleeding during treatment. Interpretation Fourteen days of post-hospital anticoagulation with the direct oral anticoagulant apixaban did not reduce the rate of death or rehospitalisation of adults hospitalised with COVID-19. These data do not support the use of prophylactic post-hospital anticoagulation in adults with COVID-19. Funding HEAL-COVID is funded by the National Institute for Health and Care Research [NIHR133788] and the NIHR Cambridge Biomedical Research Centre [ BRC-1215-20014*].

Evaluation of S/F94 as a proxy for COVID-19 severity (preprint)

Optimising statistical power in early-stage trials and observational studies accelerates discovery and improves the reliability of results. Ideally, intermediate outcomes should be continuously distributed and lie on the causal pathway between an intervention and a definitive outcome such as mortality. In order to optimise power for an intermediate outcome in the RECOVERY trial, we devised and evaluated a modification to a simple, pragmatic measure of oxygenation function - the SaO2/FIO2 (S/F) ratio. We demonstrate that, because of the ceiling effect in oxyhaemoglobin saturation, S/F ceases to reflect pulmonary oxygenation function at high values of SaO2. Using synthetic and real data, we found that the correlation of S/F with a gold standard (PaO2/FIO2, P/F ratio) improved substantially when measurements with SaO2 > 0.94 are excluded(Spearman r, synthetic data: S/F: 0.31; S/F94: 0.85). We refer to this measure as S/F94. In order to test the underlying assumptions and validity of S/F94 as a predictor of a definitive outcome (mortality), we collected an observational dataset including over 39,000 hospitalised patients with COVID-19 in the ISARIC4C study. We first demonstrated that S/F94 is predictive of mortality in COVID-19. We then compared the sample sizes required for trials using different outcome measures (S/F94, the WHO ordinal scale, sustained improvement at day 28 and mortality at day 28) ensuring comparable effect sizes. The smallest sample size was needed when S/F94 on day 5 was used as an outcome measure. To facilitate future study design, we provide an online user interface to quantify realworld power for a range of outcomes and inclusion criteria, using a synthetic dataset retaining the population-level clinical associations in real data accrued in ISARIC4C https://isaric4c.net/endpoints. We demonstrated that S/F94 is superior to S/F as a measure of pulmonary oxygenation function and is an effective intermediate outcome measure in COVID-19. It is a simple and non-invasive measurement, representative of disease severity and provides greater statistical power to detect treatment differences than other intermediate endpoints.

Nasal IgA wanes 9 months after hospitalisation with COVID-19 and is not induced by subsequent vaccination. (preprint)

Background Most studies of immunity to SARS-CoV-2 focus on circulating antibody, giving limited insights into mucosal defences that prevent viral replication and onward transmission. We studied nasal and plasma antibody responses one year after hospitalisation for COVID-19, including a period when SARS-CoV-2 vaccination was introduced. Methods Plasma and nasosorption samples were prospectively collected from 446 adults hospitalised for COVID-19 between February 2020 and March 2021 via the ISARIC4C and PHOSP-COVID consortia. IgA and IgG responses to NP and S of ancestral SARS-CoV-2, Delta and Omicron (BA.1) variants were measured by electrochemiluminescence and compared with plasma neutralisation data. Findings Strong and consistent nasal anti-NP and anti-S IgA responses were demonstrated, which remained elevated for nine months. Nasal and plasma anti-S IgG remained elevated for at least 12 months with high plasma neutralising titres against all variants. Of 180 with complete data, 160 were vaccinated between 6 and 12 months; coinciding with rises in nasal and plasma IgA and IgG anti-S titres for all SARS-CoV-2 variants, although the change in nasal IgA was minimal. Samples 12 months after admission showed no association between nasal IgA and plasma IgG responses, indicating that nasal IgA responses are distinct from those in plasma and minimally boosted by vaccination. Interpretation The decline in nasal IgA responses 9 months after infection and minimal impact of subsequent vaccination may explain the lack of long-lasting nasal defence against reinfection and the limited effects of vaccination on transmission. These findings highlight the need to develop vaccines that enhance nasal immunity.

Outcome of COVID-19 in hospitalised immunocompromised patients: an analysis of the WHO ISARIC CCP-UK prospective cohort study. (preprint)

Background Immunocompromised patients may be at higher risk of mortality if hospitalised with COVID-19 compared with immunocompetent patients. However, previous studies have been contradictory. We aimed to determine whether immunocompromised patients were at greater risk of in-hospital death, and how this risk changed over the pandemic. Methods We included patients >=19yrs with symptomatic community-acquired COVID-19 recruited to the ISARIC WHO Clinical Characterisation Protocol UK. We defined immunocompromise as: immunosuppressant medication preadmission, cancer treatment, organ transplant, HIV, or congenital immunodeficiency. We used logistic regression to compare the risk of death in both groups, adjusting for age, sex, deprivation, ethnicity, vaccination and co-morbidities. We used Bayesian logistic regression to explore mortality over time. Findings Between 17/01/2020 and 28/02/2022 we recruited 156,552 eligible patients, of whom 21,954 (14%) were immunocompromised. 29% (n=6,499) of immunocompromised and 21% (n=28,608) of immunocompetent patients died in hospital. The odds of inhospital mortality were elevated for immunocompromised patients (adjOR 1.44, 95% CI 1.39-1.50, p<0.001). As the pandemic progressed, in-hospital mortality reduced more slowly for immunocompromised patients than for immunocompetent patients. This was particularly evident with increasing age: the probability of the reduction in hospital mortality being less for immunocompromised patients aged 50-69yrs was 88% for men and 83% for women, and for those >80yrs was 99% for men, and 98% for women. Conclusions Immunocompromised patients remain at elevated risk of death from COVID-19. Targeted measures such as additional vaccine doses and monoclonal antibodies should be considered for this group.

SARS-CoV-2 infection is associated with anti-desmoglein 2 autoantibody detection. (preprint)

Post-acute cardiac sequelae, following SARS-CoV-2 infection, are well recognised as complications of COVID-19. We have previously shown the persistence of autoantibodies against antigens in skin, muscle, and heart in individuals following severe COVID-19; the most common staining on skin tissue displayed an inter-cellular cement pattern consistent with antibodies against desmosomal proteins. Desmosomes play a critical role in maintaining the structural integrity of tissues. For this reason, we analysed desmosomal protein levels and the presence of anti-desmoglein (DSG) 1, 2 and 3 antibodies in acute and convalescent sera from patients with COVID 19 of differing clinical severity. We find increased levels of DSG2 protein in sera from acute COVID patients. Furthermore, we find that DSG2 autoantibody levels are increased significantly in convalescent sera following severe COVID-19 but not in hospitalised patients recovering from influenza infection or healthy controls. Levels of autoantibody in sera from patients with severe COVID-19 were comparable to levels in patients with non-COVID-19-associated cardiac disease, potentially identifying DSG2 autoantibodies as a novel biomarker for cardiac damage. To determine if there was any association between severe COVID-19 and DSG2, we stained post-mortem cardiac tissue from patients who died from COVID-19 infection. This revealed disruption of the intercalated disc between cardiomyocytes that was consistent with separation of the DSG2 protein homodimer. Our results reveal the potential for DSG2 protein and autoimmunity to DSG2 to contribute to unexpected pathologies associated with COVID-19 infection.

Clinical characteristics with inflammation profiling of Long-COVID and association with one-year recovery following hospitalisation in the UK: a prospective observational study (preprint)

Background There are currently no effective pharmacological or non-pharmacological interventions for Long-COVID. To identify potential therapeutic targets, we focussed on previously described four recovery clusters five months after hospital discharge, their underlying inflammatory profiles and relationship with clinical outcomes at one year. Methods PHOSP-COVID is a prospective longitudinal cohort study, recruiting adults hospitalised with COVID-19 across the UK. Recovery was assessed using patient reported outcomes measures (PROMs), physical performance, and organ function at five-months and one-year after hospital discharge. Hierarchical logistic regression modelling was performed for patient-perceived recovery at one-year. Cluster analysis was performed using clustering large applications (CLARA) k-medoids approach using clinical outcomes at five-months. Inflammatory protein profiling from plasma at the five-month visit was performed. Findings 2320 participants have been assessed at five months after discharge and 807 participants have completed both five-month and one-year visits. Of these, 35.6% were female, mean age 58.7 (SD 12.5) years, and 27.8% received invasive mechanical ventilation (IMV). The proportion of patients reporting full recovery was unchanged between five months 501/165 (25.6%) and one year 232/804 (28.9%). Factors associated with being less likely to report full recovery at one year were: female sex OR 0.68 (95% CI 0.46-0.99), obesity OR 0.50 (95%CI 0.34-0.74) and IMV OR 0.42 (95%CI 0.23-0.76). Cluster analysis (n=1636) corroborated the previously reported four clusters: very severe, severe, moderate/cognitive, mild relating to the severity of physical, mental health and cognitive impairments at five months in a larger sample. There was elevation of inflammatory mediators of tissue damage and repair in both the very severe and the moderate/cognitive clusters compared to the mild cluster including interleukin-6 which was elevated in both comparisons. Overall, there was a substantial deficit in median (IQR) EQ5D-5L utility index from pre-COVID (retrospective assessment) 0.88 (0.74-1.00), five months 0.74 (0.60-0.88) to one year: 0.74 (0.59-0.88), with minimal improvements across all outcome measures at one-year after discharge in the whole cohort and within each of the four clusters. Interpretation The sequelae of a hospital admission with COVID-19 remain substantial one year after discharge across a range of health domains with the minority in our cohort feeling fully recovered. Patient perceived health-related quality of life remains reduced at one year compared to pre-hospital admission. Systematic inflammation and obesity are potential treatable traits that warrant further investigation in clinical trials.

Comparison of children and young people admitted with SARS-CoV-2 across the UK in the first and second pandemic waves: prospective multicentre observational cohort study (preprint)

BackgroundChildren and young people (CYP) were less affected than adults in the first wave of SARS-CoV-2 in the UK. We test the hypothesis that clinical characteristics of hospitalized CYP with SARS-CoV-2 in the UK second wave would differ from the first due to the combined impact of the alpha variant, school reopening and relaxation of shielding. MethodsPatients <19 years hospitalised in the UK with clinician-reported SARS-CoV-2 were enrolled in a prospective multicentre observational cohort study between 17th January 2020 and 31st January 2021. Minimum follow up time was two weeks. Clinical characteristics were compared between the first (W1) and second wave (W2) of infections. Findings2044 CYP aged <19 years were reported from 187 hospitals. 427/2044 (20.6%) had asymptomatic/incidental SARS-CoV-2 infection and were excluded from main analysis. 16.0% (248/1548) of symptomatic CYP were admitted to critical care and 0.8% (12/1504) died. 5.6% (91/1617) of symptomatic CYP had Multisystem Inflammatory Syndrome in Children (MIS-C). Patients in W2 were significantly older (median age 6.5 years, IQR 0.3-14.9) than W1 (4.0 (0.4-13.6, p 0.015). Fever was more common in W1, otherwise presenting symptoms and comorbidities were similar across waves. After excluding CYP with MIS-C, patients in W2 had lower PEWS at presentation, lower antibiotic use and less respiratory and cardiovascular support compared to W1. There was no change in the proportion of CYP admitted to critical care between W1 and W2. 58.0% (938/1617) of symptomatic CYP had no reported comorbidity. Patients without co-morbidities were younger (42.4%, 398/938, <1 year old), had lower Paediatric Early Warning Scores (PEWS) at presentation, shorter length of hospital stay and received less respiratory support. MIS-C was responsible for a large proportion of critical care admissions, invasive and non-invasive ventilatory support, inotrope and intravenous corticosteroid use in CYP without comorbidities. InterpretationSevere disease in CYP admitted with symptomatic SARS-CoV-2 in the UK remains rare. One in five CYP in this cohort had asymptomatic/incidental SARS-CoV-2 infection. We found no evidence of increased disease severity in W2 compared with W1. FundingShort form: National Institute for Health Research, UK Medical Research Council, Wellcome Trust, Department for International Development and the Bill and Melinda Gates Foundation. Long form: This work is supported by grants from the National Institute for Health Research (award CO-CIN-01) and the Medical Research Council (grant MC_PC_19059) and by the National Institute for Health Research Health Protection Research Unit (NIHR HPRU) in Emerging and Zoonotic Infections at University of Liverpool in partnership with Public Health England (PHE), in collaboration with Liverpool School of Tropical Medicine and the University of Oxford (NIHR award 200907), Wellcome Trust and Department for International Development (215091/Z/18/Z), and the Bill and Melinda Gates Foundation (OPP1209135). Liverpool Experimental Cancer Medicine Centre provided infrastructure support for this research (grant reference: C18616/A25153). JSN-V-T is seconded to the Department of Health and Social Care, England (DHSC). The views expressed are those of the authors and not necessarily those of the DHSC, DID, NIHR, MRC, Wellcome Trust, or PHE.

Evaluation of the effectiveness of remdesivir in treating severe COVID-19 using data from the ISARIC WHO Clinical Characterisation Protocol UK: a prospective, national cohort study. (preprint)

Background Remdesivir was given UK early-access approval for use in COVID-19 in people aged 12 years and older on 26th May 2020 on the basis of unmet clinical need. Evidence on the side effects, complications of therapy and effectiveness of this therapy is lacking or conflicting. Methods Adults with severe COVID-19 treated with remdesivir were compared with propensity-score matched controls, identified from the ISARIC WHO Clinical Characterisation Protocol study of UK hospitalised patients with COVID-19. Remdesivir patients were matched to controls according to baseline underlying 14-day mortality risk. The effect of remdesivir on short-term outcomes was investigated (primary outcome: 14-day mortality). Effect sizes were estimated and adjusted for potential confounders using multivariable modelling. Results 1,549 patients given remdesivir and 4,964 matched controls were identified satisfying inclusion and exclusion criteria. The balance diagnostic threshold was achieved. Patients had symptoms for a median of 6 days prior to baseline; 62% were male, with mean (SD) age 63.1 (15.6) years, and 80% categorised as White ethnicity. Fourteen-day mortality was not statistically significantly associated with treatment (9.3% remdesivir vs. 11.9% controls, odds-ratio 0.80, [95% CI 0.60-1.07], p=0.116, adjusted for age, sex, number of key comorbidities, dexamethasone use, and diagnosis of viral pneumonia. Findings Treatment with remdesivir was not associated with a reduction in mortality in our primary endpoint at 14 days. Interpretation Remdesivir did not significantly improve mortality in this study. The findings are subject to the limitations of an observational study. Balance was achieved for measured baseline factors, but unmeasured confounders may account for observed treatment effect sizes. Funding Medical Research Council UK & National Institute of Health Research

Physical, cognitive and mental health impacts of COVID-19 following hospitalisation: a multi-centre prospective cohort study (preprint)

Background The impact of COVID-19 on physical and mental health, and employment following hospitalisation is poorly understood. Methods PHOSP-COVID is a multi-centre, UK, observational study of adults discharged from hospital with a clinical diagnosis of COVID-19 involving an assessment between two- and seven-months later including detailed symptom, physiological and biochemical testing. Multivariable logistic regression was performed for patient-perceived recovery with age, sex, ethnicity, body mass index (BMI), co-morbidities, and severity of acute illness as co-variates. Cluster analysis was performed using outcomes for breathlessness, fatigue, mental health, cognition and physical function. Findings We report findings of 1077 patients discharged in 2020, from the assessment undertaken a median 5 [IQR4 to 6] months later: 36% female, mean age 58 [SD 13] years, 69% white ethnicity, 27% mechanical ventilation, and 50% had at least two co-morbidities. At follow-up only 29% felt fully recovered, 20% had a new disability, and 19% experienced a health-related change in occupation. Factors associated with failure to recover were female, middle-age, white ethnicity, two or more co-morbidities, and more severe acute illness. The magnitude of the persistent health burden was substantial and weakly related to acute severity. Four clusters were identified with different severities of mental and physical health impairment: 1) Very severe (17%), 2) Severe (21%), 3) Moderate with cognitive impairment (17%), 4) Mild (46%), with 3%, 7%, 36% and 43% feeling fully recovered, respectively. Persistent systemic inflammation determined by C-reactive protein was related to cluster severity, but not acute illness severity. Interpretation We identified factors related to recovery from a hospital admission with COVID-19 and four different phenotypes relating to the severity of physical, mental, and cognitive health five months later. The implications for clinical care include the potential to stratify care and the need for a pro-active approach with wide-access to COVID-19 holistic clinical services. Funding: UKRI and NIHR

Changes in UK hospital mortality in the first wave of COVID-19: the ISARIC WHO Clinical Characterisation Protocol prospective multicentre observational cohort study (preprint)

Background Mortality rates of UK patients hospitalised with COVID-19 appeared to fall during the first wave. We quantify potential drivers of this change and identify groups of patients who remain at high risk of dying in hospital. Methods The International Severe Acute Respiratory and emerging Infection Consortium (ISARIC) WHO Clinical Characterisation Protocol UK recruited a prospective cohort admitted to 247 acute UK hospitals with COVID-19 in the first wave (March to August 2020). Outcome was hospital mortality within 28 days of admission. We performed a three-way decomposition mediation analysis using natural effects models to explore associations between week of admission and hospital mortality adjusting for confounders (demographics, comorbidity, illness severity) and quantifying potential mediators (respiratory support and steroids). Findings Unadjusted hospital mortality fell from 32.3% (95%CI 31.8, 32.7) in March/April to 16.4% (95%CI 15.0, 17.8) in June/July 2020. Reductions were seen in all ages, ethnicities, both sexes, and in comorbid and non-comorbid patients. After adjustment, there was a 19% reduction in the odds of mortality per 4 week period (OR 0.81, 95%CI 0.79, 0.83). 15.2% of this reduction was explained by greater disease severity and comorbidity earlier in the epidemic. The use of respiratory support changed with greater use of non-invasive ventilation (NIV). 22.2% (OR 0.94, 95%CI 0.94, 0.96) of the reduction in mortality was mediated by changes in respiratory support. Interpretation The fall in hospital mortality in COVID-19 patients during the first wave in the UK was partly accounted for by changes in case mix and illness severity. A significant reduction was associated with differences in respiratory support and critical care use, which may partly reflect improved clinical decision making. The remaining improvement in mortality is not explained by these factors, and may relate to community behaviour on inoculum dose and hospital capacity strain. Funding NIHR & MRC

Short-term forecasts to inform the response to the COVID-19 epidemic in the UK (preprint)

Background: Short-term forecasts of infectious disease can create situational awareness and inform planning for outbreak response. Here, we report on multi-model forecasts of Covid-19 in the UK that were generated at regular intervals starting at the end of March 2020, in order to monitor expected healthcare utilisation and population impacts in real time. Methods: We evaluated the performance of individual model forecasts generated between 24 March and 14 July 2020, using a variety of metrics including the weighted interval score as well as metrics that assess the calibration, sharpness, bias and absolute error of forecasts separately. We further combined the predictions from individual models to ensemble forecasts using a simple mean as well as a quantile regression average that aimed to maximise performance. We further compared model performance to a null model of no change. Results: In most cases, individual models performed better than the null model, and ensembles models were well calibrated and performed comparatively to the best individual models. The quantile regression average did not noticeably outperform the mean ensemble. Conclusions: Ensembles of multi-model forecasts can inform the policy response to the Covid-19 pandemic by assessing future resource needs and expected population impact of morbidity and mortality.

Mental Health Status of Adolescents During the COVID-19 Pandemic: A Cross-sectional Survey among the Bangladeshi Graduate Students at Dhaka City (preprint)

ObjectivesTo identify the level of Mental Health Status of Adolescents During the COVID-19 Pandemic among the Bangladeshi Graduate Student at Dhaka MethodA cross-sectional survey was conducted with 330 students from different public and Private Universities in Dhaka, Bangladesh between April 01, 2020 and July 31, 2020 amid the COVID-19 lockdown period in Bangladesh. A standard, self-administered online questionnaire consisting of questions on socio-demographic variables, mental health status, as well as stress management sent to the respondents through social networking platforms. Data were analyzed using descriptive statistics, t-test, one-way ANOVA and correlation tests. ResultsThe mean score of mental health status was 2.08 based on four points scale. They felt problem in decision making (3.04), in doing the things well (2.92), in enjoying normal day to day life (2.88), in playing a useful part in life (2.85), in doing their task (2.75), living in perfectly well and in good health (2.70). The respondents also developed a suicidal tendency (2.55), felt nervous in strung-up (2.24), took longer time to do things (2.14), felt tightness and pressure in head (2.12), and found themselves pressurized by various stuff (2.05). This study also found a significant positive relationship between mental health status and age, living with parents, and parents attitude. Finally, this study revealed that the respondents managed their stress by chatting with their friends, parents and siblings, and by sleeping. ConclusionMental health status of adolescents was found moderate in this study. This study suggests further large-scale study including different socio-economic settings in order to figure out the real scenario of adolescents mental health status of the country during the pandemic.

A retrospective cluster analysis of COVID-19 cases by county (preprint)

The COVID-19 pandemic in the U.S. has exhibited distinct waves, the first beginning in March 2020, the second beginning in early June, and additional waves currently emerging. Paradoxically, almost no county has exhibited this multi-wave pattern. We aim to answer three research questions: (1) How many distinct clusters of counties exhibit similar COVID-19 patterns in the time-series of daily confirmed cases?; (2) What is the geographic distribution of the counties within each cluster? and (3) Are county-level demographic, socioeconomic and political variables associated with the COVID-19 case patterns? We analyzed data from counties in the U.S. from March 1 to October 24, 2020. Time series clustering identified clusters in the daily confirmed cases of COVID-19. An explanatory model was used to identify demographic, socioeconomic and political variables associated the cluster patterns. Four patterns were identified from the timing of the outbreaks including counties experiencing a spring, an early summer, a late summer, and a fall outbreak. Several county-level demographic, socioeconomic, and political variables showed significant associations with the identified clusters. The timing of the outbreak is related both to the geographic location within the U.S. and several variables including age, poverty distribution, and political association. These results show that the reported pattern of cases in the U.S. is observed through aggregation of the COVID-19 cases, suggesting that local trends may be more informative. The timing of the outbreak varies by county, and is associated with important demographic, socioeconomic and geographic factors.

Human Identical Sequences of SARS-CoV-2 Promote Clinical Progression of COVID-19 by Upregulating Hyaluronan via NamiRNA-Enhancer Network (preprint)

The COVID-19 pandemic is a widespread and deadly public health crisis. The pathogen SARS-CoV-2 replicates in the lower respiratory tract and causes fatal pneumonia. Although tremendous efforts have been put into investigating the pathogeny of SARS-CoV-2, the underlying mechanism of how SARS-CoV-2 interacts with its host is largely unexplored. Here, by comparing the genomic sequences of SARS-CoV-2 and human, we identified five fully conserved elements in SARS-CoV-2 genome, which were termed as "human identical sequences (HIS)". HIS are also recognized in both SARS-CoV and MERS-CoV genome. Meanwhile, HIS-SARS-CoV-2 are highly conserved in the primate. Mechanically, HIS-SARS-CoV-2 RNA directly binds to the targeted loci in human genome and further interacts with host enhancers to activate the expression of adjacent and distant genes, including cytokines gene and angiotensin converting enzyme II (ACE2), a well-known cell entry receptor of SARS-CoV-2, and hyaluronan synthase 2 (HAS2), which further increases hyaluronan formation. Noteworthily, hyaluronan level in plasma of COVID-19 patients is tightly correlated with severity and high risk for acute respiratory distress syndrome (ARDS) and may act as a predictor for the progression of COVID-19. HIS antagomirs, which downregulate hyaluronan level effectively, and 4-Methylumbelliferone (MU), an inhibitor of hyaluronan synthesis, are potential drugs to relieve the ARDS related ground-glass pattern in lung for COVID-19 treatment. Our results revealed that unprecedented HIS elements of SARS-CoV-2 contribute to the cytokine storm and ARDS in COVID-19 patients. Thus, blocking HIS-involved activating processes or hyaluronan synthesis directly by 4-MU may be effective strategies to alleviate COVID-19 progression.

The circulating SARS-CoV-2 spike variant N439K maintains fitness while evading antibody-mediated immunity (preprint)

SARS-CoV-2 can mutate to evade immunity, with consequences for the efficacy of emerging vaccines and antibody therapeutics. Herein we demonstrate that the immunodominant SARS-CoV-2 spike (S) receptor binding motif (RBM) is the most divergent region of S, and provide epidemiological, clinical, and molecular characterization of a prevalent RBM variant, N439K. We demonstrate that N439K S protein has enhanced binding affinity to the hACE2 receptor, and that N439K virus has similar clinical outcomes and in vitro replication fitness as compared to wild- type. We observed that the N439K mutation resulted in immune escape from a panel of neutralizing monoclonal antibodies, including one in clinical trials, as well as from polyclonal sera from a sizeable fraction of persons recovered from infection. Immune evasion mutations that maintain virulence and fitness such as N439K can emerge within SARS-CoV-2 S, highlighting the need for ongoing molecular surveillance to guide development and usage of vaccines and therapeutics.

Development and validation of the 4C Deterioration model for adults hospitalised with COVID-19 (preprint)

Prognostic models to predict the risk of clinical deterioration in acute COVID-19 are required to inform clinical management decisions. Among 75,016 consecutive adults across England, Scotland and Wales prospectively recruited to the ISARIC Coronavirus Clinical Characterisation Consortium (ISARIC4C) study, we developed and validated a multivariable logistic regression model for in-hospital clinical deterioration (defined as any requirement of ventilatory support or critical care, or death) using 11 routinely measured variables. We used internal-external cross-validation to show consistent measures of discrimination, calibration and clinical utility across eight geographical regions. We further validated the final model in held-out data from 8,252 individuals in London, with similarly consistent performance (C-statistic 0.77 (95% CI 0.75 to 0.78); calibration-in-the-large 0.01 (-0.04 to 0.06); calibration slope 0.96 (0.90 to 1.02)). Importantly, this model demonstrated higher net benefit than using other candidate scores to inform decision-making. Our 4C Deterioration model thus demonstrates unprecedented clinical utility and generalisability to predict clinical deterioration among adults hospitalised with COVID-19.