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

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.

Triglyceride Lowering with Pemafibrate to Reduce Cardiovascular Risk.

BACKGROUND: High triglyceride levels are associated with increased cardiovascular risk, but whether reductions in these levels would lower the incidence of cardiovascular events is uncertain. Pemafibrate, a selective peroxisome proliferator-activated receptor α modulator, reduces triglyceride levels and improves other lipid levels. METHODS: In a multinational, double-blind, randomized, controlled trial, we assigned patients with type 2 diabetes, mild-to-moderate hypertriglyceridemia (triglyceride level, 200 to 499 mg per deciliter), and high-density lipoprotein (HDL) cholesterol levels of 40 mg per deciliter or lower to receive pemafibrate (0.2-mg tablets twice daily) or matching placebo. Eligible patients were receiving guideline-directed lipid-lowering therapy or could not receive statin therapy without adverse effects and had low-density lipoprotein (LDL) cholesterol levels of 100 mg per deciliter or lower. The primary efficacy end point was a composite of nonfatal myocardial infarction, ischemic stroke, coronary revascularization, or death from cardiovascular causes. RESULTS: Among 10,497 patients (66.9% with previous cardiovascular disease), the median baseline fasting triglyceride level was 271 mg per deciliter, HDL cholesterol level 33 mg per deciliter, and LDL cholesterol level 78 mg per deciliter. The median follow-up was 3.4 years. As compared with placebo, the effects of pemafibrate on lipid levels at 4 months were -26.2% for triglycerides, -25.8% for very-low-density lipoprotein (VLDL) cholesterol, -25.6% for remnant cholesterol (cholesterol transported in triglyceride-rich lipoproteins after lipolysis and lipoprotein remodeling), -27.6% for apolipoprotein C-III, and 4.8% for apolipoprotein B. A primary end-point event occurred in 572 patients in the pemafibrate group and in 560 of those in the placebo group (hazard ratio, 1.03; 95% confidence interval, 0.91 to 1.15), with no apparent effect modification in any prespecified subgroup. The overall incidence of serious adverse events did not differ significantly between the groups, but pemafibrate was associated with a higher incidence of adverse renal events and venous thromboembolism and a lower incidence of nonalcoholic fatty liver disease. CONCLUSIONS: Among patients with type 2 diabetes, mild-to-moderate hypertriglyceridemia, and low HDL and LDL cholesterol levels, the incidence of cardiovascular events was not lower among those who received pemafibrate than among those who received placebo, although pemafibrate lowered triglyceride, VLDL cholesterol, remnant cholesterol, and apolipoprotein C-III levels. (Funded by the Kowa Research Institute; PROMINENT ClinicalTrials.gov number, NCT03071692.).

A MUC5B Gene Polymorphism, rs35705950-T, Confers Protective Effects Against COVID-19 Hospitalization but Not Severe Disease or Mortality.

Rationale: A common MUC5B gene polymorphism, rs35705950-T, is associated with idiopathic pulmonary fibrosis (IPF), but its role in severe acute respiratory syndrome coronavirus 2 infection and disease severity is unclear. Objectives: To assess whether rs35705950-T confers differential risk for clinical outcomes associated with coronavirus disease (COVID-19) infection among participants in the Million Veteran Program (MVP). Methods: The MUC5B rs35705950-T allele was directly genotyped among MVP participants; clinical events and comorbidities were extracted from the electronic health records. Associations between the incidence or severity of COVID-19 and rs35705950-T were analyzed within each ancestry group in the MVP followed by transancestry meta-analysis. Replication and joint meta-analysis were conducted using summary statistics from the COVID-19 Host Genetics Initiative (HGI). Sensitivity analyses with adjustment for additional covariates (body mass index, Charlson comorbidity index, smoking, asbestosis, rheumatoid arthritis with interstitial lung disease, and IPF) and associations with post-COVID-19 pneumonia were performed in MVP subjects. Measurements and Main Results: The rs35705950-T allele was associated with fewer COVID-19 hospitalizations in transancestry meta-analyses within the MVP (Ncases = 4,325; Ncontrols = 507,640; OR = 0.89 [0.82-0.97]; P = 6.86 × 10-3) and joint meta-analyses with the HGI (Ncases = 13,320; Ncontrols = 1,508,841; OR, 0.90 [0.86-0.95]; P = 8.99 × 10-5). The rs35705950-T allele was not associated with reduced COVID-19 positivity in transancestry meta-analysis within the MVP (Ncases = 19,168/Ncontrols = 492,854; OR, 0.98 [0.95-1.01]; P = 0.06) but was nominally significant (P < 0.05) in the joint meta-analysis with the HGI (Ncases = 44,820; Ncontrols = 1,775,827; OR, 0.97 [0.95-1.00]; P = 0.03). Associations were not observed with severe outcomes or mortality. Among individuals of European ancestry in the MVP, rs35705950-T was associated with fewer post-COVID-19 pneumonia events (OR, 0.82 [0.72-0.93]; P = 0.001). Conclusions: The MUC5B variant rs35705950-T may confer protection in COVID-19 hospitalizations.

Optimising Chest X-Rays for Image Analysis by Identifying and Removing Confounding Factors (preprint)

During the COVID-19 pandemic, the sheer volume of imaging performed in an emergency setting for COVID-19 diagnosis has resulted in a wide variability of clinical CXR acquisitions. This variation is seen in the CXR projections used, image annotations added and in the inspiratory effort and degree of rotation of clinical images. The image analysis community has attempted to ease the burden on overstretched radiology departments during the pandemic by developing automated COVID-19 diagnostic algorithms, the input for which has been CXR imaging. Large publicly available CXR datasets have been leveraged to improve deep learning algorithms for COVID-19 diagnosis. Yet the variable quality of clinically-acquired CXRs within publicly available datasets could have a profound effect on algorithm performance. COVID-19 diagnosis may be inferred by an algorithm from non-anatomical features on an image such as image labels. These imaging shortcuts may be dataset-specific and limit the generalisability of AI systems. Understanding and correcting key potential biases in CXR images is therefore an essential first step prior to CXR image analysis. In this study, we propose a simple and effective step-wise approach to pre-processing a COVID-19 chest X-ray dataset to remove undesired biases. We perform ablation studies to show the impact of each individual step. The results suggest that using our proposed pipeline could increase accuracy of the baseline COVID-19 detection algorithm by up to 13%.

Association of Kidney Comorbidities and Acute Kidney Failure With Unfavorable Outcomes After COVID-19 in Individuals With the Sickle Cell Trait.

Importance: Sickle cell trait (SCT), defined as the presence of 1 hemoglobin beta sickle allele (rs334-T) and 1 normal beta allele, is prevalent in millions of people in the US, particularly in individuals of African and Hispanic ancestry. However, the association of SCT with COVID-19 is unclear. Objective: To assess the association of SCT with the prepandemic health conditions in participants of the Million Veteran Program (MVP) and to assess the severity and sequelae of COVID-19. Design, Setting, and Participants: COVID-19 clinical data include 2729 persons with SCT, of whom 353 had COVID-19, and 129 848 SCT-negative individuals, of whom 13 488 had COVID-19. Associations between SCT and COVID-19 outcomes were examined using firth regression. Analyses were performed by ancestry and adjusted for sex, age, age squared, and ancestral principal components to account for population stratification. Data for the study were collected between March 2020 and February 2021. Exposures: The hemoglobin beta S (HbS) allele (rs334-T). Main Outcomes and Measures: This study evaluated 4 COVID-19 outcomes derived from the World Health Organization severity scale and phenotypes derived from International Classification of Diseases codes in the electronic health records. Results: Of the 132 577 MVP participants with COVID-19 data, mean (SD) age at the index date was 64.8 (13.1) years. Sickle cell trait was present in 7.8% of individuals of African ancestry and associated with a history of chronic kidney disease, diabetic kidney disease, hypertensive kidney disease, pulmonary embolism, and cerebrovascular disease. Among the 4 clinical outcomes of COVID-19, SCT was associated with an increased COVID-19 mortality in individuals of African ancestry (n = 3749; odds ratio, 1.77; 95% CI, 1.13 to 2.77; P = .01). In the 60 days following COVID-19, SCT was associated with an increased incidence of acute kidney failure. A counterfactual mediation framework estimated that on average, 20.7% (95% CI, -3.8% to 56.0%) of the total effect of SCT on COVID-19 fatalities was due to acute kidney failure. Conclusions and Relevance: In this genetic association study, SCT was associated with preexisting kidney comorbidities, increased COVID-19 mortality, and kidney morbidity.

Pharmacogenetic variants and risk of remdesivir-associated liver enzyme elevations in Million Veteran Program participants hospitalized with COVID-19.

Remdesivir is the first US Food and Drug Administration (FDA)-approved drug for the treatment of coronavirus disease 2019 (COVID-19). We conducted a retrospective pharmacogenetic study to examine remdesivir-associated liver enzyme elevation among Million Veteran Program participants hospitalized with COVID-19 between March 15, 2020, and June 30, 2021. Pharmacogene phenotypes were assigned using Stargazer. Linear regression was performed on peak log-transformed enzyme values, stratified by population, adjusted for age, sex, baseline liver enzymes, comorbidities, and 10 population-specific principal components. Patients on remdesivir had higher peak alanine aminotransferase (ALT) values following treatment initiation compared with patients not receiving remdesivir. Remdesivir administration was associated with a 33% and 24% higher peak ALT in non-Hispanic White (NHW) and non-Hispanic Black (NHB) participants (p < 0.001), respectively. In a multivariable model, NHW CYP2C19 intermediate/poor metabolizers had a 9% increased peak ALT compared with NHW normal/rapid/ultrarapid metabolizers (p = 0.015); this association was not observed in NHB participants. In summary, remdesivir-associated ALT elevations appear to be multifactorial, and further studies are needed.

Genetic Loci Associated With COVID-19 Positivity and Hospitalization in White, Black, and Hispanic Veterans of the VA Million Veteran Program.

SARS-CoV-2 has caused symptomatic COVID-19 and widespread death across the globe. We sought to determine genetic variants contributing to COVID-19 susceptibility and hospitalization in a large biobank linked to a national United States health system. We identified 19,168 (3.7%) lab-confirmed COVID-19 cases among Million Veteran Program participants between March 1, 2020, and February 2, 2021, including 11,778 Whites, 4,893 Blacks, and 2,497 Hispanics. A multi-population genome-wide association study (GWAS) for COVID-19 outcomes identified four independent genetic variants (rs8176719, rs73062389, rs60870724, and rs73910904) contributing to COVID-19 positivity, including one novel locus found exclusively among Hispanics. We replicated eight of nine previously reported genetic associations at an alpha of 0.05 in at least one population-specific or the multi-population meta-analysis for one of the four MVP COVID-19 outcomes. We used rs8176719 and three additional variants to accurately infer ABO blood types. We found that A, AB, and B blood types were associated with testing positive for COVID-19 compared with O blood type with the highest risk for the A blood group. We did not observe any genome-wide significant associations for COVID-19 severity outcomes among those testing positive. Our study replicates prior GWAS findings associated with testing positive for COVID-19 among mostly White samples and extends findings at three loci to Black and Hispanic individuals. We also report a new locus among Hispanics requiring further investigation. These findings may aid in the identification of novel therapeutic agents to decrease the morbidity and mortality of COVID-19 across all major ancestral populations.

APOL1 Risk Variants, Acute Kidney Injury, and Death in Participants With African Ancestry Hospitalized With COVID-19 From the Million Veteran Program.

IMPORTANCE: Coronavirus disease 2019 (COVID-19) confers significant risk of acute kidney injury (AKI). Patients with COVID-19 with AKI have high mortality rates. OBJECTIVE: Individuals with African ancestry with 2 copies of apolipoprotein L1 (APOL1) variants G1 or G2 (high-risk group) have significantly increased rates of kidney disease. We tested the hypothesis that the APOL1 high-risk group is associated with a higher-risk of COVID-19-associated AKI and death. DESIGN, SETTING, AND PARTICIPANTS: This retrospective cohort study included 990 participants with African ancestry enrolled in the Million Veteran Program who were hospitalized with COVID-19 between March 2020 and January 2021 with available genetic information. EXPOSURES: The primary exposure was having 2 APOL1 risk variants (RV) (APOL1 high-risk group), compared with having 1 or 0 risk variants (APOL1 low-risk group). MAIN OUTCOMES AND MEASURES: The primary outcome was AKI. The secondary outcomes were stages of AKI severity and death. Multivariable logistic regression analyses adjusted for preexisting comorbidities, medications, and inpatient AKI risk factors; 10 principal components of ancestry were performed to study these associations. We performed a subgroup analysis in individuals with normal kidney function prior to hospitalization (estimated glomerular filtration rate ≥60 mL/min/1.73 m2). RESULTS: Of the 990 participants with African ancestry, 905 (91.4%) were male with a median (IQR) age of 68 (60-73) years. Overall, 392 (39.6%) patients developed AKI, 141 (14%) developed stages 2 or 3 AKI, 28 (3%) required dialysis, and 122 (12.3%) died. One hundred twenty-five (12.6%) of the participants were in the APOL1 high-risk group. Patients categorized as APOL1 high-risk group had significantly higher odds of AKI (adjusted odds ratio [OR], 1.95; 95% CI, 1.27-3.02; P = .002), higher AKI severity stages (OR, 2.03; 95% CI, 1.37-2.99; P < .001), and death (OR, 2.15; 95% CI, 1.22-3.72; P = .007). The association with AKI persisted in the subgroup with normal kidney function (OR, 1.93; 95% CI, 1.15-3.26; P = .01). Data analysis was conducted between February 2021 and April 2021. CONCLUSIONS AND RELEVANCE: In this cohort study of veterans with African ancestry hospitalized with COVID-19 infection, APOL1 kidney risk variants were associated with higher odds of AKI, AKI severity, and death, even among individuals with prior normal kidney function.

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.

Actionable druggable genome-wide Mendelian randomization identifies repurposing opportunities for COVID-19.

Drug repurposing provides a rapid approach to meet the urgent need for therapeutics to address COVID-19. To identify therapeutic targets relevant to COVID-19, we conducted Mendelian randomization analyses, deriving genetic instruments based on transcriptomic and proteomic data for 1,263 actionable proteins that are targeted by approved drugs or in clinical phase of drug development. Using summary statistics from the Host Genetics Initiative and the Million Veteran Program, we studied 7,554 patients hospitalized with COVID-19 and >1 million controls. We found significant Mendelian randomization results for three proteins (ACE2, P = 1.6 × 10-6; IFNAR2, P = 9.8 × 10-11 and IL-10RB, P = 2.3 × 10-14) using cis-expression quantitative trait loci genetic instruments that also had strong evidence for colocalization with COVID-19 hospitalization. To disentangle the shared expression quantitative trait loci signal for IL10RB and IFNAR2, we conducted phenome-wide association scans and pathway enrichment analysis, which suggested that IFNAR2 is more likely to play a role in COVID-19 hospitalization. Our findings prioritize trials of drugs targeting IFNAR2 and ACE2 for early management of COVID-19.

The time is now: role of pragmatic clinical trials in guiding response to global pandemics.

Along with its heavy toll of morbidity and mortality, the coronavirus disease 2019 (COVID-19) pandemic exposed several limitations of the current global research response. The slow and inefficient process of carrying out traditional randomized clinical trials led regulatory authorities to hastily approve treatments and tests without sufficient evidence of safety and efficacy.We here outline issues with the current research platform, summarize shortcomings of traditional randomized clinical trials particularly apparent at the time of pandemics, and highlight the advantages of pragmatic clinical trials as an alternative to rapidly generate the needed clinical evidence. We further discuss barriers and challenges to pragmatic clinical trials implementation and explore opportunities for research institutions and regulatory authorities to facilitate widespread adoption of this vital research tool.As a subsequent wave of COVID-19, and/or another epidemic, are all but inevitable in our lifetime, we must ensure that our research infrastructure is conducive to carrying out pragmatic clinical trials to expeditiously generate the needed evidence and blunt the epidemic's toll on human lives and livelihoods.

Influenza vaccination: a 'shot' at INVESTing in cardiovascular health.

The link between viral respiratory infection and non-pulmonary organ-specific injury, including cardiac injury, has become increasingly appreciated during the current coronavirus disease 2019 (COVID-19) pandemic. Even prior to the pandemic, however, the association between acute infection with influenza and elevated cardiovascular risk was evident. The recently published results of the NHLBI-funded INfluenza Vaccine to Effectively Stop CardioThoracic Events and Decompensated (INVESTED) trial, a 5200 patient comparative effectiveness study of high-dose vs. standard-dose influenza vaccine to reduce cardiopulmonary events and mortality in a high-risk cardiovascular population, found no difference between strategies. However, the broader implications of influenza vaccine as a strategy to reduce morbidity in high-risk patients remain extremely important, with randomized controlled trial and observational data supporting vaccination in high-risk patients with cardiovascular disease. Given a favourable risk-benefit profile and widespread availability at generally low cost, we contend that influenza vaccination should remain a centrepiece of cardiovascular risk mitigation and describe the broader context of underutilization of this strategy. Few therapeutics in medicine offer seasonal efficacy from a single administration with generally mild, transient side effects, and exceedingly low rates of serious adverse effects. Infection control measures such as physical distancing, hand washing, and the use of masks during the COVID-19 pandemic have already been associated with substantially curtailed incidence of influenza outbreaks across the globe. Appending annual influenza vaccination to these measures represents an important public health and moral imperative.

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

An overview of the National COVID-19 Chest Imaging Database: data quality and cohort analysis (preprint)

The National COVID-19 Chest Imaging Database (NCCID) is a centralised database containing chest X-rays, chest Computed Tomography (CT) scans and cardiac Magnetic Resonance Images (MRI) from patients across the UK, jointly established by NHSX, the British Society of Thoracic Imaging (BSTI), Royal Surrey NHS Foundation Trust (RSNFT) and Faculty. The objective of the initiative is to support a better understanding of the coronavirus SARS-CoV-2 disease (COVID-19) and development of machine learning (ML) technologies that will improve care for patients hospitalised with a severe COVID-19 infection. The NCCID is now accumulating data from 20 NHS Trusts and Health Boards across England and Wales, with a total contribution of approximately 25,000 imaging studies in the training set (at time of writing) and is actively being used as a research tool by several organisations. This paper introduces the training dataset, including a snapshot analysis performed by NHSX covering: the completeness of clinical data, the availability of image data for the various use-cases (diagnosis, prognosis and longitudinal risk) and potential model confounders within the imaging data. The aim is to inform both existing and potential data users of the NCCIDs suitability for developing diagnostic/prognostic models. In addition, a cohort analysis was performed to measure the representativeness of the NCCID to the wider COVID-19 affected population. Three major aspects were included: geographic, demographic and temporal coverage, revealing good alignment in some categories, e.g., sex and identifying areas for improvements to data collection methods, particularly with respect to geographic coverage. All analyses and discussions are focused on the implications for building ML tools that will generalise well to the clinical use cases.

Vascular Thrombosis in Severe COVID-19: A Multicenter Study (preprint)

BACKGROUND: COVID-19 has been reported to be a prothrombotic condition. We aimed to compare the prevalence of vascular thrombosis in patients with either severe COVID-19 or non-COVID-19 viral pneumonia. METHODS: We analysed whole-body CT scanners obtained in consecutive patients admitted in three centers of the English national ECMO service. We included consecutive patients with either COVID-19 or non-COVID-19 viral pneumonia admitted from January 2019. The presence of vascular thrombosis (defined as pulmonary artery thrombus, venous thrombus, systemic arterial thrombus, or end organ infarct) and hemorrhage was recorded. Clinical outcomes were examined using a 7-point ordinal scale. RESULTS: 136 patients (45.2±10.6 years of age, 39/146 (27%) female) requiring ECMO support underwent whole-body CT scanner on admission. Of these 86 had COVID-19 pneumonia, and 50 had non-COVID-19 viral pneumonia. Vascular thrombosis was seen more often in patients with COVID-19 (OR 12.9 (95% CI 4.5;36.8)). There was no difference between the groups in the prevalence of hemorrhage (OR 2.1 (95%CI 0.6;7.2)). The risk of mortality was 1.8 (95%CI 0.97;3.44, p=0.06) in those with COVID-19 compared with non-COVID-19 pneumonia. Mortality was no different in COVID-19 patients with or without vascular thrombosis (HR 1.03 (95% CI 0.38;2.76, p=0.96) but was higher in those patients with hemorrhage on admission (HR 3.0 (95% CI 1.06;8.5, p=0.038)). CONCLUSION: COVID-19 is associated with a significantly higher prevalence of vascular thrombosis compared with non-COVID-19 viral pneumonias. Despite this, vascular thrombosis was not linked to poorer short-term prognosis in those with COVID-19.FUNDING STATEMENT: No funding to declare.DECLARATION OF INTERESTS: The authors have no conflict of interest to declare.ETHICS APPROVAL STATEMENT: The study was approved by the institutional review boards of the 3 centers with a waiver for consent due to the observational nature of the study.

The challenges of deploying artificial intelligence models in a rapidly evolving pandemic (preprint)

The COVID-19 pandemic, caused by the severe acute respiratory syndrome coronavirus 2, emerged into a world being rapidly transformed by artificial intelligence (AI) based on big data, computational power and neural networks. The gaze of these networks has in recent years turned increasingly towards applications in healthcare. It was perhaps inevitable that COVID-19, a global disease propagating health and economic devastation, should capture the attention and resources of the world's computer scientists in academia and industry. The potential for AI to support the response to the pandemic has been proposed across a wide range of clinical and societal challenges, including disease forecasting, surveillance and antiviral drug discovery. This is likely to continue as the impact of the pandemic unfolds on the world's people, industries and economy but a surprising observation on the current pandemic has been the limited impact AI has had to date in the management of COVID-19. This correspondence focuses on exploring potential reasons behind the lack of successful adoption of AI models developed for COVID-19 diagnosis and prognosis, in front-line healthcare services. We highlight the moving clinical needs that models have had to address at different stages of the epidemic, and explain the importance of translating models to reflect local healthcare environments. We argue that both basic and applied research are essential to accelerate the potential of AI models, and this is particularly so during a rapidly evolving pandemic. This perspective on the response to COVID-19, may provide a glimpse into how the global scientific community should react to combat future disease outbreaks more effectively.