ORCID Profile
0000-0002-1984-4014
Current Organisations
National Institute for Health Research
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University Hospitals Birmingham NHS Foundation Trust
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University of Birmingham
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Publisher: Elsevier BV
Date: 11-2021
Publisher: Elsevier BV
Date: 12-2021
Publisher: Springer Science and Business Media LLC
Date: 13-09-2022
DOI: 10.1186/S13054-022-04155-1
Abstract: Up to 30% of hospitalised patients with COVID-19 require advanced respiratory support, including high-flow nasal cannulas (HFNC), non-invasive mechanical ventilation (NIV), or invasive mechanical ventilation (IMV). We aimed to describe the clinical characteristics, outcomes and risk factors for failing non-invasive respiratory support in patients treated with severe COVID-19 during the first two years of the pandemic in high-income countries (HICs) and low middle-income countries (LMICs). This is a multinational, multicentre, prospective cohort study embedded in the ISARIC-WHO COVID-19 Clinical Characterisation Protocol. Patients with laboratory-confirmed SARS-CoV-2 infection who required hospital admission were recruited prospectively. Patients treated with HFNC, NIV, or IMV within the first 24 h of hospital admission were included in this study. Descriptive statistics, random forest, and logistic regression analyses were used to describe clinical characteristics and compare clinical outcomes among patients treated with the different types of advanced respiratory support. A total of 66,565 patients were included in this study. Overall, 82.6% of patients were treated in HIC, and 40.6% were admitted to the hospital during the first pandemic wave. During the first 24 h after hospital admission, patients in HICs were more frequently treated with HFNC (48.0%), followed by NIV (38.6%) and IMV (13.4%). In contrast, patients admitted in lower- and middle-income countries (LMICs) were less frequently treated with HFNC (16.1%) and the majority received IMV (59.1%). The failure rate of non-invasive respiratory support (i.e. HFNC or NIV) was 15.5%, of which 71.2% were from HIC and 28.8% from LMIC. The variables most strongly associated with non-invasive ventilation failure, defined as progression to IMV, were high leukocyte counts at hospital admission (OR [95%CI] 5.86 [4.83–7.10]), treatment in an LMIC (OR [95%CI] 2.04 [1.97–2.11]), and tachypnoea at hospital admission (OR [95%CI] 1.16 [1.14–1.18]). Patients who failed HFNC/NIV had a higher 28-day fatality ratio (OR [95%CI] 1.27 [1.25–1.30]). In the present international cohort, the most frequently used advanced respiratory support was the HFNC. However, IMV was used more often in LMIC. Higher leucocyte count, tachypnoea, and treatment in LMIC were risk factors for HFNC/NIV failure. HFNC/NIV failure was related to worse clinical outcomes, such as 28-day mortality. Trial registration This is a prospective observational study therefore, no health care interventions were applied to participants, and trial registration is not applicable.
Publisher: American Medical Association (AMA)
Date: 10-2023
DOI: 10.1001/JAMAPEDIATRICS.2023.3117
Abstract: Multiple SARS-CoV-2 variants have emerged over the COVID-19 pandemic. The implications for COVID-19 severity in children worldwide are unclear. To determine whether the dominant circulating SARS-CoV-2 variants of concern (VOCs) were associated with differences in COVID-19 severity among hospitalized children. Clinical data from hospitalized children and adolescents (younger than 18 years) who were SARS-CoV-2 positive were obtained from 9 countries (Australia, Brazil, Italy, Portugal, South Africa, Switzerland, Thailand, UK, and the US) during 3 different time frames. Time frames 1 (T1), 2 (T2), and 3 (T3) were defined to represent periods of dominance by the ancestral virus, pre-Omicron VOCs, and Omicron, respectively. Age groups for analysis were younger than 6 months, 6 months to younger than 5 years, and 5 to younger than 18 years. Children with an incidental positive test result for SARS-CoV-2 were excluded. SARS-CoV-2 hospitalization during the stipulated time frame. The severity of disease was assessed by admission to intensive care unit (ICU), the need for ventilatory support, or oxygen therapy. Among 31 785 hospitalized children and adolescents, the median age was 4 (IQR 1-12) years and 16 639 were male (52.3%). In children younger than 5 years, across successive SARS-CoV-2 waves, there was a reduction in ICU admission (T3 vs T1: risk ratio [RR], 0.56 95% CI, 0.42-0.75 [younger than 6 months] RR, 0.61, 95% CI 0.47-0.79 [6 months to younger than 5 years]), but not ventilatory support or oxygen therapy. In contrast, ICU admission (T3 vs T1: RR, 0.39, 95% CI, 0.32-0.48), ventilatory support (T3 vs T1: RR, 0.37 95% CI, 0.27-0.51), and oxygen therapy (T3 vs T1: RR, 0.47 95% CI, 0.32-0.70) decreased across SARS-CoV-2 waves in children 5 years to younger than 18 years old. The results were consistent when data were restricted to unvaccinated children. This study provides valuable insights into the impact of SARS-CoV-2 VOCs on the severity of COVID-19 in hospitalized children across different age groups and countries, suggesting that while ICU admissions decreased across the pandemic in all age groups, ventilatory and oxygen support generally did not decrease over time in children aged younger than 5 years. These findings highlight the importance of considering different pediatric age groups when assessing disease severity in COVID-19.
Publisher: European Respiratory Society (ERS)
Date: 10-12-2021
DOI: 10.1183/23120541.00552-2021
Abstract: Due to the large number of patients with severe coronavirus disease 2019 (COVID-19), many were treated outside the traditional walls of the intensive care unit (ICU), and in many cases, by personnel who were not trained in critical care. The clinical characteristics and the relative impact of caring for severe COVID-19 patients outside the ICU is unknown. This was a multinational, multicentre, prospective cohort study embedded in the International Severe Acute Respiratory and Emerging Infection Consortium World Health Organization COVID-19 platform. Severe COVID-19 patients were identified as those admitted to an ICU and/or those treated with one of the following treatments: invasive or noninvasive mechanical ventilation, high-flow nasal cannula, inotropes or vasopressors. A logistic generalised additive model was used to compare clinical outcomes among patients admitted or not to the ICU. A total of 40 440 patients from 43 countries and six continents were included in this analysis. Severe COVID-19 patients were frequently male (62.9%), older adults (median (interquartile range (IQR), 67 (55–78) years), and with at least one comorbidity (63.2%). The overall median (IQR) length of hospital stay was 10 (5–19) days and was longer in patients admitted to an ICU than in those who were cared for outside the ICU (12 (6–23) days versus 8 (4–15) days, p .0001). The 28-day fatality ratio was lower in ICU-admitted patients (30.7% (5797 out of 18 831) versus 39.0% (7532 out of 19 295), p .0001). Patients admitted to an ICU had a significantly lower probability of death than those who were not (adjusted OR 0.70, 95% CI 0.65–0.75 p .0001). Patients with severe COVID-19 admitted to an ICU had significantly lower 28-day fatality ratio than those cared for outside an ICU.
Publisher: BMJ
Date: 10-2022
DOI: 10.1136/BMJPO-2022-001657
Abstract: The impact of the COVID-19 pandemic on paediatric populations varied between high-income countries (HICs) versus low-income to middle-income countries (LMICs). We sought to investigate differences in paediatric clinical outcomes and identify factors contributing to disparity between countries. The International Severe Acute Respiratory and Emerging Infections Consortium (ISARIC) COVID-19 database was queried to include children under 19 years of age admitted to hospital from January 2020 to April 2021 with suspected or confirmed COVID-19 diagnosis. Univariate and multivariable analysis of contributing factors for mortality were assessed by country group (HICs vs LMICs) as defined by the World Bank criteria. A total of 12 860 children (3819 from 21 HICs and 9041 from 15 LMICs) participated in this study. Of these, 8961 were laboratory-confirmed and 3899 suspected COVID-19 cases. About 52% of LMICs children were black, and more than 40% were infants and adolescent. Overall in-hospital mortality rate (95% CI) was 3.3% [=(3.0% to 3.6%), higher in LMICs than HICs (4.0% (3.6% to 4.4%) and 1.7% (1.3% to 2.1%), respectively). There were significant differences between country income groups in intervention profile, with higher use of antibiotics, antivirals, corticosteroids, prone positioning, high flow nasal cannula, non-invasive and invasive mechanical ventilation in HICs. Out of the 439 mechanically ventilated children, mortality occurred in 106 (24.1%) subjects, which was higher in LMICs than HICs (89 (43.6%) vs 17 (7.2%) respectively). Pre-existing infectious comorbidities (tuberculosis and HIV) and some complications (bacterial pneumonia, acute respiratory distress syndrome and myocarditis) were significantly higher in LMICs compared with HICs. On multivariable analysis, LMIC as country income group was associated with increased risk of mortality (adjusted HR 4.73 (3.16 to 7.10)). Mortality and morbidities were higher in LMICs than HICs, and it may be attributable to differences in patient demographics, complications and access to supportive and treatment modalities.
Publisher: Elsevier BV
Date: 04-2021
Publisher: Springer Science and Business Media LLC
Date: 27-04-2022
DOI: 10.1038/S41598-022-08032-3
Abstract: COVID-19 is clinically characterised by fever, cough, and dyspnoea. Symptoms affecting other organ systems have been reported. However, it is the clinical associations of different patterns of symptoms which influence diagnostic and therapeutic decision-making. In this study, we applied clustering techniques to a large prospective cohort of hospitalised patients with COVID-19 to identify clinically meaningful sub-phenotypes. We obtained structured clinical data on 59,011 patients in the UK (the ISARIC Coronavirus Clinical Characterisation Consortium, 4C) and used a principled, unsupervised clustering approach to partition the first 25,477 cases according to symptoms reported at recruitment. We validated our findings in a second group of 33,534 cases recruited to ISARIC-4C, and in 4,445 cases recruited to a separate study of community cases. Unsupervised clustering identified distinct sub-phenotypes. First, a core symptom set of fever, cough, and dyspnoea, which co-occurred with additional symptoms in three further patterns: fatigue and confusion, diarrhoea and vomiting, or productive cough. Presentations with a single reported symptom of dyspnoea or confusion were also identified, alongside a sub-phenotype of patients reporting few or no symptoms. Patients presenting with gastrointestinal symptoms were more commonly female, had a longer duration of symptoms before presentation, and had lower 30-day mortality. Patients presenting with confusion, with or without core symptoms, were older and had a higher unadjusted mortality. Symptom sub-phenotypes were highly consistent in replication analysis within the ISARIC-4C study. Similar patterns were externally verified in patients from a study of self-reported symptoms of mild disease. The large scale of the ISARIC-4C study enabled robust, granular discovery and replication. Clinical interpretation is necessary to determine which of these observations have practical utility. We propose that four sub-phenotypes are usefully distinct from the core symptom group: gastro-intestinal disease, productive cough, confusion, and pauci-symptomatic presentations. Importantly, each is associated with an in-hospital mortality which differs from that of patients with core symptoms.
Publisher: Elsevier BV
Date: 10-2023
Publisher: Springer Science and Business Media LLC
Date: 08-07-2021
DOI: 10.1038/S41586-021-03767-X
Abstract: The genetic make-up of an in idual contributes to the susceptibility and response to viral infection. Although environmental, clinical and social factors have a role in the chance of exposure to SARS-CoV-2 and the severity of COVID-19 1,2 , host genetics may also be important. Identifying host-specific genetic factors may reveal biological mechanisms of therapeutic relevance and clarify causal relationships of modifiable environmental risk factors for SARS-CoV-2 infection and outcomes. We formed a global network of researchers to investigate the role of human genetics in SARS-CoV-2 infection and COVID-19 severity. Here we describe the results of three genome-wide association meta-analyses that consist of up to 49,562 patients with COVID-19 from 46 studies across 19 countries. We report 13 genome-wide significant loci that are associated with SARS-CoV-2 infection or severe manifestations of COVID-19. Several of these loci correspond to previously documented associations to lung or autoimmune and inflammatory diseases 3–7 . They also represent potentially actionable mechanisms in response to infection. Mendelian randomization analyses support a causal role for smoking and body-mass index for severe COVID-19 although not for type II diabetes. The identification of novel host genetic factors associated with COVID-19 was made possible by the community of human genetics researchers coming together to prioritize the sharing of data, results, resources and analytical frameworks. This working model of international collaboration underscores what is possible for future genetic discoveries in emerging pandemics, or indeed for any complex human disease.
Publisher: Cold Spring Harbor Laboratory
Date: 05-07-2021
DOI: 10.1101/2021.07.04.21259945
Abstract: Continuous positive airways pressure (CPAP) and high-flow nasal oxygen (HFNO) are considered ‘aerosol-generating procedures’ (AGPs) in the treatment of COVID-19. We aimed to measure air and surface environmental contamination of SARS-CoV-2 virus when CPAP and HFNO were used, compared with supplemental oxygen, to investigate the potential risks of viral transmission to healthcare workers and patients. 30 hospitalised patients with COVID-19 requiring supplemental oxygen, with a fraction of inspired oxygen ≥0.4 to maintain oxygen saturations ≥94%, were prospectively enrolled into an observational environmental s ling study. Participants received either supplemental oxygen, CPAP or HFNO (n=10 in each group). A nasopharyngeal swab, three air and three surface s les were collected from each participant and the clinical environment. RT qPCR analyses were performed for viral and human RNA, and positive/suspected-positive s les were cultured for the presence of biologically viable virus. Overall 21/30 (70%) of participants tested positive for SARS-CoV-2 RNA in the nasopharynx. In contrast, only 4/90 (4%) and 6/90 (7%) of all air and surface s les tested positive (positive for E and ORF1a) for viral RNA respectively, although there were an additional 10 suspected-positive s les in both air and surfaces s les (positive for E or ORF1a). CPAP/HFNO use or coughing was not associated with significantly more environmental contamination. Only one nasopharyngeal s le was culture positive. The use of CPAP and HFNO to treat moderate/severe COVID-19 was not associated with significantly higher levels of air or surface viral contamination in the immediate care environment.
Publisher: American Medical Association (AMA)
Date: 08-02-2022
Publisher: Elsevier BV
Date: 03-2021
Publisher: BMJ
Date: 04-11-2021
DOI: 10.1136/THORAXJNL-2021-218035
Abstract: Continuous positive airways pressure (CPAP) and high-flow nasal oxygen (HFNO) are considered ‘aerosol-generating procedures’ in the treatment of COVID-19. To measure air and surface environmental contamination with SARS-CoV-2 virus when CPAP and HFNO are used, compared with supplemental oxygen, to investigate the potential risks of viral transmission to healthcare workers and patients. 30 hospitalised patients with COVID-19 requiring supplemental oxygen, with a fraction of inspired oxygen ≥0.4 to maintain oxygen saturation ≥94%, were prospectively enrolled into an observational environmental s ling study. Participants received either supplemental oxygen, CPAP or HFNO (n=10 in each group). A nasopharyngeal swab, three air and three surface s les were collected from each participant and the clinical environment. Real-time quantitative polymerase chain reaction analyses were performed for viral and human RNA, and positive/suspected-positive s les were cultured for the presence of biologically viable virus. Overall 21/30 (70%) participants tested positive for SARS-CoV-2 RNA in the nasopharynx. In contrast, only 4/90 (4%) and 6/90 (7%) of all air and surface s les tested positive (positive for E and ORF1a) for viral RNA respectively, although there were an additional 10 suspected-positive s les in both air and surfaces s les (positive for E or ORF1a). CPAP/HFNO use or coughing was not associated with significantly more environmental contamination than supplemental oxygen use. Only one nasopharyngeal s le was culture positive. The use of CPAP and HFNO to treat moderate/severe COVID-19 did not appear to be associated with substantially higher levels of air or surface viral contamination in the immediate care environment, compared with the use of supplemental oxygen.
Publisher: Elsevier BV
Date: 12-2020
Publisher: eLife Sciences Publications, Ltd
Date: 05-10-2022
DOI: 10.7554/ELIFE.80556
Abstract: Whilst timely clinical characterisation of infections caused by novel SARS-CoV-2 variants is necessary for evidence-based policy response, in idual-level data on infecting variants are typically only available for a minority of patients and settings. Here, we propose an innovative approach to study changes in COVID-19 hospital presentation and outcomes after the Omicron variant emergence using publicly available population-level data on variant relative frequency to infer SARS-CoV-2 variants likely responsible for clinical cases. We apply this method to data collected by a large international clinical consortium before and after the emergence of the Omicron variant in different countries. Our analysis, that includes more than 100,000 patients from 28 countries, suggests that in many settings patients hospitalised with Omicron variant infection less often presented with commonly reported symptoms compared to patients infected with pre-Omicron variants. Patients with COVID-19 admitted to hospital after Omicron variant emergence had lower mortality compared to patients admitted during the period when Omicron variant was responsible for only a minority of infections (odds ratio in a mixed-effects logistic regression adjusted for likely confounders, 0.67 [95% confidence interval 0.61–0.75]). Qualitatively similar findings were observed in sensitivity analyses with different assumptions on population-level Omicron variant relative frequencies, and in analyses using available in idual-level data on infecting variant for a subset of the study population. Although clinical studies with matching viral genomic information should remain a priority, our approach combining publicly available data on variant frequency and a multi-country clinical characterisation dataset with more than 100,000 records allowed analysis of data from a wide range of settings and novel insights on real-world heterogeneity of COVID-19 presentation and clinical outcome. Bronner P. Gonçalves, Peter Horby, Gail Carson, Piero L. Olliaro, Valeria Balan, Barbara Wanjiru Citarella, and research costs were supported by the UK Foreign, Commonwealth and Development Office (FCDO) and Wellcome [215091/Z/18/Z, 222410/Z/21/Z, 225288/Z/22/Z] and Janice Caoili and Madiha Hashmi were supported by the UK FCDO and Wellcome [222048/Z/20/Z]. Peter Horby, Gail Carson, Piero L. Olliaro, Kalynn Kennon and Joaquin Baruch were supported by the Bill & Melinda Gates Foundation [OPP1209135] Laura Merson was supported by University of Oxford’s COVID-19 Research Response Fund - with thanks to its donors for their philanthropic support. Matthew Hall was supported by a Li Ka Shing Foundation award to Christophe Fraser. Moritz U.G. Kraemer was supported by the Branco Weiss Fellowship, Google.org, the Oxford Martin School, the Rockefeller Foundation, and the European Union Horizon 2020 project MOOD (#874850). The contents of this publication are the sole responsibility of the authors and do not necessarily reflect the views of the European Commission. Contributions from Srinivas Murthy, Asgar Rishu, Rob Fowler, James Joshua Douglas, François Martin Carrier were supported by CIHR Coronavirus Rapid Research Funding Opportunity OV2170359 and coordinated out of Sunnybrook Research Institute. Contributions from Evert-Jan Wils and David S.Y. Ong were supported by a grant from foundation Bevordering Onderzoek Franciscus and Andrea Angheben by the Italian Ministry of Health “Fondi Ricerca corrente–L1P6” to IRCCS Ospedale Sacro Cuore–Don Calabria. The data contributions of J.Kenneth Baillie, Malcolm G. Semple, and Ewen M. Harrison were supported by grants from the National Institute for Health Research (NIHR award CO-CIN-01), the Medical Research Council (MRC grant MC_PC_19059), and by the NIHR Health Protection Research Unit (HPRU) in Emerging and Zoonotic Infections at University of Liverpool in partnership with Public Health England (PHE) (award 200907), NIHR HPRU in Respiratory Infections at Imperial College London with PHE (award 200927), Liverpool Experimental Cancer Medicine Centre (grant C18616/A25153), NIHR Biomedical Research Centre at Imperial College London (award IS-BRC-1215-20013), and NIHR Clinical Research Network providing infrastructure support. All funders of the ISARIC Clinical Characterisation Group are listed in the appendix.
Publisher: Springer Science and Business Media LLC
Date: 11-12-2021
DOI: 10.1038/S41586-020-03065-Y
Abstract: Host-mediated lung inflammation is present
Publisher: Wiley
Date: 05-09-2022
DOI: 10.1111/IRV.13039
Abstract: Case definitions are used to guide clinical practice, surveillance and research protocols. However, how they identify COVID‐19‐hospitalised patients is not fully understood. We analysed the proportion of hospitalised patients with laboratory‐confirmed COVID‐19, in the ISARIC prospective cohort study database, meeting widely used case definitions. Patients were assessed using the Centers for Disease Control (CDC), European Centre for Disease Prevention and Control (ECDC), World Health Organization (WHO) and UK Health Security Agency (UKHSA) case definitions by age, region and time. Case fatality ratios (CFRs) and symptoms of those who did and who did not meet the case definitions were evaluated. Patients with incomplete data and non‐laboratory‐confirmed test result were excluded. A total of 263,218 of the patients (42%) in the ISARIC database were included. Most patients (90.4%) were from Europe and Central Asia. The proportions of patients meeting the case definitions were 56.8% (WHO), 74.4% (UKHSA), 81.6% (ECDC) and 82.3% (CDC). For each case definition, patients at the extremes of age distribution met the criteria less frequently than those aged 30 to 70 years geographical and time variations were also observed. Estimated CFRs were similar for the patients who met the case definitions. However, when more patients did not meet the case definition, the CFR increased. The performance of case definitions might be different in different regions and may change over time. Similarly concerning is the fact that older patients often did not meet case definitions, risking delayed medical care. While epidemiologists must balance their analytics with field applicability, ongoing revision of case definitions is necessary to improve patient care through early diagnosis and limit potential nosocomial spread.
Publisher: Elsevier BV
Date: 02-2022
Publisher: Elsevier BV
Date: 02-2021
Publisher: Elsevier BV
Date: 10-2023
Publisher: Oxford University Press (OUP)
Date: 10-09-2022
Abstract: Different neurological manifestations of coronavirus disease 2019 (COVID-19) in adults and children and their impact have not been well characterized. We aimed to determine the prevalence of neurological manifestations and in-hospital complications among hospitalized COVID-19 patients and ascertain differences between adults and children. We conducted a prospective multicentre observational study using the International Severe Acute Respiratory and emerging Infection Consortium (ISARIC) cohort across 1507 sites worldwide from 30 January 2020 to 25 May 2021. Analyses of neurological manifestations and neurological complications considered unadjusted prevalence estimates for predefined patient subgroups, and adjusted estimates as a function of patient age and time of hospitalization using generalized linear models. Overall, 161 239 patients (158 267 adults 2972 children) hospitalized with COVID-19 and assessed for neurological manifestations and complications were included. In adults and children, the most frequent neurological manifestations at admission were fatigue (adults: 37.4% children: 20.4%), altered consciousness (20.9% 6.8%), myalgia (16.9% 7.6%), dysgeusia (7.4% 1.9%), anosmia (6.0% 2.2%) and seizure (1.1% 5.2%). In adults, the most frequent in-hospital neurological complications were stroke (1.5%), seizure (1%) and CNS infection (0.2%). Each occurred more frequently in intensive care unit (ICU) than in non-ICU patients. In children, seizure was the only neurological complication to occur more frequently in ICU versus non-ICU (7.1% versus 2.3%, P & 0.001). Stroke prevalence increased with increasing age, while CNS infection and seizure steadily decreased with age. There was a dramatic decrease in stroke over time during the pandemic. Hypertension, chronic neurological disease and the use of extracorporeal membrane oxygenation were associated with increased risk of stroke. Altered consciousness was associated with CNS infection, seizure and stroke. All in-hospital neurological complications were associated with increased odds of death. The likelihood of death rose with increasing age, especially after 25 years of age. In conclusion, adults and children have different neurological manifestations and in-hospital complications associated with COVID-19. Stroke risk increased with increasing age, while CNS infection and seizure risk decreased with age.
Publisher: Elsevier BV
Date: 04-2022
Publisher: Elsevier BV
Date: 09-2023
Publisher: Elsevier BV
Date: 03-2021
Publisher: Elsevier BV
Date: 2022
Publisher: Public Library of Science (PLoS)
Date: 13-09-2023
Publisher: Elsevier BV
Date: 07-2020
Publisher: Elsevier BV
Date: 08-2023
Publisher: Elsevier BV
Date: 10-2020
Publisher: Elsevier BV
Date: 05-2023
Publisher: Elsevier BV
Date: 09-2021
Publisher: Elsevier BV
Date: 05-2021
Publisher: Cold Spring Harbor Laboratory
Date: 25-07-2020
DOI: 10.1101/2020.07.17.20155218
Abstract: ISARIC (International Severe Acute Respiratory and emerging Infections Consortium) partnerships and outbreak preparedness initiatives enabled the rapid launch of standardised clinical data collection on COVID-19 in Jan 2020. Extensive global participation has resulted in a large, standardised collection of comprehensive clinical data from hundreds of sites across dozens of countries. Data are analysed regularly and reported publicly to inform patient care and public health response. This report, our 17th report, is a part of a series published over the past 2 years. Data have been entered for 800,459 in iduals from 1701 partner institutions and networks across 60 countries. The comprehensive analyses detailed in this report includes hospitalised in iduals of all ages for whom data collection occurred between 30 January 2020 and up to and including 5 January 2022, AND who have laboratory-confirmed SARS-COV-2 infection or clinically diagnosed COVID-19. For the 699,014 cases who meet eligibility criteria for this report, selected findings include: median age of 58 years, with an approximately equal (50/50) male:female sex distribution 29% of the cohort are at least 70 years of age, whereas 4% are 0-19 years of age the most common symptom combination in this hospitalised cohort is shortness of breath, cough, and history of fever, which has remained constant over time the five most common symptoms at admission were shortness of breath, cough, history of fever, fatigue/malaise, and altered consciousness/confusion, which is unchanged from the previous reports age-associated differences in symptoms are evident, including the frequency of altered consciousness increasing with age, and fever, respiratory and constitutional symptoms being present mostly in those 40 years and above 16% of patients with relevant data available were admitted at some point during their illness into an intensive care unit (ICU), which is slightly lower than previously reported (19%) antibiotic agents were used in 35% of patients for whom relevant data are available (669,630), a significant reduction from our previous reports (80%) which reflects a shifting proportion of data contributed by different institutions in ICU/HDU admitted patients with data available (50,560), 91% received antibiotics use of corticosteroids was reported in 24% of all patients for whom data were available (677,012) in ICU/HDU admitted patients with data available (50,646), 69% received corticosteroids outcomes are known for 632,518 patients and the overall estimated case fatality ratio (CFR) is 23.9% (95%CI 23.8-24.1), rising to 37.1% (95%CI 36.8-37.4) for patients who were admitted to ICU/HDU, demonstrating worse outcomes in those with the most severe disease To access previous versions of ISARIC COVID-19 Clinical Data Report please use the link below: esearch/covid-19-clinical-research-resources/evidence-reports/
Publisher: Springer Science and Business Media LLC
Date: 30-07-2022
DOI: 10.1038/S41597-022-01534-9
Abstract: The International Severe Acute Respiratory and Emerging Infection Consortium (ISARIC) COVID-19 dataset is one of the largest international databases of prospectively collected clinical data on people hospitalized with COVID-19. This dataset was compiled during the COVID-19 pandemic by a network of hospitals that collect data using the ISARIC-World Health Organization Clinical Characterization Protocol and data tools. The database includes data from more than 705,000 patients, collected in more than 60 countries and 1,500 centres worldwide. Patient data are available from acute hospital admissions with COVID-19 and outpatient follow-ups. The data include signs and symptoms, pre-existing comorbidities, vital signs, chronic and acute treatments, complications, dates of hospitalization and discharge, mortality, viral strains, vaccination status, and other data. Here, we present the dataset characteristics, explain its architecture and how to gain access, and provide tools to facilitate its use.
Publisher: eLife Sciences Publications, Ltd
Date: 23-11-2021
DOI: 10.7554/ELIFE.70970
Abstract: There is potentially considerable variation in the nature and duration of the care provided to hospitalised patients during an infectious disease epidemic or pandemic. Improvements in care and clinician confidence may shorten the time spent as an inpatient, or the need for admission to an intensive care unit (ICU) or high dependency unit (HDU). On the other hand, limited resources at times of high demand may lead to rationing. Nevertheless, these variables may be used as static proxies for disease severity, as outcome measures for trials, and to inform planning and logistics. We investigate these time trends in an extremely large international cohort of 142,540 patients hospitalised with COVID-19. Investigated are: time from symptom onset to hospital admission, probability of ICU/HDU admission, time from hospital admission to ICU/HDU admission, hospital case fatality ratio (hCFR) and total length of hospital stay. Time from onset to admission showed a rapid decline during the first months of the pandemic followed by peaks during August/September and December 2020. ICU/HDU admission was more frequent from June to August. The hCFR was lowest from June to August. Raw numbers for overall hospital stay showed little variation, but there is clear decline in time to discharge for ICU/HDU survivors. Our results establish that variables of these kinds have limitations when used as outcome measures in a rapidly evolving situation. 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 funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Publisher: Elsevier BV
Date: 05-2021
Publisher: Springer Science and Business Media LLC
Date: 11-07-2023
Publisher: Elsevier BV
Date: 2021
Publisher: Elsevier BV
Date: 2023
Publisher: Elsevier BV
Date: 07-2022
Publisher: Cold Spring Harbor Laboratory
Date: 22-06-2022
DOI: 10.1101/2022.06.22.22276764
Abstract: Whilst timely clinical characterisation of infections caused by novel SARS-CoV-2 variants is necessary for evidence-based policy response, in idual-level data on infecting variants are typically only available for a minority of patients and settings. Here, we propose an innovative approach to study changes in COVID-19 hospital presentation and outcomes after the Omicron variant emergence using publicly available population-level data on variant relative frequency to infer SARS-CoV-2 variants likely responsible for clinical cases. We apply this method to data collected by a large international clinical consortium before and after the emergence of the Omicron variant in different countries. Our analysis, that includes more than 100,000 patients from 28 countries, suggests that in many settings patients hospitalised with Omicron variant infection less often presented with commonly reported symptoms compared to patients infected with pre-Omicron variants. Patients with COVID-19 admitted to hospital after Omicron variant emergence had lower mortality compared to patients admitted during the period when Omicron variant was responsible for only a minority of infections (odds ratio in a mixed-effects logistic regression adjusted for likely confounders, 0.67 [95% confidence interval 0.61 – 0.75]). Qualitatively similar findings were observed in sensitivity analyses with different assumptions on population-level Omicron variant relative frequencies, and in analyses using available in idual-level data on infecting variant for a subset of the study population. Although clinical studies with matching viral genomic information should remain a priority, our approach combining publicly available data on variant frequency and a multi-country clinical characterisation dataset with more than 100,000 records allowed analysis of data from a wide range of settings and novel insights on real-world heterogeneity of COVID-19 presentation and clinical outcome.
Publisher: Massachusetts Medical Society
Date: 19-07-2100
Publisher: Springer Science and Business Media LLC
Date: 17-05-2023
DOI: 10.1038/S41586-023-06034-3
Abstract: Critical illness in COVID-19 is an extreme and clinically homogeneous disease phenotype that we have previously shown 1 to be highly efficient for discovery of genetic associations 2 . Despite the advanced stage of illness at presentation, we have shown that host genetics in patients who are critically ill with COVID-19 can identify immunomodulatory therapies with strong beneficial effects in this group 3 . Here we analyse 24,202 cases of COVID-19 with critical illness comprising a combination of microarray genotype and whole-genome sequencing data from cases of critical illness in the international GenOMICC (11,440 cases) study, combined with other studies recruiting hospitalized patients with a strong focus on severe and critical disease: ISARIC4C (676 cases) and the SCOURGE consortium (5,934 cases). To put these results in the context of existing work, we conduct a meta-analysis of the new GenOMICC genome-wide association study (GWAS) results with previously published data. We find 49 genome-wide significant associations, of which 16 have not been reported previously. To investigate the therapeutic implications of these findings, we infer the structural consequences of protein-coding variants, and combine our GWAS results with gene expression data using a monocyte transcriptome-wide association study (TWAS) model, as well as gene and protein expression using Mendelian randomization. We identify potentially druggable targets in multiple systems, including inflammatory signalling ( JAK1 ), monocyte–macrophage activation and endothelial permeability ( PDE4A ), immunometabolism ( SLC2A5 and AK5 ), and host factors required for viral entry and replication ( TMPRSS2 and RAB2A ).
Publisher: Cold Spring Harbor Laboratory
Date: 16-08-2020
DOI: 10.1101/2020.08.14.20168088
Abstract: Severe COVID-19 is characterised by fever, cough, and dyspnoea. Symptoms affecting other organ systems have been reported. However, it is the clinical associations of different patterns of symptoms which influence diagnostic and therapeutic decision-making. In this study, we applied simple machine learning techniques to a large prospective cohort of hospitalised patients with COVID-19 identify clinically meaningful sub-groups. We obtained structured clinical data on 59 011 patients in the UK (the ISARIC Coronavirus Clinical Characterisation Consortium, 4C) and used a principled, unsupervised clustering approach to partition the first 25 477 cases according to symptoms reported at recruitment. We validated our findings in a second group of 33 534 cases recruited to ISARIC-4C, and in 4 445 cases recruited to a separate study of community cases. Unsupervised clustering identified distinct sub-groups. First, a core symptom set of fever, cough, and dyspnoea, which co-occurred with additional symptoms in three further patterns: fatigue and confusion, diarrhoea and vomiting, or productive cough. Presentations with a single reported symptom of dyspnoea or confusion were common, and a subgroup of patients reported few or no symptoms. Patients presenting with gastrointestinal symptoms were more commonly female, had a longer duration of symptoms before presentation, and had lower 30-day mortality. Patients presenting with confusion, with or without core symptoms, were older and had a higher unadjusted mortality. Symptom clusters were highly consistent in replication analysis using a further 35446 in iduals subsequently recruited to ISARIC-4C. Similar patterns were externally verified in 4445 patients from a study of self-reported symptoms of mild disease. The large scale of the ISARIC-4C study enabled robust, granular discovery and replication of patient clusters. Clinical interpretation is necessary to determine which of these observations have practical utility. We propose that four patterns are usefully distinct from the core symptom groups: gastro-intestinal disease, productive cough, confusion, and pauci-symptomatic presentations. Importantly, each is associated with an in-hospital mortality which differs from that of patients with core symptoms. These observations deepen our understanding of COVID-19 and will influence clinical diagnosis, risk prediction, and future mechanistic and clinical studies. Medical Research Council National Institute Health Research Well-come Trust Department for International Development Bill and Melinda Gates Foundation Liverpool Experimental Cancer Medicine Centre.
Publisher: Elsevier BV
Date: 07-2023
Publisher: Cold Spring Harbor Laboratory
Date: 21-09-2021
DOI: 10.1101/2021.09.11.21263419
Abstract: Policymakers need robust data to respond to the COVID-19 pandemic. We describe demographic features, treatments and clinical outcomes in the International Severe Acute Respiratory and emerging Infection Consortium (ISARIC) COVID-19 cohort, the world’s largest international, standardised cohort of hospitalised patients. The dataset analysed includes COVID-19 patients hospitalised between January 2020 and May 2021. We investigated how symptoms on admission, comorbidities, risk factors, and treatments varied by age, sex, and other characteristics. We used Cox proportional hazards models to investigate associations between demographics, symptoms, comorbidities, and other factors with risk of death, admission to intensive care unit (ICU), and invasive mechanical ventilation (IMV). 439,922 patients with laboratory-confirmed (91.7%) or clinically-diagnosed (8.3%) SARS-CoV-2 infection from 49 countries were enrolled. Age (adjusted hazard ratio [HR] per 10 years 1.49 [95% CI 1.49-1.50]) and male sex (1.26 [1.24-1.28]) were associated with a higher risk of death. Rates of admission to ICU and use of IMV increased with age up to age 60, then dropped. Symptoms, comorbidities, and treatments varied by age and had varied associations with clinical outcomes. Tuberculosis was associated with an 86% higher risk of death, and HIV with an 87% higher risk of death. Case fatality ratio varied by country partly due to differences in the clinical characteristics of recruited patients. The size of our international database and the standardized data collection method makes this study a reliable and comprehensive international description of COVID-19 clinical features. This is a viable model to be applied to future epidemics. UK Foreign, Commonwealth and Development Office, the Bill & Melinda Gates Foundation and Wellcome. See acknowledgements section for funders of sites that contributed data. To identify large, international analyses of hospitalised COVID-19 patients that used standardised data collection, we conducted a systematic review of the literature from 1 Jan 2020 to 28 Apr 2020. We identified 78 studies, with data from 77,443 people (1) predominantly from China. We could not find any studies including data from low and middle-income countries. We repeated our search on 18 Aug 2021 but could not identify any further studies that met our inclusion criteria. Our study uses standardised clinical data collection to collect data from a vast number of patients across the world, including patients from low-, middle-, and high-income countries. The size of our database gives us great confidence in the accuracy of our descriptions of the global impact of COVID-19. We can confirm findings reported by smaller, country-specific studies and compare clinical data between countries. We have demonstrated that it is possible to collect large volumes of standardised clinical data during a pandemic of a novel acute respiratory infection. The results provide a valuable resource for present policymakers and future global health researchers. Presenting symptoms of SARS-CoV-2 infection in patients requiring hospitalisation are now well-described globally, with the most common being fever, cough, and shortness of breath. Other symptoms also commonly occur, including altered consciousness in older adults and gastrointestinal symptoms in younger patients, and age can influence the likelihood of a patient having symptoms that match one or more case definitions. There are geographic and temporal variations in the case fatality rate (CFR), but overall, CFR was 20.6% in this large international cohort of hospitalised patients with a median age of 60 years (IQR: 45 to 74 years).
Publisher: Springer Science and Business Media LLC
Date: 25-06-2021
DOI: 10.1007/S15010-021-01599-5
Abstract: The ISARIC prospective multinational observational study is the largest cohort of hospitalized patients with COVID-19. We present relationships of age, sex, and nationality to presenting symptoms. International, prospective observational study of 60 109 hospitalized symptomatic patients with laboratory-confirmed COVID-19 recruited from 43 countries between 30 January and 3 August 2020. Logistic regression was performed to evaluate relationships of age and sex to published COVID-19 case definitions and the most commonly reported symptoms. ‘Typical’ symptoms of fever (69%), cough (68%) and shortness of breath (66%) were the most commonly reported. 92% of patients experienced at least one of these. Prevalence of typical symptoms was greatest in 30- to 60-year-olds (respectively 80, 79, 69% at least one 95%). They were reported less frequently in children (≤ 18 years: 69, 48, 23 85%), older adults (≥ 70 years: 61, 62, 65 90%), and women (66, 66, 64 90% vs. men 71, 70, 67 93%, each P 0.001). The most common atypical presentations under 60 years of age were nausea and vomiting and abdominal pain, and over 60 years was confusion. Regression models showed significant differences in symptoms with sex, age and country. This international collaboration has allowed us to report reliable symptom data from the largest cohort of patients admitted to hospital with COVID-19. Adults over 60 and children admitted to hospital with COVID-19 are less likely to present with typical symptoms. Nausea and vomiting are common atypical presentations under 30 years. Confusion is a frequent atypical presentation of COVID-19 in adults over 60 years. Women are less likely to experience typical symptoms than men.
Publisher: Massachusetts Medical Society
Date: 25-02-2021
Publisher: Public Library of Science (PLoS)
Date: 20-04-2022
DOI: 10.1371/JOURNAL.PMED.1003969
Abstract: Acute kidney injury (AKI) is one of the most common and significant problems in patients with Coronavirus Disease 2019 (COVID-19). However, little is known about the incidence and impact of AKI occurring in the community or early in the hospital admission. The traditional Kidney Disease Improving Global Outcomes (KDIGO) definition can fail to identify patients for whom hospitalisation coincides with recovery of AKI as manifested by a decrease in serum creatinine (sCr). We hypothesised that an extended KDIGO (eKDIGO) definition, adapted from the International Society of Nephrology (ISN) 0by25 studies, would identify more cases of AKI in patients with COVID-19 and that these may correspond to community-acquired AKI (CA-AKI) with similarly poor outcomes as previously reported in this population. All in iduals recruited using the International Severe Acute Respiratory and Emerging Infection Consortium (ISARIC)–World Health Organization (WHO) Clinical Characterisation Protocol (CCP) and admitted to 1,609 hospitals in 54 countries with Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infection from February 15, 2020 to February 1, 2021 were included in the study. Data were collected and analysed for the duration of a patient’s admission. Incidence, staging, and timing of AKI were evaluated using a traditional and eKDIGO definition, which incorporated a commensurate decrease in sCr. Patients within eKDIGO diagnosed with AKI by a decrease in sCr were labelled as deKDIGO. Clinical characteristics and outcomes—intensive care unit (ICU) admission, invasive mechanical ventilation, and in-hospital death—were compared for all 3 groups of patients. The relationship between eKDIGO AKI and in-hospital death was assessed using survival curves and logistic regression, adjusting for disease severity and AKI susceptibility. A total of 75,670 patients were included in the final analysis cohort. Median length of admission was 12 days (interquartile range [IQR] 7, 20). There were twice as many patients with AKI identified by eKDIGO than KDIGO (31.7% versus 16.8%). Those in the eKDIGO group had a greater proportion of stage 1 AKI (58% versus 36% in KDIGO patients). Peak AKI occurred early in the admission more frequently among eKDIGO than KDIGO patients. Compared to those without AKI, patients in the eKDIGO group had worse renal function on admission, more in-hospital complications, higher rates of ICU admission (54% versus 23%) invasive ventilation (45% versus 15%), and increased mortality (38% versus 19%). Patients in the eKDIGO group had a higher risk of in-hospital death than those without AKI (adjusted odds ratio: 1.78, 95% confidence interval: 1.71 to 1.80, p -value 0.001). Mortality and rate of ICU admission were lower among deKDIGO than KDIGO patients (25% versus 50% death and 35% versus 70% ICU admission) but significantly higher when compared to patients with no AKI (25% versus 19% death and 35% versus 23% ICU admission) (all p -values × 10 −5 ). Limitations include ad hoc sCr s ling, exclusion of patients with less than two sCr measurements, and limited availability of sCr measurements prior to initiation of acute dialysis. An extended KDIGO definition of AKI resulted in a significantly higher detection rate in this population. These additional cases of AKI occurred early in the hospital admission and were associated with worse outcomes compared to patients without AKI.
Publisher: Oxford University Press (OUP)
Date: 28-02-2023
DOI: 10.1093/IJE/DYAD012
Abstract: We describe demographic features, treatments and clinical outcomes in the International Severe Acute Respiratory and emerging Infection Consortium (ISARIC) COVID-19 cohort, one of the world's largest international, standardized data sets concerning hospitalized patients. The data set analysed includes COVID-19 patients hospitalized between January 2020 and January 2022 in 52 countries. We investigated how symptoms on admission, co-morbidities, risk factors and treatments varied by age, sex and other characteristics. We used Cox regression models to investigate associations between demographics, symptoms, co-morbidities and other factors with risk of death, admission to an intensive care unit (ICU) and invasive mechanical ventilation (IMV). Data were available for 689 572 patients with laboratory-confirmed (91.1%) or clinically diagnosed (8.9%) SARS-CoV-2 infection from 52 countries. Age [adjusted hazard ratio per 10 years 1.49 (95% CI 1.48, 1.49)] and male sex [1.23 (1.21, 1.24)] were associated with a higher risk of death. Rates of admission to an ICU and use of IMV increased with age up to age 60 years then dropped. Symptoms, co-morbidities and treatments varied by age and had varied associations with clinical outcomes. The case-fatality ratio varied by country partly due to differences in the clinical characteristics of recruited patients and was on average 21.5%. Age was the strongest determinant of risk of death, with a ∼30-fold difference between the oldest and youngest groups each of the co-morbidities included was associated with up to an almost 2-fold increase in risk. Smoking and obesity were also associated with a higher risk of death. The size of our international database and the standardized data collection method make this study a comprehensive international description of COVID-19 clinical features. Our findings may inform strategies that involve prioritization of patients hospitalized with COVID-19 who have a higher risk of death.
Publisher: Elsevier BV
Date: 2021
DOI: 10.2139/SSRN.3779160
Location: United Kingdom of Great Britain and Northern Ireland
Location: United Kingdom of Great Britain and Northern Ireland
Location: United Kingdom of Great Britain and Northern Ireland
Location: United Kingdom of Great Britain and Northern Ireland
Location: United Kingdom of Great Britain and Northern Ireland
No related grants have been discovered for Christopher Green.