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  1. Article ; Online: Prospective validation of the 4C prognostic models for adults hospitalised with COVID-19 using the ISARIC WHO Clinical Characterisation Protocol.

    Knight, Stephen R / Gupta, Rishi K / Ho, Antonia / Pius, Riinu / Buchan, Iain / Carson, Gail / Drake, Thomas M / Dunning, Jake / Fairfield, Cameron J / Gamble, Carrol / Green, Christopher A / Halpin, Sophie / Hardwick, Hayley E / Holden, Karl A / Horby, Peter W / Jackson, Clare / Mclean, Kenneth A / Merson, Laura / Nguyen-Van-Tam, Jonathan S /
    Norman, Lisa / Olliaro, Piero L / Pritchard, Mark G / Russell, Clark D / Shaw, Catherine A / Sheikh, Aziz / Solomon, Tom / Sudlow, Cathie / Swann, Olivia V / Turtle, Lance C W / Openshaw, Peter J M / Baillie, J Kenneth / Docherty, Annemarie / Semple, Malcolm G / Noursadeghi, Mahdad / Harrison, Ewen M

    Thorax

    2021  Volume 77, Issue 6, Page(s) 606–615

    Abstract: Purpose: To prospectively validate two risk scores to predict mortality (4C Mortality) and in-hospital deterioration (4C Deterioration) among adults hospitalised with COVID-19.: Methods: Prospective observational cohort study of adults (age ≥18 years) ...

    Abstract Purpose: To prospectively validate two risk scores to predict mortality (4C Mortality) and in-hospital deterioration (4C Deterioration) among adults hospitalised with COVID-19.
    Methods: Prospective observational cohort study of adults (age ≥18 years) with confirmed or highly suspected COVID-19 recruited into the International Severe Acute Respiratory and emerging Infections Consortium (ISARIC) WHO Clinical Characterisation Protocol UK (CCP-UK) study in 306 hospitals across England, Scotland and Wales. Patients were recruited between 27 August 2020 and 17 February 2021, with at least 4 weeks follow-up before final data extraction. The main outcome measures were discrimination and calibration of models for in-hospital deterioration (defined as any requirement of ventilatory support or critical care, or death) and mortality, incorporating predefined subgroups.
    Results: 76 588 participants were included, of whom 27 352 (37.4%) deteriorated and 12 581 (17.4%) died. Both the 4C Mortality (0.78 (0.77 to 0.78)) and 4C Deterioration scores (pooled C-statistic 0.76 (95% CI 0.75 to 0.77)) demonstrated consistent discrimination across all nine National Health Service regions, with similar performance metrics to the original validation cohorts. Calibration remained stable (4C Mortality: pooled slope 1.09, pooled calibration-in-the-large 0.12; 4C Deterioration: 1.00, -0.04), with no need for temporal recalibration during the second UK pandemic wave of hospital admissions.
    Conclusion: Both 4C risk stratification models demonstrate consistent performance to predict clinical deterioration and mortality in a large prospective second wave validation cohort of UK patients. Despite recent advances in the treatment and management of adults hospitalised with COVID-19, both scores can continue to inform clinical decision making.
    Trial registration number: ISRCTN66726260.
    MeSH term(s) Adolescent ; Adult ; COVID-19/therapy ; Hospital Mortality ; Humans ; Observational Studies as Topic ; Prognosis ; SARS-CoV-2 ; State Medicine ; World Health Organization
    Language English
    Publishing date 2021-11-22
    Publishing country England
    Document type Journal Article ; Observational Study ; Research Support, Non-U.S. Gov't
    ZDB-ID 204353-1
    ISSN 1468-3296 ; 0040-6376
    ISSN (online) 1468-3296
    ISSN 0040-6376
    DOI 10.1136/thoraxjnl-2021-217629
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  2. Article ; Online: Development and validation of the ISARIC 4C Deterioration model for adults hospitalised with COVID-19: a prospective cohort study.

    Gupta, Rishi K / Harrison, Ewen M / Ho, Antonia / Docherty, Annemarie B / Knight, Stephen R / van Smeden, Maarten / Abubakar, Ibrahim / Lipman, Marc / Quartagno, Matteo / Pius, Riinu / Buchan, Iain / Carson, Gail / Drake, Thomas M / Dunning, Jake / Fairfield, Cameron J / Gamble, Carrol / Green, Christopher A / Halpin, Sophie / Hardwick, Hayley E /
    Holden, Karl A / Horby, Peter W / Jackson, Clare / Mclean, Kenneth A / Merson, Laura / Nguyen-Van-Tam, Jonathan S / Norman, Lisa / Olliaro, Piero L / Pritchard, Mark G / Russell, Clark D / Scott-Brown, James / Shaw, Catherine A / Sheikh, Aziz / Solomon, Tom / Sudlow, Cathie / Swann, Olivia V / Turtle, Lance / Openshaw, Peter J M / Baillie, J Kenneth / Semple, Malcolm G / Noursadeghi, Mahdad

    The Lancet. Respiratory medicine

    2021  Volume 9, Issue 4, Page(s) 349–359

    Abstract: Background: Prognostic models to predict the risk of clinical deterioration in acute COVID-19 cases are urgently required to inform clinical management decisions.: Methods: We developed and validated a multivariable logistic regression model for in- ... ...

    Abstract Background: Prognostic models to predict the risk of clinical deterioration in acute COVID-19 cases are urgently required to inform clinical management decisions.
    Methods: 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) among consecutively hospitalised adults with highly suspected or confirmed COVID-19 who were prospectively recruited to the International Severe Acute Respiratory and Emerging Infections Consortium Coronavirus Clinical Characterisation Consortium (ISARIC4C) study across 260 hospitals in England, Scotland, and Wales. Candidate predictors that were specified a priori were considered for inclusion in the model on the basis of previous prognostic scores and emerging literature describing routinely measured biomarkers associated with COVID-19 prognosis. We used internal-external cross-validation to evaluate discrimination, calibration, and clinical utility across eight National Health Service (NHS) regions in the development cohort. We further validated the final model in held-out data from an additional NHS region (London).
    Findings: 74 944 participants (recruited between Feb 6 and Aug 26, 2020) were included, of whom 31 924 (43·2%) of 73 948 with available outcomes met the composite clinical deterioration outcome. In internal-external cross-validation in the development cohort of 66 705 participants, the selected model (comprising 11 predictors routinely measured at the point of hospital admission) showed consistent discrimination, calibration, and clinical utility across all eight NHS regions. In held-out data from London (n=8239), the model showed a similarly consistent performance (C-statistic 0·77 [95% CI 0·76 to 0·78]; calibration-in-the-large 0·00 [-0·05 to 0·05]); calibration slope 0·96 [0·91 to 1·01]), and greater net benefit than any other reproducible prognostic model.
    Interpretation: The 4C Deterioration model has strong potential for clinical utility and generalisability to predict clinical deterioration and inform decision making among adults hospitalised with COVID-19.
    Funding: National Institute for Health Research (NIHR), UK Medical Research Council, Wellcome Trust, Department for International Development, Bill & Melinda Gates Foundation, EU Platform for European Preparedness Against (Re-)emerging Epidemics, NIHR Health Protection Research Unit (HPRU) in Emerging and Zoonotic Infections at University of Liverpool, NIHR HPRU in Respiratory Infections at Imperial College London.
    MeSH term(s) Aged ; Aged, 80 and over ; COVID-19/diagnosis ; COVID-19/mortality ; COVID-19/therapy ; Clinical Decision Rules ; Clinical Decision-Making/methods ; Clinical Deterioration ; Critical Care/statistics & numerical data ; Female ; Hospital Mortality ; Humans ; Intensive Care Units/statistics & numerical data ; Logistic Models ; Male ; Middle Aged ; Patient Admission/statistics & numerical data ; Prognosis ; Prospective Studies ; Reproducibility of Results ; Respiration, Artificial/statistics & numerical data ; SARS-CoV-2/isolation & purification ; Severity of Illness Index ; United Kingdom/epidemiology
    Language English
    Publishing date 2021-01-11
    Publishing country England
    Document type Journal Article ; Multicenter Study ; Research Support, Non-U.S. Gov't ; Validation Study
    ZDB-ID 2686754-0
    ISSN 2213-2619 ; 2213-2600
    ISSN (online) 2213-2619
    ISSN 2213-2600
    DOI 10.1016/S2213-2600(20)30559-2
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  3. Article ; Online: Risk stratification of patients admitted to hospital with covid-19 using the ISARIC WHO Clinical Characterisation Protocol: development and validation of the 4C Mortality Score.

    Knight, Stephen R / Ho, Antonia / Pius, Riinu / Buchan, Iain / Carson, Gail / Drake, Thomas M / Dunning, Jake / Fairfield, Cameron J / Gamble, Carrol / Green, Christopher A / Gupta, Rishi / Halpin, Sophie / Hardwick, Hayley E / Holden, Karl A / Horby, Peter W / Jackson, Clare / Mclean, Kenneth A / Merson, Laura / Nguyen-Van-Tam, Jonathan S /
    Norman, Lisa / Noursadeghi, Mahdad / Olliaro, Piero L / Pritchard, Mark G / Russell, Clark D / Shaw, Catherine A / Sheikh, Aziz / Solomon, Tom / Sudlow, Cathie / Swann, Olivia V / Turtle, Lance Cw / Openshaw, Peter Jm / Baillie, J Kenneth / Semple, Malcolm G / Docherty, Annemarie B / Harrison, Ewen M

    BMJ (Clinical research ed.)

    2020  Volume 370, Page(s) m3339

    Abstract: Objective: To develop and validate a pragmatic risk score to predict mortality in patients admitted to hospital with coronavirus disease 2019 (covid-19).: Design: Prospective observational cohort study.: Setting: International Severe Acute ... ...

    Abstract Objective: To develop and validate a pragmatic risk score to predict mortality in patients admitted to hospital with coronavirus disease 2019 (covid-19).
    Design: Prospective observational cohort study.
    Setting: International Severe Acute Respiratory and emerging Infections Consortium (ISARIC) World Health Organization (WHO) Clinical Characterisation Protocol UK (CCP-UK) study (performed by the ISARIC Coronavirus Clinical Characterisation Consortium-ISARIC-4C) in 260 hospitals across England, Scotland, and Wales. Model training was performed on a cohort of patients recruited between 6 February and 20 May 2020, with validation conducted on a second cohort of patients recruited after model development between 21 May and 29 June 2020
    Main outcome measure: In-hospital mortality.
    Results: 35 463 patients were included in the derivation dataset (mortality rate 32.2%) and 22 361 in the validation dataset (mortality rate 30.1%). The final 4C Mortality Score included eight variables readily available at initial hospital assessment: age, sex, number of comorbidities, respiratory rate, peripheral oxygen saturation, level of consciousness, urea level, and C reactive protein (score range 0-21 points). The 4C Score showed high discrimination for mortality (derivation cohort: area under the receiver operating characteristic curve 0.79, 95% confidence interval 0.78 to 0.79; validation cohort: 0.77, 0.76 to 0.77) with excellent calibration (validation: calibration-in-the-large=0, slope=1.0). Patients with a score of at least 15 (n=4158, 19%) had a 62% mortality (positive predictive value 62%) compared with 1% mortality for those with a score of 3 or less (n=1650, 7%; negative predictive value 99%). Discriminatory performance was higher than 15 pre-existing risk stratification scores (area under the receiver operating characteristic curve range 0.61-0.76), with scores developed in other covid-19 cohorts often performing poorly (range 0.63-0.73).
    Conclusions: An easy-to-use risk stratification score has been developed and validated based on commonly available parameters at hospital presentation. The 4C Mortality Score outperformed existing scores, showed utility to directly inform clinical decision making, and can be used to stratify patients admitted to hospital with covid-19 into different management groups. The score should be further validated to determine its applicability in other populations.
    Study registration: ISRCTN66726260.
    MeSH term(s) Aged ; Aged, 80 and over ; Betacoronavirus ; COVID-19 ; Clinical Protocols ; Cohort Studies ; Coronavirus Infections/diagnosis ; Coronavirus Infections/mortality ; Female ; Hospital Mortality ; Hospitalization ; Humans ; Male ; Middle Aged ; Pandemics ; Pneumonia, Viral/diagnosis ; Pneumonia, Viral/mortality ; Predictive Value of Tests ; ROC Curve ; Risk Assessment ; SARS-CoV-2 ; Survival Rate ; United Kingdom
    Keywords covid19
    Language English
    Publishing date 2020-09-09
    Publishing country England
    Document type Journal Article ; Observational Study ; Research Support, Non-U.S. Gov't
    ZDB-ID 1362901-3
    ISSN 1756-1833 ; 0959-8154 ; 0959-8146 ; 0959-8138 ; 0959-535X ; 1759-2151
    ISSN (online) 1756-1833
    ISSN 0959-8154 ; 0959-8146 ; 0959-8138 ; 0959-535X ; 1759-2151
    DOI 10.1136/bmj.m3339
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  4. Book ; Online: Risk stratification of patients admitted to hospital with covid-19 using the ISARIC WHO Clinical Characterisation Protocol

    Knight, Stephen R / Ho, Antonia / Pius, Riinu / Buchan, Iain / Carson, Gail / Drake, Thomas M / Dunning, Jake / Fairfield, Cameron J / Gamble, Carrol / Green, Christopher A / Gupta, Rishi / Halpin, Sophie / Hardwick, Hayley E / Holden, Karl A / Horby, Peter W / Jackson, Clare / Mclean, Kenneth A / Merson, Laura / Nguyen-Van-Tam, Jonathan S /
    Norman, Lisa / Noursadeghi, Mahdad / Olliaro, Piero L / Pritchard, Mark G / Russell, Clark D / Shaw, Catherine A / Sheikh, Aziz / Solomon, Tom / Sudlow, Cathie / Swann, Olivia V / Turtle, Lance CW / Openshaw, Peter JM / Baillie, J Kenneth / Semple, Malcolm G / Docherty, Annemarie B / Harrison, Ewen M / on behalf of the ISARIC4C investigators

    development and validation of the 4C Mortality Score

    2020  

    Abstract: ... Objective ... To develop and validate a pragmatic risk score to predict mortality in patients admitted to hospital with coronavirus disease 2019 (covid-19). ... ... Design ... Prospective observational cohort study. ... ... ...

    Abstract <sec><st>Objective</st> To develop and validate a pragmatic risk score to predict mortality in patients admitted to hospital with coronavirus disease 2019 (covid-19). </sec> <sec><st>Design</st> Prospective observational cohort study. </sec> <sec><st>Setting</st> International Severe Acute Respiratory and emerging Infections Consortium (ISARIC) World Health Organization (WHO) Clinical Characterisation Protocol UK (CCP-UK) study (performed by the ISARIC Coronavirus Clinical Characterisation Consortium—ISARIC-4C) in 260 hospitals across England, Scotland, and Wales. Model training was performed on a cohort of patients recruited between 6 February and 20 May 2020, with validation conducted on a second cohort of patients recruited after model development between 21 May and 29 June 2020 . </sec> <sec><st>Participants</st> Adults (age ≥18 years) admitted to hospital with covid-19 at least four weeks before final data extraction. </sec> <sec><st>Main outcome measure</st> In-hospital mortality. </sec> <sec><st>Results</st> 35 463 patients were included in the derivation dataset (mortality rate 32.2%) and 22 361 in the validation dataset (mortality rate 30.1%). The final 4C Mortality Score included eight variables readily available at initial hospital assessment: age, sex, number of comorbidities, respiratory rate, peripheral oxygen saturation, level of consciousness, urea level, and C reactive protein (score range 0-21 points). The 4C Score showed high discrimination for mortality (derivation cohort: area under the receiver operating characteristic curve 0.79, 95% confidence interval 0.78 to 0.79; validation cohort: 0.77, 0.76 to 0.77) with excellent calibration (validation: calibration-in-the-large=0, slope=1.0). Patients with a score of at least 15 (n=4158, 19%) had a 62% mortality (positive predictive value 62%) compared with 1% mortality for those with a score of 3 or less (n=1650, 7%; negative predictive value 99%). Discriminatory performance was higher than 15 pre-existing risk stratification scores (area under the receiver operating characteristic curve range 0.61-0.76), with scores developed in other covid-19 cohorts often performing poorly (range 0.63-0.73). </sec> <sec><st>Conclusions</st> An easy-to-use risk stratification score has been developed and validated based on commonly available parameters at hospital presentation. The 4C Mortality Score outperformed existing scores, showed utility to directly inform clinical decision making, and can be used to stratify patients admitted to hospital with covid-19 into different management groups. The score should be further validated to determine its applicability in other populations. </sec> <sec><st>Study registration</st> ISRCTN66726260 </sec>
    Keywords RESEARCH ; covid19
    Language English
    Publishing date 2020-09-09 15:30:35.0
    Publisher BMJ Publishing Group Ltd
    Publishing country us
    Document type Book ; Online
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  5. Article ; Online: Ethnicity and Outcomes from COVID-19

    Harrison, Ewen M. / Docherty, Annemarie B. / Barr, Benjamin / Buchan, Iain / Carson, Gail / Drake, Tom M. / Dunning, Jake / Fairfield, Cameron J. / Gamble, Carrol / Green, Christopher A. / Griffiths, Chris / Halpin, Sophie / Hardwick, Hayley E. / Ho, Antonia / Holden, Karl A. / Hollinghurst, Joe / Horby, Peter W. / Jackson, Clare / Katikireddi, Srinivasa Vittal /
    Knight, Stephen / Lyons, Ronan / MacMahon, James / Mclean, Kenneth A. / Merson, Laura / Murphy, Derek / Nguyen-Van-Tam, Jonathan S. / Norman, Lisa / Olliaro, Piero L. / Pareek, Manish / Piroddi, Roberta / Pius, Riinu / Read, Jonathan M. / Russell, Clark D. / Sattar, Naveed / Shaw, Catherine A. / Sheikh, Aziz / Sinha, Ian P. / Swann, Olivia / Taylor-Robinson, David / Thomas, Daniel / Turtle, Lance / Openshaw, Peter JM / Baillie, J. Kenneth / Semple, Malcolm G.

    SSRN Electronic Journal ; ISSN 1556-5068

    The ISARIC CCP-UK Prospective Observational Cohort Study of Hospitalised Patients

    2020  

    Keywords covid19
    Language English
    Publisher Elsevier BV
    Publishing country us
    Document type Article ; Online
    DOI 10.2139/ssrn.3618215
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  6. Article ; Online: Ethnicity and outcomes from COVID-19

    Harrison, Ewen M. / Docherty, Annemarie B. / Barr, Benjamin / Buchan, Iain / Carson, Gail / Drake, Tom M. / Dunning, Jake / Fairfield, Cameron J. / Gamble, Carrol / Green, Christopher A. / Griffiths, Chris / Halpin, Sophie / Hardwick, Hayley E. / Ho, Antonia / Holden, Karl A. / Hollinghurst, Joe / Horby, Peter W. / Jackson, Clare / Katikireddi, Srinivasa Vittal /
    Knight, Stephen / Lyons, Ronan / MacMahon, James / Mclean, Kenneth A. / Merson, Laura / Murphy, Derek / Nguyen-Van-Tam, Jonathan S. / Norman, Lisa / Olliaro, Piero L. / Pareek, Manish / Piroddi, Roberta / Pius, Riinu / Read, Jonathan M. / Russell, Clark D. / Sattar, Naveed / Shaw, Catherine A. / Sheikh, Aziz / Sinha, Ian P. / Swann, Olivia / Taylor-Robinson, David / Thomas, Daniel / Turtle, Lance / Openshaw, Peter JM / Baillie, J. Kenneth / Semple, Malcolm G. / Scott, Janet T.

    the ISARIC CCP-UK prospective observational cohort study of hospitalised patients

    2020  

    Abstract: Background: Reports of ethnic inequalities in COVID-19 outcomes are conflicting and the reasons for any differences in outcomes are unclear. We investigated ethnic inequalities in critical care admission patterns, the need for invasive mechanical ... ...

    Abstract Background: Reports of ethnic inequalities in COVID-19 outcomes are conflicting and the reasons for any differences in outcomes are unclear. We investigated ethnic inequalities in critical care admission patterns, the need for invasive mechanical ventilation (IMV), and in-hospital mortality, among hospitalised patients with COVID-19. Methods: We undertook a prospective cohort study in which dedicated research staff recruited hospitalised patients with suspected/confirmed COVID-19 from 260 hospitals across England, Scotland and Wales, collecting data directly and from records between 6th February and 8th May 2020 with follow-up until 22nd May 2020. Analysis used hierarchical regression models accounting for confounding, competing risks, and clustering of patients in hospitals. Potential mediators for death were explored with a three-way decomposition mediation analysis. Findings: Of 34,986 patients enrolled, 30,693 (88%) had ethnicity recorded: South Asian (1,388, 5%), East Asian (266, 1%), Black (1,094, 4%), Other Ethnic Minority (2,398, 8%) (collectively Ethnic Minorities), and White groups (25,547, 83%). Ethnic Minorities were younger and more likely to have diabetes (type 1/type 2) but had fewer other comorbidities such as chronic heart disease or dementia than the White group. No difference was seen between ethnic groups in the time from symptom onset to hospital admission, nor in illness severity at admission. Critical care admission was more common in South Asian (odds ratio 1.28, 95% confidence interval 1.09 to 1.52), Black (1.36, 1.14 to 1.62), and Other Ethnic Minority (1.29, 1.13 to 1.47) groups compared to the White group, after adjusting for age, sex and location. This was broadly unchanged after adjustment for deprivation and comorbidities. Patterns were similar for IMV. Higher adjusted mortality was seen in the South Asian (hazard ratio 1.19, 1.05 to 1.36), but not East Asian (1.00, 0.74 to 1.35), Black (1.05, 0.91 to 1.26) or Other Ethnic Minority (0.99, 0.89 to 1.10) groups, compared to the White group. 18% (95% CI, 9% to 56%) of the excess mortality in South Asians was mediated by pre-existing diabetes. Interpretation: Ethnic Minorities in hospital with COVID-19 were more likely to be admitted to critical care and receive IMV than Whites, despite similar disease severity on admission, similar duration of symptoms, and being younger with fewer comorbidities. South Asians are at greater risk of dying, due at least in part to a higher prevalence of pre-existing diabetes. Trial Registration: The study was registered at https://www.isrctn.com/ISRCTN66726260. Funding Statement: This work is supported by grants from: the National Institute for Health Research [award CO-CIN-01], 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], and Liverpool Experimental Cancer Medicine Centre for providing infrastructure support for this research (Grant Reference: C18616/A25153). JSN-V-T is seconded to the Department of Health and Social Care, England (DHSC).
    Keywords covid19
    Language English
    Publishing date 2020-06-17
    Publishing country uk
    Document type Article ; Online
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  7. Article ; Online: Risk stratification of patients admitted to hospital with covid-19 using the ISARIC WHO Clinical Characterisation Protocol

    Knight, Stephen R. / Ho, Antonia / Pius, Riinu / Buchan, Iain / Carson, Gail / Drake, Thomas M. / Dunning, Jake / Fairfield, Cameron J. / Gamble, Carrol / Green, Christopher A. / Gupta, Rishi / Halpin, Sophie / Hardwick, Hayley E. / Holden, Karl A. / Horby, Peter W. / Jackson, Clare / Mclean, Kenneth A. / Merson, Laura / Nguyen-Van-Tam, Jonathan S. /
    Norman, Lisa / Noursadeghi, Mahdad / Olliaro, Piero L. / Pritchard, Mark G. / Russell, Clark D. / Shaw, Catherine A. / Sheikh, Aziz / Solomon, Tom / Sudlow, Cathie / Swann, Olivia V. / Turtle, Lance C.W. / Openshaw, Peter J.M. / Baillie, J. Kenneth / Semple, Malcolm G. / Docherty, Annemarie B. / Harrison, Ewen M.

    development and validation of the 4C Mortality Score

    2020  

    Abstract: OBJECTIVE:To develop and validate a pragmatic risk score to predict mortality in patients admitted to hospital with coronavirus disease 2019 (covid-19). DESIGN:Prospective observational cohort study. SETTING:International Severe Acute Respiratory and ... ...

    Abstract OBJECTIVE:To develop and validate a pragmatic risk score to predict mortality in patients admitted to hospital with coronavirus disease 2019 (covid-19). DESIGN:Prospective observational cohort study. SETTING:International Severe Acute Respiratory and emerging Infections Consortium (ISARIC) World Health Organization (WHO) Clinical Characterisation Protocol UK (CCP-UK) study (performed by the ISARIC Coronavirus Clinical Characterisation Consortium-ISARIC-4C) in 260 hospitals across England, Scotland, and Wales. Model training was performed on a cohort of patients recruited between 6 February and 20 May 2020, with validation conducted on a second cohort of patients recruited after model development between 21 May and 29 June 2020. PARTICIPANTS: Adults (age ≥18 years) admitted to hospital with covid-19 at least four weeks before final data extraction. MAIN OUTCOME MEASURE:In-hospital mortality. RESULTS:35 463 patients were included in the derivation dataset (mortality rate 32.2%) and 22 361 in the validation dataset (mortality rate 30.1%). The final 4C Mortality Score included eight variables readily available at initial hospital assessment: age, sex, number of comorbidities, respiratory rate, peripheral oxygen saturation, level of consciousness, urea level, and C reactive protein (score range 0-21 points). The 4C Score showed high discrimination for mortality (derivation cohort: area under the receiver operating characteristic curve 0.79, 95% confidence interval 0.78 to 0.79; validation cohort: 0.77, 0.76 to 0.77) with excellent calibration (validation: calibration-in-the-large=0, slope=1.0). Patients with a score of at least 15 (n=4158, 19%) had a 62% mortality (positive predictive value 62%) compared with 1% mortality for those with a score of 3 or less (n=1650, 7%; negative predictive value 99%). Discriminatory performance was higher than 15 pre-existing risk stratification scores (area under the receiver operating characteristic curve range 0.61-0.76), with scores developed in other covid-19 cohorts often performing poorly (range 0.63-0.73). CONCLUSIONS:An easy-to-use risk stratification score has been developed and validated based on commonly available parameters at hospital presentation. The 4C Mortality Score outperformed existing scores, showed utility to directly inform clinical decision making, and can be used to stratify patients admitted to hospital with covid-19 into different management groups. The score should be further validated to determine its applicability in other populations. STUDY REGISTRATION:ISRCTN66726260.
    Keywords covid19
    Language English
    Publishing date 2020-09-09
    Publisher BMJ Publishing Group
    Publishing country uk
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  8. Article ; Online: Risk stratification of patients admitted to hospital with covid-19 using the ISARIC WHO Clinical Characterisation Protocol

    Knight, Stephen R / Ho, Antonia / Pius, Riinu / Buchan, Iain / Carson, Gail / Drake, Thomas M / Dunning, Jake / Fairfield, Cameron J / Gamble, Carrol / Green, Christopher A / Gupta, Rishi / Halpin, Sophie / Hardwick, Hayley E / Holden, Karl A / Horby, Peter W / Jackson, Clare / Mclean, Kenneth A / Merson, Laura / Nguyen-Van-Tam, Jonathan S /
    Norman, Lisa / Noursadeghi, Mahdad / Olliaro, Piero L / Pritchard, Mark G / Russell, Clark D / Shaw, Catherine A / Sheikh, Aziz / Solomon, Tom / Sudlow, Cathie / Swann, Olivia V / Turtle, Lance CW / Openshaw, Peter JM / Baillie, J Kenneth / Semple, Malcolm G / Docherty, Annemarie B / Harrison, Ewen M

    BMJ

    development and validation of the 4C Mortality Score

    2020  , Page(s) m3339

    Abstract: Abstract Objective To develop and validate a pragmatic risk score to predict mortality in patients admitted to hospital with coronavirus disease 2019 (covid-19). Design Prospective observational cohort study. Setting International Severe Acute ... ...

    Abstract Abstract Objective To develop and validate a pragmatic risk score to predict mortality in patients admitted to hospital with coronavirus disease 2019 (covid-19). Design Prospective observational cohort study. Setting International Severe Acute Respiratory and emerging Infections Consortium (ISARIC) World Health Organization (WHO) Clinical Characterisation Protocol UK (CCP-UK) study (performed by the ISARIC Coronavirus Clinical Characterisation Consortium—ISARIC-4C) in 260 hospitals across England, Scotland, and Wales. Model training was performed on a cohort of patients recruited between 6 February and 20 May 2020, with validation conducted on a second cohort of patients recruited after model development between 21 May and 29 June 2020 . Participants Adults (age ≥18 years) admitted to hospital with covid-19 at least four weeks before final data extraction. Main outcome measure In-hospital mortality. Results 35 463 patients were included in the derivation dataset (mortality rate 32.2%) and 22 361 in the validation dataset (mortality rate 30.1%). The final 4C Mortality Score included eight variables readily available at initial hospital assessment: age, sex, number of comorbidities, respiratory rate, peripheral oxygen saturation, level of consciousness, urea level, and C reactive protein (score range 0-21 points). The 4C Score showed high discrimination for mortality (derivation cohort: area under the receiver operating characteristic curve 0.79, 95% confidence interval 0.78 to 0.79; validation cohort: 0.77, 0.76 to 0.77) with excellent calibration (validation: calibration-in-the-large=0, slope=1.0). Patients with a score of at least 15 (n=4158, 19%) had a 62% mortality (positive predictive value 62%) compared with 1% mortality for those with a score of 3 or less (n=1650, 7%; negative predictive value 99%). Discriminatory performance was higher than 15 pre-existing risk stratification scores (area under the receiver operating characteristic curve range 0.61-0.76), with scores developed in other covid-19 cohorts often performing poorly (range 0.63-0.73). Conclusions An easy-to-use risk stratification score has been developed and validated based on commonly available parameters at hospital presentation. The 4C Mortality Score outperformed existing scores, showed utility to directly inform clinical decision making, and can be used to stratify patients admitted to hospital with covid-19 into different management groups. The score should be further validated to determine its applicability in other populations. Study registration ISRCTN66726260
    Keywords covid19
    Language English
    Publisher BMJ
    Publishing country uk
    Document type Article ; Online
    ZDB-ID 1362901-3
    ISSN 1756-1833 ; 0959-8154 ; 0959-8146 ; 0959-8138 ; 0959-535X ; 1759-2151
    ISSN (online) 1756-1833
    ISSN 0959-8154 ; 0959-8146 ; 0959-8138 ; 0959-535X ; 1759-2151
    DOI 10.1136/bmj.m3339
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  9. Article ; Online: SARS-CoV-2 Omicron-B.1.1.529 leads to widespread escape from neutralizing antibody responses

    Dejnirattisai, Wanwisa / Huo, Jiandong / Zhou, Daming / Zahradník, Jiří / Supasa, Piyada / Liu, Chang / Duyvesteyn, Helen M.E. / Ginn, Helen M. / Mentzer, Alexander J. / Tuekprakhon, Aekkachai / Nutalai, Rungtiwa / Wang, Beibei / Dijokaite, Aiste / Khan, Suman / Avinoam, Ori / Bahar, Mohammad / Skelly, Donal / Adele, Sandra / Johnson, Sile Ann /
    Amini, Ali / Ritter, Thomas G. / Mason, Chris / Dold, Christina / Pan, Daniel / Assadi, Sara / Bellass, Adam / Omo-Dare, Nicola / Koeckerling, David / Flaxman, Amy / Jenkin, Daniel / Aley, Parvinder K. / Voysey, Merryn / Clemens, Sue Ann Costa / Naveca, Felipe Gomes / Nascimento, Valdinete / Nascimento, Fernanda / Fernandes da Costa, Cristiano / Resende, Paola Cristina / Pauvolid-Correa, Alex / Siqueira, Marilda M. / Baillie, Vicky / Serafin, Natali / Kwatra, Gaurav / Da Silva, Kelly / Madhi, Shabir A. / Nunes, Marta C. / Malik, Tariq / Openshaw, Peter J.M. / Baillie, J. Kenneth / Semple, Malcolm G. / Townsend, Alain R. / Huang, Kuan-Ying A. / Tan, Tiong Kit / Carroll, Miles W. / Klenerman, Paul / Barnes, Eleanor / Dunachie, Susanna J. / Constantinides, Bede / Webster, Hermione / Crook, Derrick / Pollard, Andrew J. / Lambe, Teresa / Paterson, Neil G. / Williams, Mark A. / Hall, David R. / Fry, Elizabeth E. / Mongkolsapaya, Juthathip / Ren, Jingshan / Schreiber, Gideon / Stuart, David I. / Screaton, Gavin R. / Conlon, Christopher / Deeks, Alexandra S. / Frater, John / Frending, Lisa / Gardiner, Siobhan / Jämsén, Anni / Jeffery, Katie / Malone, Tom / Phillips, Eloise / Rothwell, Lucy / Stafford, Lizzie / Baillie, J Kenneth / Openshaw, Peter JM. / Carson, Gail / Alex, Beatrice / Andrikopoulos, Petros / Bach, Benjamin / Barclay, Wendy S. / Bogaert, Debby / Chand, Meera / Chechi, Kanta / Cooke, Graham S. / da Silva Filipe, Ana / de Silva, Thushan / Docherty, Annemarie B. / dos Santos Correia, Gonçalo / Dumas, Marc-Emmanuel / Dunning, Jake / Fletcher, Tom / Green, Christoper A. / Greenhalf, William / Griffin, Julian L. / Gupta, Rishi K. / Harrison, Ewen M. / Hiscox, Julian A. / Wai Ho, Antonia Ying / Horby, Peter W. / Ijaz, Samreen / Khoo, Saye / Law, Andrew / Lewis, Matthew R. / Liggi, Sonia / Lim, Wei Shen / Maslen, Lynn / Merson, Laura / Meynert, Alison M. / Moore, Shona C. / Noursadeghi, Mahdad / Olanipekun, Michael / Osagie, Anthonia / Palmarini, Massimo / Palmieri, Carlo / Paxton, William A. / Pollakis, Georgios / Price, Nicholas / Rambaut, Andrew / Robertson, Dave / Russell, Clark D. / Sancho-Shimizu, Vanessa / Sands, Caroline J. / Scott, Janet T. / Sigfrid, Louise / Solomon, Tom / Sriskandan, Shiranee / Stuart, David / Summers, Charlotte / Swann, Olivia V. / Takats, Zoltan / Takis, Panteleimon / Tedder, Richard S. / Thompson, AA Roger / Thomson, Emma C. / Thwaites, Ryan S. / Turtle, Lance CW. / Zambon, Maria / Hardwick, Hayley / Donohue, Chloe / Griffiths, Fiona / Oosthuyzen, Wilna / Donegan, Cara / Spencer, Rebecca G. / Norman, Lisa / Pius, Riinu / Drake, Thomas M. / Fairfield, Cameron J. / Knight, Stephen R. / Mclean, Kenneth A. / Murphy, Derek / Shaw, Catherine A. / Dalton, Jo / Girvan, Michelle / Saviciute, Egle / Roberts, Stephanie / Harrison, Janet / Marsh, Laura / Connor, Marie / Halpin, Sophie / Jackson, Clare / Gamble, C. / Plotkin, Daniel / Lee, James / Leeming, Gary / Wham, Murray / Clohisey, Sara / Hendry, Ross / Scott-Brown, Jas / Shaw, Victoria / McDonald, Sarah E. / Keating, Seán / Ahmed, Katie A. / Armstrong, Jane A. / Ashworth, Milton / Asiimwe, Innocent G. / Bakshi, Siddharth / Barlow, Samantha L. / Booth, Laura / Brennan, Benjamin / Bullock, Katie / Catterall, Benjamin WA. / Clark, Jordan J. / Clarke, Emily A. / Cole, Sarah / Cooper, Louise / Cox, Helen / Davis, Christopher / Dincarslan, Oslem / Dunn, Chris / Dyer, Philip / Elliott, Angela / Evans, Anthony / Finch, Lorna / Fisher, Lewis WS. / Foster, Terry / Garcia-Dorival, Isabel / Gunning, Philip / Hartley, Catherine / Jensen, Rebecca L. / Jones, Christopher B. / Jones, Trevor R. / Khandaker, Shadia / King So, Katharine / Kiy, Robyn T. / Koukorava, Chrysa / Lake, Annette / Lant, Suzannah / Latawiec, Diane / Lavelle-Langham, Lara / Lefteri, Daniella / Lett, Lauren / Livoti, Lucia A. / Mancini, Maria / McDonald, Sarah / McEvoy, Laurence / McLauchlan, John / Metelmann, Soeren / Miah, Nahida S. / Middleton, Joanna / Mitchell, Joyce / Murphy, Ellen G. / Penrice-Randal, Rebekah / Pilgrim, Jack / Prince, Tessa / Reynolds, Will / Ridley, P. Matthew / Sales, Debby / Shaw, Victoria E. / Shears, Rebecca K. / Small, Benjamin / Subramaniam, Krishanthi S. / Szemiel, Agnieska / Taggart, Aislynn / Tanianis-Hughes, Jolanta / Thomas, Jordan / Trochu, Erwan / van Tonder, Libby / Wilcock, Eve / Zhang, J. Eunice / Flaherty, Lisa / Maziere, Nicole / Cass, Emily / Carracedo, Alejandra Doce / Carlucci, Nicola / Holmes, Anthony / Massey, Hannah / Murphy, Lee / McCafferty, Sarah / Clark, Richard / Fawkes, Angie / Morrice, Kirstie / Maclean, Alan / Wrobel, Nicola / Donnelly, Lorna / Coutts, Audrey / Hafezi, Katarzyna / MacGillivray, Louise / Gilchrist, Tammy / Adeniji, Kayode / Agranoff, Daniel / Agwuh, Ken / Ail, Dhiraj / Aldera, Erin L. / Alegria, Ana / Allen, Sam / Angus, Brian / Ashish, Abdul / Atkinson, Dougal / Bari, Shahedal / Barlow, Gavin / Barnass, Stella / Barrett, Nicholas / Bassford, Christopher / Basude, Sneha / Baxter, David / Beadsworth, Michael / Bernatoniene, Jolanta / Berridge, John / Berry, Colin / Best, Nicola / Bothma, Pieter / Chadwick, David / Brittain-Long, Robin / Bulteel, Naomi / Burden, Tom / Burtenshaw, Andrew / Caruth, Vikki / Chambler, Duncan / Chee, Nigel / Child, Jenny / Chukkambotla, Srikanth / Clark, Tom / Collini, Paul / Cosgrove, Catherine / Cupitt, Jason / Cutino-Moguel, Maria-Teresa / Dark, Paul / Dawson, Chris / Dervisevic, Samir / Donnison, Phil / Douthwaite, Sam / Drummond, Andrew / DuRand, Ingrid / Dushianthan, Ahilanadan / Dyer, Tristan / Evans, Cariad / Eziefula, Chi / Fegan, Chrisopher / Finn, Adam / Fullerton, Duncan / Garg, Sanjeev / Garg, Atul / Gkrania-Klotsas, Effrossyni / Godden, Jo / Goldsmith, Arthur / Graham, Clive / Hardy, Elaine / Hartshorn, Stuart / Harvey, Daniel / Havalda, Peter / Hawcutt, Daniel B. / Hobrok, Maria / Hodgson, Luke / Hormis, Anil / Jacobs, Michael / Jain, Susan / Jennings, Paul / Kaliappan, Agilan / Kasipandian, Vidya / Kegg, Stephen / Kelsey, Michael / Kendall, Jason / Kerrison, Caroline / Kerslake, Ian / Koch, Oliver / Koduri, Gouri / Kōśi, Jōrjj / Laha, Shondipon / Laird, Steven / Larkin, Susan / Leiner, Tamas / Lillie, Patrick / Limb, James / Linnett, Vanessa / Little, Jeff / Lyttle, Mark / MacMahon, Michael / MacNaughton, Emily / Mankregod, Ravish / Masson, Huw / Matovu, Elijah / McCullough, Katherine / McEwen, Ruth / Meda, Manjula / Mills, Gary / Minton, Jane / Mirfenderesky, Mariyam / Mohandas, Kavya / Mok, Quen / Moon, James / Moore, Elinoor / Morgan, Patrick / Morris, Craig / Mortimore, Katherine / Moses, S. / Mpenge, Mbiye / Mulla, Rohinton / Murphy, Michael / Nagel, Megan / Nagarajan, Thapas / Nelson, Mark / Norris, Lillian / O’Shea, Matthew K. / Otahal, Igor / Ostermann, Marlies / Pais, Mark / Panchatsharam, Selva / Papakonstantinou, Danai / Paraiso, Hassan / Patel, Brij / Pattison, Natalie / Pepperell, Justin / Peters, Mark / Phull, Mandeep / Pintus, Stefania / Pooni, Jagtur Singh / Planche, Tim / Post, Frank / Price, David / Prout, Rachel / Rae, Nikolas / Reschreiter, Henrik / Reynolds, Tim / Richardson, Neil / Roberts, Mark / Roberts, Devender / Rose, Alistair / Rousseau, Guy / Ruge, Bobby / Ryan, Brendan / Saluja, Taranprit / Schmid, Matthias L. / Shah, Aarti / Shanmuga, Prad / Sharma, Anil / Shawcross, Anna / Sizer, Jeremy / Shankar-Hari, Manu / Smith, Richard / Snelson, Catherine / Spittle, Nick / Staines, Nikki / Stambach, Tom / Stewart, Richard / Subudhi, Pradeep / Szakmany, Tamas / Tatham, Kate / Thomas, Jo / Thompson, Chris / Thompson, Robert / Tridente, Ascanio / Tupper-Carey, Darell / Twagira, Mary / Vallotton, Nick / Vancheeswaran, Rama / Vincent-Smith, Lisa / Visuvanathan, Shico / Vuylsteke, Alan / Waddy, Sam / Wake, Rachel / Walden, Andrew / Welters, Ingeborg / Whitehouse, Tony / Whittaker, Paul / Whittington, Ashley / Papineni, Padmasayee / Wijesinghe, Meme / Williams, Martin / Wilson, Lawrence / Winchester, Stephen / Wiselka, Martin / Wolverson, Adam / Wootton, Daniel G. / Workman, Andrew / Yates, Bryan / Young, Peter

    Cell. 2022 Feb. 03, v. 185, no. 3 p.467-484.e15

    2022  

    Abstract: On 24ᵗʰ November 2021, the sequence of a new SARS-CoV-2 viral isolate Omicron-B.1.1.529 was announced, containing far more mutations in Spike (S) than previously reported variants. Neutralization titers of Omicron by sera from vaccinees and convalescent ... ...

    Institution OPTIC Consortium
    ISARIC4C Consortium
    Abstract On 24ᵗʰ November 2021, the sequence of a new SARS-CoV-2 viral isolate Omicron-B.1.1.529 was announced, containing far more mutations in Spike (S) than previously reported variants. Neutralization titers of Omicron by sera from vaccinees and convalescent subjects infected with early pandemic Alpha, Beta, Gamma, or Delta are substantially reduced, or the sera failed to neutralize. Titers against Omicron are boosted by third vaccine doses and are high in both vaccinated individuals and those infected by Delta. Mutations in Omicron knock out or substantially reduce neutralization by most of the large panel of potent monoclonal antibodies and antibodies under commercial development. Omicron S has structural changes from earlier viruses and uses mutations that confer tight binding to ACE2 to unleash evolution driven by immune escape. This leads to a large number of mutations in the ACE2 binding site and rebalances receptor affinity to that of earlier pandemic viruses.
    Keywords Severe acute respiratory syndrome coronavirus 2 ; evolution ; neutralization ; pandemic ; vaccines ; SARS-CoV-2 ; Omicron ; variants ; immune evasion ; receptor interaction ; Spike ; RBD
    Language English
    Dates of publication 2022-0203
    Size p. 467-484.e15.
    Publishing place Elsevier Inc.
    Document type Article ; Online
    ZDB-ID 187009-9
    ISSN 1097-4172 ; 0092-8674
    ISSN (online) 1097-4172
    ISSN 0092-8674
    DOI 10.1016/j.cell.2021.12.046
    Database NAL-Catalogue (AGRICOLA)

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