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.
Stephen R Knight,Antonia Ho,Riinu Pius,Iain Buchan,Gail Carson,Thomas M Drake,Jake Dunning,Jake Dunning,Cameron J Fairfield,Carrol Gamble,Christopher A Green,Rishi K Gupta,Sophie Halpin,Hayley E Hardwick,Karl A Holden,Peter Horby,Clare Jackson,Kenneth A. McLean,Laura Merson,Jonathan S. Nguyen-Van-Tam,Lisa Norman,Mahdad Noursadeghi,Piero Olliaro,Mark G Pritchard,Clark D Russell,Catherine A Shaw,Aziz Sheikh,Tom Solomon,Tom Solomon,Cathie Sudlow,Olivia Swann,Lance Turtle,Lance Turtle,Peter J. M. Openshaw,J Kenneth Baillie,Malcolm G Semple,Annemarie B Docherty,Ewen M Harrison +37 more
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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.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.read more
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Prediction models for diagnosis and prognosis of covid-19: systematic review and critical appraisal
Laure Wynants,Laure Wynants,Ben Van Calster,Ben Van Calster,Gary S. Collins,Gary S. Collins,Richard D Riley,Georg Heinze,Ewoud Schuit,Marc J.M. Bonten,Darren Dahly,Johanna A A G Damen,Thomas P. A. Debray,Valentijn M.T. de Jong,Maarten De Vos,Paula Dhiman,Paula Dhiman,Maria C Haller,Michael O. Harhay,Liesbet Henckaerts,Pauline Heus,Michael Kammer,Nina Kreuzberger,Anna Lohmann,Kim Luijken,Jie Ma,Glen P. Martin,David J. McLernon,Constanza L Andaur Navarro,Johannes B. Reitsma,Jamie C. Sergeant,Chunhu Shi,Nicole Skoetz,Luc J.M. Smits,Kym I E Snell,Matthew Sperrin,René Spijker,René Spijker,Ewout W. Steyerberg,Toshihiko Takada,Ioanna Tzoulaki,Ioanna Tzoulaki,Sander M. J. van Kuijk,Bas C T van Bussel,Bas C T van Bussel,Iwan C. C. van der Horst,Florien S. van Royen,Jan Y Verbakel,Jan Y Verbakel,Christine Wallisch,Christine Wallisch,Jack Wilkinson,Robert Wolff,Lotty Hooft,Karel G.M. Moons,Maarten van Smeden +55 more
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TL;DR: In this paper, a systematic review was conducted using standardized methodology, searching two electronic databases (PubMed and SCOPUS) for relevant literature published between 1st January 2020 and 9th July 2020.
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Population risk factors for severe disease and mortality in COVID-19: A global systematic review and meta-analysis
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Louise Sigfrid,Thomas M Drake,Ellen Pauley,Edwin C. Jesudason,Piero Olliaro,Wei Shen Lim,Annelies Gillesen,Colin Berry,David J Lowe,Joanne McPeake,Nazir I Lone,Daniel Munblit,Daniel Munblit,Muge Cevik,Anna Casey,Peter Bannister,Clark D Russell,Lynsey Goodwin,Lynsey Goodwin,Antonia Ho,Lance Turtle,Margaret E O’Hara,Claire Hastie,Chloe Donohue,Rebecca G Spencer,Cara Donegan,Alison Gummery,Janet Harrison,Hayley E Hardwick,Claire E. Hastie,Gail Carson,Laura Merson,J Kenneth Baillie,Peter J. M. Openshaw,Ewen M Harrison,Annemarie B Docherty,Malcolm G Semple,Malcolm G Semple,Janet T Scott +38 more
TL;DR: In this article, the authors sought to establish the long-term effects of Covid-19 following hospitalisation, including new symptoms, disability, breathlessness, and quality of life (EQ5D-5L).
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