37
views
0
recommends
+1 Recommend
3 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      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

      research-article
      1 , 2 , 3 , 1 , 4 , 5 , 1 , 6 , 7 , 1 , 8 , 9 , 10 , 8 , 11 , 11 , 5 , 8 , 1 , 5 , 12 , 1 , 13 , 14 , 14 , 15 , 1 , 1 , 11 , 16 , 17 , 18 , 11 , 19 , 7 , 20 , 21 , 11 , 22 , , 1 , 21 , 1 , 23 , on behalf of the ISARIC4C investigators
      BMJ (Clinical research ed.)

      Read this article at

      ScienceOpenPublisherPMC
      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          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

          Related collections

          Most cited references52

          • Record: found
          • Abstract: found
          • Article: not found

          Clinical course and outcomes of critically ill patients with SARS-CoV-2 pneumonia in Wuhan, China: a single-centered, retrospective, observational study

          Summary Background An ongoing outbreak of pneumonia associated with the severe acute respiratory coronavirus 2 (SARS-CoV-2) started in December, 2019, in Wuhan, China. Information about critically ill patients with SARS-CoV-2 infection is scarce. We aimed to describe the clinical course and outcomes of critically ill patients with SARS-CoV-2 pneumonia. Methods In this single-centered, retrospective, observational study, we enrolled 52 critically ill adult patients with SARS-CoV-2 pneumonia who were admitted to the intensive care unit (ICU) of Wuhan Jin Yin-tan hospital (Wuhan, China) between late December, 2019, and Jan 26, 2020. Demographic data, symptoms, laboratory values, comorbidities, treatments, and clinical outcomes were all collected. Data were compared between survivors and non-survivors. The primary outcome was 28-day mortality, as of Feb 9, 2020. Secondary outcomes included incidence of SARS-CoV-2-related acute respiratory distress syndrome (ARDS) and the proportion of patients requiring mechanical ventilation. Findings Of 710 patients with SARS-CoV-2 pneumonia, 52 critically ill adult patients were included. The mean age of the 52 patients was 59·7 (SD 13·3) years, 35 (67%) were men, 21 (40%) had chronic illness, 51 (98%) had fever. 32 (61·5%) patients had died at 28 days, and the median duration from admission to the intensive care unit (ICU) to death was 7 (IQR 3–11) days for non-survivors. Compared with survivors, non-survivors were older (64·6 years [11·2] vs 51·9 years [12·9]), more likely to develop ARDS (26 [81%] patients vs 9 [45%] patients), and more likely to receive mechanical ventilation (30 [94%] patients vs 7 [35%] patients), either invasively or non-invasively. Most patients had organ function damage, including 35 (67%) with ARDS, 15 (29%) with acute kidney injury, 12 (23%) with cardiac injury, 15 (29%) with liver dysfunction, and one (2%) with pneumothorax. 37 (71%) patients required mechanical ventilation. Hospital-acquired infection occurred in seven (13·5%) patients. Interpretation The mortality of critically ill patients with SARS-CoV-2 pneumonia is considerable. The survival time of the non-survivors is likely to be within 1–2 weeks after ICU admission. Older patients (>65 years) with comorbidities and ARDS are at increased risk of death. The severity of SARS-CoV-2 pneumonia poses great strain on critical care resources in hospitals, especially if they are not adequately staffed or resourced. Funding None.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: found

            The Third International Consensus Definitions for Sepsis and Septic Shock (Sepsis-3).

            Definitions of sepsis and septic shock were last revised in 2001. Considerable advances have since been made into the pathobiology (changes in organ function, morphology, cell biology, biochemistry, immunology, and circulation), management, and epidemiology of sepsis, suggesting the need for reexamination.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              A new method of classifying prognostic comorbidity in longitudinal studies: Development and validation

              The objective of this study was to develop a prospectively applicable method for classifying comorbid conditions which might alter the risk of mortality for use in longitudinal studies. A weighted index that takes into account the number and the seriousness of comorbid disease was developed in a cohort of 559 medical patients. The 1-yr mortality rates for the different scores were: "0", 12% (181); "1-2", 26% (225); "3-4", 52% (71); and "greater than or equal to 5", 85% (82). The index was tested for its ability to predict risk of death from comorbid disease in the second cohort of 685 patients during a 10-yr follow-up. The percent of patients who died of comorbid disease for the different scores were: "0", 8% (588); "1", 25% (54); "2", 48% (25); "greater than or equal to 3", 59% (18). With each increased level of the comorbidity index, there were stepwise increases in the cumulative mortality attributable to comorbid disease (log rank chi 2 = 165; p less than 0.0001). In this longer follow-up, age was also a predictor of mortality (p less than 0.001). The new index performed similarly to a previous system devised by Kaplan and Feinstein. The method of classifying comorbidity provides a simple, readily applicable and valid method of estimating risk of death from comorbid disease for use in longitudinal studies. Further work in larger populations is still required to refine the approach because the number of patients with any given condition in this study was relatively small.
                Bookmark

                Author and article information

                Journal
                8900488
                BMJ
                BMJ
                BMJ (Clinical research ed.)
                0959-8138
                1756-1833
                19 November 2020
                09 September 2020
                09 September 2020
                11 December 2020
                : 370
                : m3339
                Affiliations
                [1 ]Centre for Medical Informatics, The Usher Institute, University of Edinburgh, Edinburgh, UK
                [2 ]Medical Research Council, University of Glasgow Centre for Virus Research, Glasgow, UK
                [3 ]Department of Infectious Diseases, Queen Elizabeth University Hospital, Glasgow, UK
                [4 ]Institute of Population Health Sciences, University of Liverpool, Liverpool, UK
                [5 ]ISARIC Global Support Centre, Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, UK
                [6 ]National Infection Service, Public Health England, London, UK
                [7 ]National Heart and Lung Institute, Imperial College London, London, UK
                [8 ]Liverpool Clinical Trials Centre, University of Liverpool, Liverpool, UK
                [9 ]Institute of Microbiology & Infection, University of Birmingham, Birmingham, UK
                [10 ]Institute of Global Health, University College London, London, UK
                [11 ]NIHR Health Protection Research Unit, Institute of Infection, Veterinary and Ecological Sciences, Faculty of Health and Life Sciences, University of Liverpool, Liverpool, UK
                [12 ]Division of Epidemiology and Public Health, University of Nottingham School of Medicine, Nottingham, UK
                [13 ]Division of Infection and Immunity, University College London, London, UK
                [14 ]Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, UK
                [15 ]Queen’s Medical Research Institute, University of Edinburgh, Edinburgh, UK
                [16 ]Walton Centre NHS Foundation Trust, Liverpool, UK
                [17 ]Health Data Research UK, London, UK
                [18 ]Department of Child Life and Health, University of Edinburgh, Edinburgh, UK
                [19 ]Tropical & Infectious Disease Unit, Royal Liverpool University Hospital, Liverpool, UK
                [20 ]Roslin Institute, University of Edinburgh, Edinburgh, UK
                [21 ]Intensive Care Unit, Royal Infirmary Edinburgh, Edinburgh, UK
                [22 ]Respiratory Medicine, Alder Hey Children’s Hospital, Institute in The Park, University of Liverpool, Alder Hey Children’s Hospital, Liverpool L12 2AP, UK
                [23 ]Department of Clinical Surgery, University of Edinburgh, Edinburgh, UK
                Author notes
                [* ]Correspondence to: M G Semple m.g.semple@ 123456liverpool.ac.uk (or @ProfCalumSemple on Twitter)
                Article
                EMS104583
                10.1136/bmj.m3339
                7116472
                32907855
                45bda07c-1b6c-4f6e-9432-94af2f545d4f

                This is an Open Access article distributed in accordance with the terms of the Creative Commons Attribution (CC BY 4.0) license, which permits others to distribute, remix, adapt and build upon this work, for commercial use, provided the original work is properly cited. See: http://creativecommons.org/licenses/by/4.0/.

                Categories
                Article

                Medicine
                Medicine

                Comments

                Comment on this article