Knight, Stephen, Ho, Antonia 
ORCID: 0000-0003-1465-3785, Pius, Riinu, Buchan, Iain ORCID: 0000-0003-3392-1650, Carson, Gail ORCID: 0000-0001-8439-9933, Drake, Thomas, Dunning, Jake, Fairfield, Cameron ORCID: 0000-0001-7635-1868, Gamble, Carrol ORCID: 0000-0002-3021-1955, Green, Christopher et al (show 25 more authors)
(2020)
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.
MedRxiv.
2020.07.30.20165464-.
Abstract
<h4>Objectives</h4> To develop and validate a pragmatic risk score to predict mortality for patients admitted to hospital with covid-19. <h4>Design</h4> Prospective observational cohort study: ISARIC WHO CCP-UK study (ISARIC Coronavirus Clinical Characterisation Consortium [4C]). 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 between 21 May and 29 June 2020. <h4>Setting</h4> 260 hospitals across England, Scotland, and Wales. <h4>Participants</h4> Adult patients (≥18 years) admitted to hospital with covid-19 admitted at least four weeks before final data extraction. <h4>Main outcome measures</h4> In-hospital mortality. <h4>Results</h4> There were 34 692 patients included in the derivation dataset (mortality rate 31.7%) and 22 454 in the validation dataset (mortality 31.5%). 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, and C-reactive protein (score range 0-21 points). The 4C risk stratification score demonstrated high discrimination for mortality (derivation cohort: AUROC 0.79; 95% CI 0.78 − 0.79; validation cohort 0.78, 0.77-0.79) with excellent calibration (slope = 1.0). Patients with a score ≥15 (n = 2310, 17.4%) had a 67% mortality (i.e., positive predictive value 67%) compared with 1.0% mortality for those with a score ≤3 (n = 918, 7%; negative predictive value 99%). Discriminatory performance was higher than 15 pre-existing risk stratification scores (AUROC range 0.60-0.76), with scores developed in other covid-19 cohorts often performing poorly (range 0.63-0.73). <h4>Conclusions</h4> We have developed and validated an easy-to-use risk stratification score based on commonly available parameters at hospital presentation. This outperformed existing scores, demonstrated utility to directly inform clinical decision making, and can be used to stratify inpatients with covid-19 into different management groups. The 4C Mortality Score may help clinicians identify patients with covid-19 at high risk of dying during current and subsequent waves of the pandemic. <h4>Study registration</h4> ISRCTN66726260
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | Clinical Research, Patient Safety, 4.2 Evaluation of markers and technologies, 4 Detection, screening and diagnosis, 3 Good Health and Well Being |
| Depositing User: | Symplectic Admin |
| Date Deposited: | 27 Aug 2020 10:43 |
| Last Modified: | 14 Mar 2024 20:33 |
| DOI: | 10.1101/2020.07.30.20165464 |
| Open Access URL: | https://www.medrxiv.org/content/10.1101/2020.07.30... |
| Related URLs: | |
| URI: | https://livrepository.liverpool.ac.uk/id/eprint/3098836 |
Dimensions
Dimensions
