scispace - formally typeset
Open AccessJournal ArticleDOI

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.

Reads0
Chats0
TLDR
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

Content maybe subject to copyright    Report

Citations
More filters
Journal ArticleDOI

Prediction models for diagnosis and prognosis of covid-19: systematic review and critical appraisal

TL;DR: Proposed models for covid-19 are poorly reported, at high risk of bias, and their reported performance is probably optimistic, according to a review of published and preprint reports.
Journal ArticleDOI

Population risk factors for severe disease and mortality in COVID-19: A global systematic review and meta-analysis.

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.
Posted ContentDOI

Population risk factors for severe disease and mortality in COVID-19: A global systematic review and meta-analysis

TL;DR: A range of easily assessed parameters are valuable to predict elevated risk of severe illness and mortality as a result of COVID-19, including patient characteristics and detailed comorbidities, alongside the novel inclusion of real-time symptoms and vital measurements.
References
More filters
Journal ArticleDOI

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

TL;DR: The method of classifying comorbidity provides a simple, readily applicable and valid method of estimating risk of death fromComorbid disease for use in longitudinal studies and further work in larger populations is still required to refine the approach.
Journal ArticleDOI

APACHE II: a severity of disease classification system.

TL;DR: The form and validation results of APACHE II, a severity of disease classification system that uses a point score based upon initial values of 12 routine physiologic measurements, age, and previous health status, are presented.
Journal ArticleDOI

The SOFA (Sepsis-related Organ Failure Assessment) score to describe organ dysfunction/failure. On behalf of the Working Group on Sepsis-Related Problems of the European Society of Intensive Care Medicine.

TL;DR: The ESICM developed a so-called sepsis-related organ failure assessment (SOFA) score to describe quantitatively and as objectively as possible the degree of organ dysfunction/failure over time in groups of patients or even in individual patients.
Related Papers (5)