Session Type: 1-hour Oral Session
Session Title: 1-hour Oral Session
Authors(s): T. Crocker-Buque (1), S. Williams (2), A.R. Brentnall (3), R. Gabe (3), S. Tiberi (1)
Authors Affiliations(s): (1) The Royal London Hospital, Barts Health NHS Trust, United Kingdom, (2) Barts Health NHS Trust, United Kingdom, (3) Wolfson Institute of Preventive Medicine, Queen Mary University of London, United Kingdom
Third Party Affiliation: On behalf of the Barts Health and Queen Mary COVID-19 Trials Group
Background:
Barts Health National Health Service Trust (BHNHST) serves a diverse population of 2.5 million people in London, UK. We undertook a health services evaluation of factors used to evaluate risk of severe acute respiratory coronavirus 2 (SARS-CoV-2) infection using predictive clinical risk models, including the International Severe Acute Respiratory and Emerging Infection Consortium (ISARIC) 4C models.
Methods:Patients with confirmed polymerase chain reaction (PCR) tests admitted between 1st March and 1st August 2020 were included alongside clinician-diagnosed suspected cases. Prognostic factors from the UK national ISARIC 4C mortality and deterioration scores were extracted from electronic health records and logistic regression was used to quantify the strength of association with 28-day mortality and clinical deterioration using national death registry linkage.
Results:1,621 of 2,783 patients had a confirmed diagnosis, with the remainder being clinical suspected cases. Of confirmed cases 61% were male and 54% were from Black and Minority Ethnic groups. 26% died within 28-days of admission. Mortality was strongly associated with older age. The 4C mortality score had good stratification of risk with a calibration slope of 1.14 (95% confidence interval 1.01-1.27). It may have under-estimated mortality risk in those with a high respiratory rate or requiring oxygen, but no additional factors conferring mortality risk were identified.
Conclusions:Patients in this diverse patient cohort had similar mortality associated with prognostic factors to the 4C score derivation sample, but survival might be poorer in those with respiratory failure.
Keyword(s): COVID-19, Risk prediction, MortalitySession Type: 1-hour Oral Session
Session Title: 1-hour Oral Session
Authors(s): T. Crocker-Buque (1), S. Williams (2), A.R. Brentnall (3), R. Gabe (3), S. Tiberi (1)
Authors Affiliations(s): (1) The Royal London Hospital, Barts Health NHS Trust, United Kingdom, (2) Barts Health NHS Trust, United Kingdom, (3) Wolfson Institute of Preventive Medicine, Queen Mary University of London, United Kingdom
Third Party Affiliation: On behalf of the Barts Health and Queen Mary COVID-19 Trials Group
Background:
Barts Health National Health Service Trust (BHNHST) serves a diverse population of 2.5 million people in London, UK. We undertook a health services evaluation of factors used to evaluate risk of severe acute respiratory coronavirus 2 (SARS-CoV-2) infection using predictive clinical risk models, including the International Severe Acute Respiratory and Emerging Infection Consortium (ISARIC) 4C models.
Methods:Patients with confirmed polymerase chain reaction (PCR) tests admitted between 1st March and 1st August 2020 were included alongside clinician-diagnosed suspected cases. Prognostic factors from the UK national ISARIC 4C mortality and deterioration scores were extracted from electronic health records and logistic regression was used to quantify the strength of association with 28-day mortality and clinical deterioration using national death registry linkage.
Results:1,621 of 2,783 patients had a confirmed diagnosis, with the remainder being clinical suspected cases. Of confirmed cases 61% were male and 54% were from Black and Minority Ethnic groups. 26% died within 28-days of admission. Mortality was strongly associated with older age. The 4C mortality score had good stratification of risk with a calibration slope of 1.14 (95% confidence interval 1.01-1.27). It may have under-estimated mortality risk in those with a high respiratory rate or requiring oxygen, but no additional factors conferring mortality risk were identified.
Conclusions:Patients in this diverse patient cohort had similar mortality associated with prognostic factors to the 4C score derivation sample, but survival might be poorer in those with respiratory failure.
Keyword(s): COVID-19, Risk prediction, Mortality