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Risk prediction of covid-19 related death and hospital admission in adults after covid-19 vaccination: national prospective cohort study

Julia Hippisley-Cox, Carol AC Coupland, Nisha Mehta, Ruth H Keogh, Karla Diaz-Ordaz, Kamlesh Khunti, Ronan Lyons Orcid Logo, Frank Kee, Aziz Sheikh, Shamim Rahman, Jonathan Valabhji, Ewen M Harrison, Peter Sellen, Nazmus Haq, Malcolm G Semple, Peter W M Johnson, Andrew Hayward, Jonathan S Nguyen-Van-Tam

BMJ, Volume: 374, Start page: n2244

Swansea University Author: Ronan Lyons Orcid Logo

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DOI (Published version): 10.1136/bmj.n2244

Abstract

Objectives To derive and validate risk prediction algorithms to estimate the risk of covid-19 related mortality and hospital admission in UK adults after one or two doses of covid-19 vaccination.Design Prospective, population based cohort study using the QResearch database linked to data on covid-19...

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Published in: BMJ
ISSN: 0959-8138 1756-1833
Published: BMJ 2021
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Secondary outcome was covid-19 related hospital admission. Outcomes were assessed from 14 days after each vaccination dose. Models were fitted in the derivation cohort to derive risk equations using a range of predictor variables. Performance was evaluated in a separate validation cohort of general practices.Results Of 6&#x2009;952&#x2009;440 vaccinated patients in the derivation cohort, 5&#x2009;150&#x2009;310 (74.1%) had two vaccine doses. Of 2031 covid-19 deaths and 1929 covid-19 hospital admissions, 81 deaths (4.0%) and 71 admissions (3.7%) occurred 14 days or more after the second vaccine dose. The risk algorithms included age, sex, ethnic origin, deprivation, body mass index, a range of comorbidities, and SARS-CoV-2 infection rate. Incidence of covid-19 mortality increased with age and deprivation, male sex, and Indian and Pakistani ethnic origin. Cause specific hazard ratios were highest for patients with Down&#x2019;s syndrome (12.7-fold increase), kidney transplantation (8.1-fold), sickle cell disease (7.7-fold), care home residency (4.1-fold), chemotherapy (4.3-fold), HIV/AIDS (3.3-fold), liver cirrhosis (3.0-fold), neurological conditions (2.6-fold), recent bone marrow transplantation or a solid organ transplantation ever (2.5-fold), dementia (2.2-fold), and Parkinson&#x2019;s disease (2.2-fold). Other conditions with increased risk (ranging from 1.2-fold to 2.0-fold increases) included chronic kidney disease, blood cancer, epilepsy, chronic obstructive pulmonary disease, coronary heart disease, stroke, atrial fibrillation, heart failure, thromboembolism, peripheral vascular disease, and type 2 diabetes. A similar pattern of associations was seen for covid-19 related hospital admissions. No evidence indicated that associations differed after the second dose, although absolute risks were reduced. The risk algorithm explained 74.1% (95% confidence interval 71.1% to 77.0%) of the variation in time to covid-19 death in the validation cohort. Discrimination was high, with a D statistic of 3.46 (95% confidence interval 3.19 to 3.73) and C statistic of 92.5. Performance was similar after each vaccine dose. In the top 5% of patients with the highest predicted covid-19 mortality risk, sensitivity for identifying covid-19 deaths within 70 days was 78.7%.Conclusion This population based risk algorithm performed well showing high levels of discrimination for identifying those patients at highest risk of covid-19 related death and hospital admission after vaccination.</abstract><type>Journal Article</type><journal>BMJ</journal><volume>374</volume><journalNumber/><paginationStart>n2244</paginationStart><paginationEnd/><publisher>BMJ</publisher><placeOfPublication/><isbnPrint/><isbnElectronic/><issnPrint>0959-8138</issnPrint><issnElectronic>1756-1833</issnElectronic><keywords>Humans, Vaccination, Hospitalization, Risk Assessment, Prospective Studies, Comorbidity, Databases, Factual, Adult, Aged, Aged, 80 and over, Middle Aged, Female, Male, United Kingdom, COVID-19, SARS-CoV-2, COVID-19 Vaccines</keywords><publishedDay>17</publishedDay><publishedMonth>9</publishedMonth><publishedYear>2021</publishedYear><publishedDate>2021-09-17</publishedDate><doi>10.1136/bmj.n2244</doi><url/><notes>This article has a correction. 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spelling 2022-08-17T12:51:59.1486362 v2 58431 2021-10-20 Risk prediction of covid-19 related death and hospital admission in adults after covid-19 vaccination: national prospective cohort study 83efcf2a9dfcf8b55586999d3d152ac6 0000-0001-5225-000X Ronan Lyons Ronan Lyons true false 2021-10-20 HDAT Objectives To derive and validate risk prediction algorithms to estimate the risk of covid-19 related mortality and hospital admission in UK adults after one or two doses of covid-19 vaccination.Design Prospective, population based cohort study using the QResearch database linked to data on covid-19 vaccination, SARS-CoV-2 results, hospital admissions, systemic anticancer treatment, radiotherapy, and the national death and cancer registries.Settings Adults aged 19-100 years with one or two doses of covid-19 vaccination between 8 December 2020 and 15 June 2021.Main outcome measures Primary outcome was covid-19 related death. Secondary outcome was covid-19 related hospital admission. Outcomes were assessed from 14 days after each vaccination dose. Models were fitted in the derivation cohort to derive risk equations using a range of predictor variables. Performance was evaluated in a separate validation cohort of general practices.Results Of 6 952 440 vaccinated patients in the derivation cohort, 5 150 310 (74.1%) had two vaccine doses. Of 2031 covid-19 deaths and 1929 covid-19 hospital admissions, 81 deaths (4.0%) and 71 admissions (3.7%) occurred 14 days or more after the second vaccine dose. The risk algorithms included age, sex, ethnic origin, deprivation, body mass index, a range of comorbidities, and SARS-CoV-2 infection rate. Incidence of covid-19 mortality increased with age and deprivation, male sex, and Indian and Pakistani ethnic origin. Cause specific hazard ratios were highest for patients with Down’s syndrome (12.7-fold increase), kidney transplantation (8.1-fold), sickle cell disease (7.7-fold), care home residency (4.1-fold), chemotherapy (4.3-fold), HIV/AIDS (3.3-fold), liver cirrhosis (3.0-fold), neurological conditions (2.6-fold), recent bone marrow transplantation or a solid organ transplantation ever (2.5-fold), dementia (2.2-fold), and Parkinson’s disease (2.2-fold). Other conditions with increased risk (ranging from 1.2-fold to 2.0-fold increases) included chronic kidney disease, blood cancer, epilepsy, chronic obstructive pulmonary disease, coronary heart disease, stroke, atrial fibrillation, heart failure, thromboembolism, peripheral vascular disease, and type 2 diabetes. A similar pattern of associations was seen for covid-19 related hospital admissions. No evidence indicated that associations differed after the second dose, although absolute risks were reduced. The risk algorithm explained 74.1% (95% confidence interval 71.1% to 77.0%) of the variation in time to covid-19 death in the validation cohort. Discrimination was high, with a D statistic of 3.46 (95% confidence interval 3.19 to 3.73) and C statistic of 92.5. Performance was similar after each vaccine dose. In the top 5% of patients with the highest predicted covid-19 mortality risk, sensitivity for identifying covid-19 deaths within 70 days was 78.7%.Conclusion This population based risk algorithm performed well showing high levels of discrimination for identifying those patients at highest risk of covid-19 related death and hospital admission after vaccination. Journal Article BMJ 374 n2244 BMJ 0959-8138 1756-1833 Humans, Vaccination, Hospitalization, Risk Assessment, Prospective Studies, Comorbidity, Databases, Factual, Adult, Aged, Aged, 80 and over, Middle Aged, Female, Male, United Kingdom, COVID-19, SARS-CoV-2, COVID-19 Vaccines 17 9 2021 2021-09-17 10.1136/bmj.n2244 This article has a correction. Please see: https://doi.org/10.1136/bmj.n2300 COLLEGE NANME Health Data Science COLLEGE CODE HDAT Swansea University National Institute for Health Research (NIHR); RHK was supported by a UKRI Future Leaders Fellowship (MR/S017968/1); KD-O was supported by a grant from the Alan Turing Institute Health Programme (EP/T001569/1) 2022-08-17T12:51:59.1486362 2021-10-20T12:30:09.4432076 Faculty of Medicine, Health and Life Sciences Swansea University Medical School - Medicine Julia Hippisley-Cox 1 Carol AC Coupland 2 Nisha Mehta 3 Ruth H Keogh 4 Karla Diaz-Ordaz 5 Kamlesh Khunti 6 Ronan Lyons 0000-0001-5225-000X 7 Frank Kee 8 Aziz Sheikh 9 Shamim Rahman 10 Jonathan Valabhji 11 Ewen M Harrison 12 Peter Sellen 13 Nazmus Haq 14 Malcolm G Semple 15 Peter W M Johnson 16 Andrew Hayward 17 Jonathan S Nguyen-Van-Tam 18 58431__21236__458e0d529d6b4d90ad327a437971c1b2.pdf 58431.pdf 2021-10-20T12:35:39.9470610 Output 680731 application/pdf Version of Record true This is an Open Access article distributed in accordance with the terms of the Creative Commons Attribution (CC BY 4.0) license true eng http://creativecommons.org/licenses/by/4.0/
title Risk prediction of covid-19 related death and hospital admission in adults after covid-19 vaccination: national prospective cohort study
spellingShingle Risk prediction of covid-19 related death and hospital admission in adults after covid-19 vaccination: national prospective cohort study
Ronan Lyons
title_short Risk prediction of covid-19 related death and hospital admission in adults after covid-19 vaccination: national prospective cohort study
title_full Risk prediction of covid-19 related death and hospital admission in adults after covid-19 vaccination: national prospective cohort study
title_fullStr Risk prediction of covid-19 related death and hospital admission in adults after covid-19 vaccination: national prospective cohort study
title_full_unstemmed Risk prediction of covid-19 related death and hospital admission in adults after covid-19 vaccination: national prospective cohort study
title_sort Risk prediction of covid-19 related death and hospital admission in adults after covid-19 vaccination: national prospective cohort study
author_id_str_mv 83efcf2a9dfcf8b55586999d3d152ac6
author_id_fullname_str_mv 83efcf2a9dfcf8b55586999d3d152ac6_***_Ronan Lyons
author Ronan Lyons
author2 Julia Hippisley-Cox
Carol AC Coupland
Nisha Mehta
Ruth H Keogh
Karla Diaz-Ordaz
Kamlesh Khunti
Ronan Lyons
Frank Kee
Aziz Sheikh
Shamim Rahman
Jonathan Valabhji
Ewen M Harrison
Peter Sellen
Nazmus Haq
Malcolm G Semple
Peter W M Johnson
Andrew Hayward
Jonathan S Nguyen-Van-Tam
format Journal article
container_title BMJ
container_volume 374
container_start_page n2244
publishDate 2021
institution Swansea University
issn 0959-8138
1756-1833
doi_str_mv 10.1136/bmj.n2244
publisher BMJ
college_str Faculty of Medicine, Health and Life Sciences
hierarchytype
hierarchy_top_id facultyofmedicinehealthandlifesciences
hierarchy_top_title Faculty of Medicine, Health and Life Sciences
hierarchy_parent_id facultyofmedicinehealthandlifesciences
hierarchy_parent_title Faculty of Medicine, Health and Life Sciences
department_str Swansea University Medical School - Medicine{{{_:::_}}}Faculty of Medicine, Health and Life Sciences{{{_:::_}}}Swansea University Medical School - Medicine
document_store_str 1
active_str 0
description Objectives To derive and validate risk prediction algorithms to estimate the risk of covid-19 related mortality and hospital admission in UK adults after one or two doses of covid-19 vaccination.Design Prospective, population based cohort study using the QResearch database linked to data on covid-19 vaccination, SARS-CoV-2 results, hospital admissions, systemic anticancer treatment, radiotherapy, and the national death and cancer registries.Settings Adults aged 19-100 years with one or two doses of covid-19 vaccination between 8 December 2020 and 15 June 2021.Main outcome measures Primary outcome was covid-19 related death. Secondary outcome was covid-19 related hospital admission. Outcomes were assessed from 14 days after each vaccination dose. Models were fitted in the derivation cohort to derive risk equations using a range of predictor variables. Performance was evaluated in a separate validation cohort of general practices.Results Of 6 952 440 vaccinated patients in the derivation cohort, 5 150 310 (74.1%) had two vaccine doses. Of 2031 covid-19 deaths and 1929 covid-19 hospital admissions, 81 deaths (4.0%) and 71 admissions (3.7%) occurred 14 days or more after the second vaccine dose. The risk algorithms included age, sex, ethnic origin, deprivation, body mass index, a range of comorbidities, and SARS-CoV-2 infection rate. Incidence of covid-19 mortality increased with age and deprivation, male sex, and Indian and Pakistani ethnic origin. Cause specific hazard ratios were highest for patients with Down’s syndrome (12.7-fold increase), kidney transplantation (8.1-fold), sickle cell disease (7.7-fold), care home residency (4.1-fold), chemotherapy (4.3-fold), HIV/AIDS (3.3-fold), liver cirrhosis (3.0-fold), neurological conditions (2.6-fold), recent bone marrow transplantation or a solid organ transplantation ever (2.5-fold), dementia (2.2-fold), and Parkinson’s disease (2.2-fold). Other conditions with increased risk (ranging from 1.2-fold to 2.0-fold increases) included chronic kidney disease, blood cancer, epilepsy, chronic obstructive pulmonary disease, coronary heart disease, stroke, atrial fibrillation, heart failure, thromboembolism, peripheral vascular disease, and type 2 diabetes. A similar pattern of associations was seen for covid-19 related hospital admissions. No evidence indicated that associations differed after the second dose, although absolute risks were reduced. The risk algorithm explained 74.1% (95% confidence interval 71.1% to 77.0%) of the variation in time to covid-19 death in the validation cohort. Discrimination was high, with a D statistic of 3.46 (95% confidence interval 3.19 to 3.73) and C statistic of 92.5. Performance was similar after each vaccine dose. In the top 5% of patients with the highest predicted covid-19 mortality risk, sensitivity for identifying covid-19 deaths within 70 days was 78.7%.Conclusion This population based risk algorithm performed well showing high levels of discrimination for identifying those patients at highest risk of covid-19 related death and hospital admission after vaccination.
published_date 2021-09-17T04:14:57Z
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