PreprintPDF Available

Place and causes of acute cardiovascular mortality during the COVID19 pandemic: retrospective cohort study of 580,972 deaths in England and Wales, 2014 to 2020

Authors:

Abstract and Figures

Importance. The COVID-19 pandemic has resulted in a decline in admissions with cardiovascular (CV) emergencies. The fatal consequences of this are unknown. Objectives - To describe the place and causes of acute CV death during the COVID-19 pandemic. Design - Retrospective nationwide cohort. Setting - England and Wales. Participants - All adult (age ≥18 years) acute CV deaths (n=580,972) between 1st January 2014 and 2nd June 2020. Exposure - The COVID-19 pandemic (defined as from the onset of the first COVID-19 death in England on 2nd March 2020). Main outcomes - Place (hospital, care home, home) and acute CV events directly contributing to death as stated on the first part of the Medical Certificate of Cause of Death. Results - After 2nd March 2020, there were 22,820 acute CV deaths of which 5.7% related to COVID-19, and an excess acute CV mortality of 1752 (+8%) compared with the expected daily deaths in the same period. Deaths in the community accounted for nearly half of all deaths during this period. Care homes had the greatest increase in excess acute CV deaths (1065, +40%), followed by deaths at home (1728, +34%) and in hospital (57, +0%). The most frequent cause of acute CV death during this period was stroke (8,290, 36.3%), followed by acute coronary syndrome (ACS) (5,532, 24.2%), heart failure (5,280, 23.1%), pulmonary embolism (2,067, 9.1%) and cardiac arrest (1,037, 4.5%). Deep vein thrombosis had the greatest increase in cause of excess acute CV death (18, +25%), followed pulmonary embolism (340, +19%) and stroke (782, +10%). The greatest cause of excess CV death in care homes was stroke (700, +48%), compared with cardiac arrest (80, +56%) at home, and pulmonary embolism (126, +14%) and cardiogenic shock (41, +14%) in hospital. Conclusions and relevance - The COVID-19 pandemic has resulted in an inflation in acute CV deaths above that expected for the time of year, nearly half of which occurred in the community. The most common cause of acute CV death was stroke followed by acute coronary syndrome and heart failure. This is key information to optimise messaging to the public and enable health resource planning.
Content may be subject to copyright.
Title: Place and causes of acute cardiovascular mortality during the COVID19
pandemic: retrospective cohort study of 580,972 deaths in England and Wales, 2014
to 2020
Authors: Jianhua Wu (Associate Professor of Biostatistics) 1,2, Mamas A Mamas
(Professor of Cardiology) 3,4, Mohamed Mohamed (Specialist Registrar in
Cardiology)3,4, Chun Shing Kwok (Specialist Registrar in Cardiology) 3,4, Chris
Roebuck (Chief Statistician NHS Digital) 5, Ben Humberstone (Head of health analysis
and life events ONS) 6, Tom Denwood (Executive Director NHS Digital) 5, Tom
Luescher (Professor of Cardiology)7, Mark A de Belder (Professor of Cardiology)8,
John E Deanfield (Professor of Cardiology) 8,9, Chris P Gale (Professor of
Cardiovascular Medicine) 1,10,11
1 Leeds Institute for Data Analytics, University of Leeds, Leeds, UK
2 Division of Clinical and Translational Research, School of Dentistry, University of
Leeds, Leeds, UK
3 Keele Cardiovascular Research Group, Centre for Prognosis Research, Institute for
Primary Care and Health Sciences, Keele University, Stoke-on-Trent, UK
4 Department of Cardiology, Royal Stoke University Hospital, Stoke-on-Trent, UK
5 NHS Digital, Leeds, UK
6 Office for National Statistics, Newport, Wales
7 Imperial College, National Heart and Lung Institute, London
8 National Institute for Cardiovascular Outcomes Research, Barts Health NHS Trust,
London
9 Institute of Cardiovascular Sciences, University College, London
10 Leeds Teaching Hospitals NHS Trust, Leeds, UK.
11 Leeds Institute for Cardiovascular and Metabolic Medicine, University of Leeds,
Leeds, UK
Correspondence: Professor Chris P Gale,
Co-Director Leeds Institute for Data Analytics
Leeds Institute of Cardiovascular and Metabolic Medicine,
Worsley Building, Level 11, Clarendon Way,
University of Leeds, Leeds, LS2 9JT, UK.
Email: c.p.gale@leeds.ac.uk
Tel: 0044 (0)113 343 8916
Twitter: @cpgale3
Word count: Excluding tables, figures, abstract, summary boxes and
references: 2481
Abstract: 347
Figures: 3 Supplementary figures: 0
Tables: 3 Supplementary tables: 0
Keywords: COVID-19; cardiovascular; excess mortality
Abstract
Importance. The COVID-19 pandemic has resulted in a decline in admissions with
cardiovascular (CV) emergencies. The fatal consequences of this are unknown.
Objectives To describe the place and causes of acute CV death during the COVID-
19 pandemic.
Design Retrospective nationwide cohort.
Setting England and Wales.
Participants All adult (age ≥18 years) acute CV deaths (n=580,972) between 1st
January 2014 and 2nd June 2020.
Exposure The COVID-19 pandemic (defined as from the onset of the first COVID-19
death in England on 2nd March 2020).
Main outcomes Place (hospital, care home, home) and acute CV events directly
contributing to death as stated on the first part of the Medical Certificate of Cause of
Death.
Results - After 2nd March 2020, there were 22,820 acute CV deaths of which 5.7%
related to COVID-19, and an excess acute CV mortality of 1752 (+8%) compared with
the expected daily deaths in the same period. Deaths in the community accounted for
nearly half of all deaths during this period. Care homes had the greatest increase in
excess acute CV deaths (1065, +40%), followed by deaths at home (1728, +34%) and
in hospital (57, +0%). The most frequent cause of acute CV death during this period
was stroke (8,290, 36.3%), followed by acute coronary syndrome (ACS) (5,532, 24.2%),
heart failure (5,280, 23.1%), pulmonary embolism (2,067, 9.1%) and cardiac arrest
(1,037, 4.5%). Deep vein thrombosis had the greatest increase in cause of excess acute
CV death (18, +25%), followed pulmonary embolism (340, +19%) and stroke (782,
+10%). The greatest cause of excess CV death in care homes was stroke (700, +48%),
compared with cardiac arrest (80, +56%) at home, and pulmonary embolism (126,
+14%) and cardiogenic shock (41, +14%) in hospital.
Conclusions and relevance The COVID-19 pandemic has resulted in an inflation in
acute CV deaths above that expected for the time of year, nearly half of which
occurred in the community. The most common cause of acute CV death was stroke
followed by acute coronary syndrome and heart failure. This is key information to
optimise messaging to the public and enable health resource planning.
Introduction
Cardiovascular disease (CVD) is one of the most prevalent underlying condition
associated with increased mortality from COVID-19 infection.1-5 Yet, we and others
have shown a substantial reduction in presentations to hospitals with acute
cardiovascular (CV) conditions including acute coronary syndrome, heart failure,
cardiac arrhythmia and stroke during the pandemic.6-9. This would be expected to
result in a much higher number of deaths, unless there has been an actual decrease in
the incidence of these acute conditions. The detailed impact on mortality from acute
CVD has, however, not been studied at national level.
We now report, with high temporal resolution, CV specific mortality during COVID-19
in England and Wales. In particular, we have evaluated the location of CV deaths (e.g.
hospitals, home or care homes), their relation to COVID-19 infection and the specific
CV fatal events that contributed directly to death. This information is vital for the
understanding of healthcare policy during the pandemic and to assist Governments
around the world reorganise healthcare services.
Methods
Data and deaths
The analytical cohort included all certified and registered deaths in England and Wales
≥18 years of age, between 1st January 2014 and 2nd June 2020 recorded in the Civil
Registration Deaths Data of the Office for National Statistics (ONS) of England and
Wales.10
Acute CV death
The primary analysis was based upon any of the ICD-10 codes corresponding to the
immediate cause of death and contributed causes registered, and the doctor who
attended the deceased during their last illness completes a medical certificate of cause
of death (MCCD) within 5 days unless there is to be a coroner’s post-mortem or an
inquest. Cardiovascular events directly leading to death (herein called acute CV
deaths) were categorised as acute coronary syndrome (ST-elevation myocardial
infarction (STEMI), non-STEMI (NSTEMI), type 2 myocardial infarction, re-infarction)
abbreviated as ACS, heart failure, cardiac arrest, ventricular tachycardia and/or
ventricular fibrillation (VT and VF), stroke (acute ischaemic stroke, acute haemorrhagic
stroke, other non-cerebral strokes, unspecified stroke), cardiogenic shock, pulmonary
embolism, deep venous thrombosis, aortic disease (aortic aneurysm rupture and
aortic dissection) and infective endocarditis (Supplement table 1). ICD-10 codes ‘U071
(confirmed) and ‘U072’ (suspected) were used to identify whether a death was related
to COVID-19 infection on any part of the MCCD.
Statistical Analyses
Baseline characteristics were described using numbers and percentages for
categorical data. Data were stratified by COVID-19 status (suspected or confirmed, not
infected), age band (<50, 50-59, 60-69, 70-79, 80+ years)), sex, place of death (home,
hospital, care home or hospice). The number of daily deaths was presented using a 7-
day simple moving average (the mean number of daily deaths for that day and the
preceding 6 days) from 1st February 2020 up to and including 2nd June 2020, adjusted
for seasonality.
The expected daily deaths from 1st February 2020 up to and including 2nd June 2020
were estimated using Farrington surveillance algorithm for daily historical data
between 2014 and 2020.11 The algorithm used overdispersed Poisson generalised
linear models with spline terms to model trends in counts of daily death, accounting
for seasonality. The number of non-COVID-19 CV deaths each day from 1st February
2020 were subtracted from the estimated expected daily deaths in the same time
period to create a zero historical baseline. Deaths above this baseline maybe
interpreted as excess mortality, which were calculated as the difference between the
observed daily deaths and the expected daily deaths. Negative values, where the
observed deaths fell below the expected deaths, were set to zero. The rate of excess
deaths was derived from dividing excess mortality by the sum of the expected deaths
between 2nd March 2020 and 2nd June 2020.
For the categories of acute CV death, the ICD-10 code on the MCCD was counted only
once per deceased. Thus, the overall rate of acute CV death represents the number of
people with a direct CV cause of death. Given that, people may have more than one
of the pre-defined CV events leading to death, analyses for each of the pre-defined CV
categories represents the number of events (not people) per category. For the
purposes of this investigation, CVD that contributed, but did not directly lead to death
were excluded from the analyses. All tests were two-sided and statistical significance
considered as P<0.05. Statistical analyses were performed in R version 4.0.0.
Results
Between 1st January 2014 and 2nd June 2020, there were 3,401,270 deaths from all-
causes among adults. The proportion of deaths increased with increasing age band
and there were 1,728,591 (50.8%) in women (Table 1). People dying from any of the
directly contributing CV categories accounted for 58,0972 (17.1%) of all deaths, of
which 6.1% had at least two of the pre-defined CV categories that directly contributed
to death. Most deaths occurred in hospital (62.6%) followed by home (23.7%) and at
care home (13.6%).
Acute CV deaths before 2nd March 2020
Of the 558,152 acute CV deaths between 1st January 2014 and 1st March 2020, 48.3%
were among women (Table 1). The most frequent place of death was hospital and
most frequent cause of death was stroke, which accounted for 199,730 (35.8%) of the
acute CV deaths. The South East of England had the greatest number of acute CV
deaths.
Acute CV deaths after 2nd March 2020
Following the first UK death from COVID-19, there were 22,820 acute CV deaths of
which 5.7% related to COVID-19 (7.8% suspected; 92.2% confirmed), and an excess
acute CV mortality of 1752 (+8%) compared with the expected historical average in
the same time period of the year. COVID-19 deaths accounted for 1,307 (74.6%) of all
excess deaths after this date (Figure 1, Table 2). Qualitatively, excess acute CV
mortality began in late March 2020 and peaked in early April 2020. Whist hospital
remained the most frequent place of acute CV death, there were proportionally fewer
deaths in hospital (53.1% vs 63.0%) and more at home (30.4% vs 23.5%) and in care
homes (16.5% vs 13.5%) (Table 1). Moreover, care homes had the greatest increase in
excess acute CV deaths (+40%), followed by deaths at home (+34%) and there was no
excess acute CV deaths in hospital (Table 2). The number of excess acute CV deaths
were higher more among men than women (1009, +9% vs. 773, +8%), and was highest
in the age category 18-49 years (138, +17%) (Table 2). The most frequent cause of
acute CV death during the COVID19 pandemic was stroke (36.3%), followed by acute
coronary syndrome (24.2%), heart failure (23.1%), pulmonary embolism (9.1%) and
cardiac arrest (4.5%) (Table 1). Moreover, deep vein thrombosis demonstrated the
greatest increase in excess acute CV death (18, +25%), followed by pulmonary
embolism (340, +19%) and stroke (782, +10%) (Figure 2, Table 2).
COVID-19 CV deaths following 2nd March 2020
Compared with deaths prior to 2nd March 2020, COVID-19 CV deaths were more likely
to occur in hospital (81.5% vs. 63.0%), much less at home (7.1% vs. 23.5%) and
remained of similar proportions to non-COVID-19 CV deaths in care homes (13.5% vs.
11.4%). The rate of COVID-19 excess CV deaths was higher in hospitals than care
homes (+8% vs. +6%), and less at home (+2%). Excess COVID-19 CV deaths occurred in
similar proportions for men and women (+7% vs. +5%), and the rate of excess COVID-
19 CV deaths was comparable across the age bands (Table 2). Pulmonary embolism
had the greatest increase in cause of excess COVID-19 CV death (223, +13%), followed
by stroke (501, +7%) and cardiac arrest (83, +7%) (Figure 2, Table 2).
Place and cause of death after 2nd March 2020
The greatest inflation in excess CV death in care homes was for stroke (700, +48%),
followed by acute coronary syndrome (116, +42%), and compared with cardiac arrest
(80, +56%) and stroke (349, +47%) at home, and pulmonary embolism (126, +14%) and
cardiogenic shock (41, +14%) in hospital (Figure 3, Table 3). For stroke, ACS, heart
failure and cardiac arrest, the numbers of deaths in hospital were lower than the
historical baseline (Figure 3).
Discussion
We show for the first time, in a nationwide complete analysis of all adult deaths, the
extent, site and underlying causes of the increased acute CV mortality during the
COVID-19 pandemic compared with previous years. This shows that the pandemic has
resulted in an inflation in acute CV deaths above that expected for the time of year,
nearly half of which occurred outside of the hospital setting, either at home or in care
homes, and with care homes experiencing the greatest increase in excess acute CV
deaths. The most common cause of acute CV death during the COVID19 pandemic was
stroke followed by acute coronary syndrome and heart failure. This is key information
to optimise messaging to the public, as well as for allocation of health resources and
planning.
Numerous international studies have reported the decline in hospital presentations
for a range of CV emergencies.6-9 To the best of our knowledge, this is the first study
to show that this is associated with an adverse overall CV impact. Whilst stroke and
acute coronary syndrome accounted for the vast majority of acute CV deaths, the
number of deaths in hospital due to these conditions fell below that expected for the
time of year and it increased in the community. This ‘displacement of death’, most
likely, signifies that people either did not seek help or were not referred to hospital
during the pandemic. Given the times series plots show that the excess in acute CV
mortality began in late March 2020 and peaked in early April 2020, government
directives at the time including the onset of the UK lockdown on 23rd March 2020
could have accentuated the public response.
Care homes witnessed the greatest increase in excess acute CV deaths. Here, stroke,
acute coronary syndrome, heart failure and pulmonary embolism were the
commonest cause of acute CV death. This finding highlights the susceptibility of the
elderly and co-morbid to the wider implications of COVID-19 crisis. That is, not only
were care home residents prone to the respiratory effects of COVID-19 infection, but
they will also have been exposed to the acute CV complications of COVID-19 and
decisions not to go to hospital for fear of becoming infected. This situation will have
been exacerbated by the discharge of unknowingly infected patients from hospitals to
care homes early in the course of the pandemic, a lack of systematic antibody testing
for the SARS-CoV-2 virus, the efficient person-to-person transmission of the virus and
its propensity to death in the vulnerable.1 12
The major causes of acute CV death were different between hospital and community
settings. In hospital, the greatest increase in excess acute CV deaths was for
pulmonary embolism and cardiogenic shock, followed equally by ventricular
tachycardia and ventricular fibrillation, deep vein thrombosis and infective
endocarditis. Our earlier work using data from National Health Service hospitals in
England found that during the COVID-19 pandemic, patients with acute myocardial
infarction who did present to hospital delayed seeking help. The excess in deaths from
cardiogenic shock and cardiac arrhythmias is, therefore, very likely the consequence
of delayed presentation to hospital with acute coronary syndrome.
Complications of untreated acute myocardial infarction include cardiac arrest,
arrhythmia, acute heart failure and stroke, many of which we found were recorded in
excess early on in the pandemic. In line with previous findings,13 we also identified an
increase in cardiac arrest much more so at home than in hospital. Again, this signals
the catastrophic impact of the delays to seeking help for acute CV conditions. In
hospital, there was also an inflation of deaths from infective endocarditis and aortic
dissection and rupture, indicating perhaps a more advanced (and for some,
irreversible) stage of disease presentation during the pandemic.
Notwithstanding delays to seeking help, it is possible that COVID-19 is a critical factor
in the pathophysiology of CV events. Infection with COVID-19 is associated with
unrecognised venous and arterial thromboembolic complications and a COVID19
coagulopathy that confers an increased risk of death.14-16 Our study provides evidence
for an increase in deaths above that expected for the time of year directly related to
pulmonary embolism and deep vein thrombosis. Together, these findings lend support
to the use of anticoagulation among higher risk people with COVID-19.17
Whilst previous reports have described an elevated risk of death among the elderly
and people with CV disease during the COVID-19 pandemic, none have characterised
the CV events directly leading to death or quantified the excess in acute CV mortality.1
3 18 To date, insights have been derived from small series of cases, regional or national
death records data each reporting elevated mortality rates, but none by the type
and place of cardiovascular death.1 2 19-22 The unique strengths of this investigation
include full population coverage of all adult deaths across places of death. Most
previous reports have been confined to hospitals deaths and have not captured the
full extent of the impact of the pandemic, including deaths outside of hospitals in
people who may not have been tested for the disease.
Nonetheless, our study has limitations. During the COVID19 pandemic, emergency
guidance enabled any doctor in the UK (not just the attending) to complete the MCCD,
the duration of time over which the deceased was not seen before referral to the
coroner was extended from 14 to 28 days, and causes of death could be “to the best
of their knowledge and belief” without diagnostic proof, if appropriate and to avoid
delay.23 This may have resulted in misclassification bias, with underreporting of the
deaths directly due to CV disease in preference to COVID19 infection (which is a
notifiable disease under the Health Protection (Notification) Regulations 2010) or
respiratory disease. In fact, we found that MCCDs with COVID-19 certification less
frequently contained details of acute CV events directly leading to death. Although the
MCCD allows the detailing of the sequence of events directly leading to death, we
found that after 2nd March 2020 few (5.7%) had multiple acute CV events recorded,
and therefore the categorisation of the acute CV events effectively represents per
patient events. The lower proportion of deaths with COVID-19 at home and in care
homes may represent the lack of access to community-based COVID19 testing.
Equally, because there was no systematic testing of the UK populace for the presence
the COVID-19, deaths associated with the infection may have been under estimated.24
This analysis will have excluded a small proportion of deaths under review by the
Coroner, though typically these will have been unnatural in aetiology.
Conclusion
To date, there is no whole-population, high temporal resolution information about CV-
specific mortality during the COVID19 pandemic. Through the systematic classification
of all adult deaths in England and Wales it has been possible to show that there has
been an excess in acute CV mortality during the COVID-19 pandemic, seen greatest in
care homes and which corresponds with the onset of public messaging and the
substantial decline in admissions to hospital with acute CV emergencies
Acknowledgments
We acknowledge the intellectual input of Professor Colin Baigent, University of
Oxford.
JW had full access to all of the data in the study and takes responsibility for the
accuracy of the data analysis. The Office for National Statistics provided NHS Digital
with the mortality data and takes responsibility for the integrity of these data.
Details of funding:
JW and CPG are funded by the University of Leeds. MAM is funded by the University
of Keele. The funding organizations for this study had no involvement in the design
and conduct of the study; collection, management, analysis and interpretation of the
data; preparation, review, or approval of the manuscript; or the decision to submit the
manuscript for publication.
Ethical approval
Ethical approval was not required as this study used fully anonymised routinely
collected civil registration deaths data. The data analysis was conducted through
remote access to NHS Digital Data Science Server.
Data sharing
The Secretary of State for Health and Social Care has issued a time limited Notice
under Regulation 3(4) of the NHS (Control of Patient Information Regulations) 2002
(COPI) to share confidential patient information. The study complies with the
Declaration of Helsinki.
Patient and Public Involvement statement
Patient and public were not involved because this study was to analyse routinely
collected mortality data.
Figure 1. Time series of acute CV deaths, by place of death
The number of daily CV deaths is presented using a 7-day simple moving average
(indicating the mean number of daily CV deaths for that day and the preceding 6 days)
from 1st February 2020 up to and including 2nd June 2020, adjusted for seasonality.
The number of non-COVID-19 excess CV deaths each day from 1st February 2020 were
subtracted from the expected daily death estimated using Farrington surveillance
algorithm in the same time period. The green line is a zero historical baseline. The red
line represents daily COVID-19 CV death from 2nd March to 2nd June 2020, the purple
line represents excess daily non-COVID-19 CV death from 2nd March to 2nd June 2020
and the blue line represents the total excess daily CV death from 1st February to 2nd
June 2020.
Figure 2. Time series of acute CV deaths by COVID-19, by cause of death
The number of daily CV deaths is presented using a 7-day simple moving average
(indicating the mean number of daily CV deaths for that day and the preceding 6 days)
from 1st February 2020 up to and including 2nd June 2020, adjusted for seasonality.
The number of non-COVID-19 excess CV deaths each day from 1st February 2020 were
subtracted from the expected daily death estimated using Farrington surveillance
algorithm in the same time period. The green line is a zero historical baseline. The red
line represents daily COVID-19 CV death from 2nd March to 2nd June 2020, the purple
line represents excess daily non-COVID-19 CV death from 2nd March to 2nd June 2020
and the blue line represents the total excess daily CV death from 1st February to 2nd
June 2020.
Figure 3. Time series of acute CV deaths by cause of death and place of death
The number of daily CV deaths is presented using a 7-day simple moving average
(indicating the mean number of daily CV deaths for that day and the preceding 6 days)
from 1st February 2020 up to and including 2nd June 2020, adjusted for seasonality.
The number of non-COVID-19 excess CV deaths each day from 1st February 2020 were
subtracted from the expected daily death estimated using Farrington surveillance
algorithm in the same time period. The green line is a zero historical baseline. The red
line represents excess daily death at hospital, the purple line represents excess daily
CV death at care home and hospice and the blue line represents excess daily CV death
at home.
References
1. Banerjee A, Pasea L, Harris S, et al. Estimating excess 1-year mortality
associated with the COVID-19 pandemic according to underlying
conditions and age: a population-based cohort study. Lancet 2020 doi:
10.1016/S0140-6736(20)30854-0 [published Online First: 2020/05/15]
2. Onder G, Rezza G, Brusaferro S. Case-Fatality Rate and Characteristics of
Patients Dying in Relation to COVID-19 in Italy. JAMA 2020 doi:
10.1001/jama.2020.4683 [published Online First: 2020/03/24]
3. Docherty AB, Harrison EM, Green CA, et al. Features of 20 133 UK patients in
hospital with covid-19 using the ISARIC WHO Clinical Characterisation
Protocol: prospective observational cohort study. BMJ 2020;369:m1985.
doi: 10.1136/bmj.m1985 [published Online First: 2020/05/24]
4.
https://www.ons.gov.uk/peoplepopulationandcommunity/birthsdeathsa
ndmarriages/deaths/bulletins/deathsinvolvingcovid19englandandwales
/latest#pre-existing-conditions-of-people-who-died-with-covid-19.
5.
https://www.ons.gov.uk/peoplepopulationandcommunity/birthsdeathsa
ndmarriages/deaths/articles/analysisofdeathregistrationsnotinvolvingco
ronaviruscovid19englandandwales28december2019to1may2020/techni
calannex#characteristics-of-non-covid-19-excess-deaths.
6. Solomon MD, McNulty EJ, Rana JS, et al. The Covid-19 Pandemic and the
Incidence of Acute Myocardial Infarction. N Engl J Med 2020 doi:
10.1056/NEJMc2015630 [published Online First: 2020/05/20]
7.
https://assets.publishing.service.gov.uk/government/uploads/system/u
ploads/attachment_data/file/886455/EDSSSBulletin2020wk20.pdf.
8. Kansagra AP, Goyal MS, Hamilton S, et al. Collateral Effect of Covid-19 on
Stroke Evaluation in the United States. N Engl J Med 2020 doi:
10.1056/NEJMc2014816 [published Online First: 2020/05/10]
9. Bollmann A, Hohenstein S, Meier-Hellmann A, et al. Emergency hospital
admissions and interventional treatments for heart failure and cardiac
arrhythmias in Germany during the Covid-19 outbreak Insights from the
German-wide Helios hospital network. Eur Heart J Qual Care Clin
Outcomes 2020 doi: 10.1093/ehjqcco/qcaa049 [published Online First:
2020/06/06]
10.
https://www.ons.gov.uk/peoplepopulationandcommunity/birthsdeathsa
ndmarriages/deaths/methodologies/userguidetomortalitystatisticsjuly2
017.
11. Noufaily A, Enki DG, Farrington P, et al. An improved algorithm for outbreak
detection in multiple surveillance systems. Stat Med 2013;32(7):1206-22.
doi: 10.1002/sim.5595 [published Online First: 2012/09/04]
12. Chen Y, Li L. SARS-CoV-2: virus dynamics and host response. Lancet Infect Dis
2020;20(5):515-16. doi: 10.1016/S1473-3099(20)30235-8 [published
Online First: 2020/03/28]
13. Baldi E, Sechi GM, Mare C, et al. Out-of-Hospital Cardiac Arrest during the
Covid-19 Outbreak in Italy. N Engl J Med 2020 doi:
10.1056/NEJMc2010418 [published Online First: 2020/04/30]
14. Ackermann M, Verleden SE, Kuehnel M, et al. Pulmonary Vascular
Endothelialitis, Thrombosis, and Angiogenesis in Covid-19. N Engl J Med
2020 doi: 10.1056/NEJMoa2015432 [published Online First:
2020/05/22]
15. Levi M, Thachil J, Iba T, et al. Coagulation abnormalities and thrombosis in
patients with COVID-19. Lancet Haematol 2020 doi: 10.1016/S2352-
3026(20)30145-9 [published Online First: 2020/05/15]
16. Tang N, Li D, Wang X, et al. Abnormal coagulation parameters are associated
with poor prognosis in patients with novel coronavirus pneumonia.
Journal of thrombosis and haemostasis : JTH 2020;18(4):844-47. doi:
10.1111/jth.14768 [published Online First: 2020/02/20]
17. Tang N, Bai H, Chen X, et al. Anticoagulant treatment is associated with
decreased mortality in severe coronavirus disease 2019 patients with
coagulopathy. Journal of thrombosis and haemostasis : JTH
2020;18(5):1094-99. doi: 10.1111/jth.14817 [published Online First:
2020/03/29]
18.
https://www.ons.gov.uk/peoplepopulationandcommunity/birthsdeathsa
ndmarriages/deaths/bulletins/deathsinvolvingcovid19englandandwales
/deathsoccurringinapril2020#pre-existing-conditions-of-people-who-
died-with-covid-19
19. https://www.ft.com/content/40fc8904-febf-4a66-8d1c-ea3e48bbc034.
20. Baud D, Qi X, Nielsen-Saines K, et al. Real estimates of mortality following
COVID-19 infection. Lancet Infect Dis 2020 doi: 10.1016/S1473-
3099(20)30195-X [published Online First: 2020/03/17]
21. https://www.worldometers.info/coronavirus/coronavirus-death-rate/.
22. Piccininni M, Rohmann JL, Foresti L, et al. Use of all cause mortality to
quantify the consequences of covid-19 in Nembro, Lombardy: descriptive
study. BMJ 2020;369:m1835. doi: 10.1136/bmj.m1835 [published Online
First: 2020/05/16]
23.
https://assets.publishing.service.gov.uk/government/uploads/system/u
ploads/attachment_data/file/877302/guidance-for-doctors-completing-
medical-certificates-of-cause-of-death-covid-19.pdf.
24. Raleigh VS. Tackling UK's mortality problem: covid-19 and other causes. BMJ
2020;369:m2295. doi: 10.1136/bmj.m2295 [published Online First:
2020/06/13]
Table 1. Acute CV deaths before and after 2nd March 2020, by COVID-19
status
Acute CV deaths
before 2nd March
2020
Non-COVID-19
acute CV deaths
after 2nd March
2020
COVID-19
acute CV
deaths
after 2nd
March 2020
Acute CV
deaths
after 2nd
March 2020
Total
n = 558,152
n = 21,513
n = 1,307
n = 22,820
Sex
Men
288,770 (51.7)
11,440 (53.2)
768 (58.8)
12,208 (53.5)
Women
269,382 (48.3)
10,073 (46.8)
539 (41.2)
10,612 (46.5)
Age category (years)
18-49
20,182 ( 3.6)
850 ( 4.0)
51 ( 3.9)
901 ( 3.9)
50-59
32,667 ( 5.9)
1,419 ( 6.6)
116 ( 8.9)
1,535 ( 6.7)
60-69
64,743 (11.6)
2,644 (12.3)
185 (14.2)
2,829 (12.4)
70-79
128,845 (23.1)
5,252 (24.4)
335 (25.6)
5,587 (24.5)
80+
311,715 (55.8)
11,348 (52.7)
620 (47.4)
11,968 (52.4)
Region
North East
24,113 ( 5.1)
1,074 ( 5.0)
55 ( 4.2)
1,129 ( 4.9)
North West
65,429 (13.7)
2,875 (13.4)
166 (12.7)
3,041 (13.3)
Yorkshire and The Humber
48,026 (10.1)
2,121 ( 9.9)
119 ( 9.1)
2,240 ( 9.8)
East Midlands
36,534 ( 7.7)
1,681 ( 7.8)
77 ( 5.9)
1,758 ( 7.7)
West Midlands
51,883 (10.9)
2,399 (11.2)
178 (13.6)
2,577 (11.3)
East of England
49,023 (10.3)
2,214 (10.3)
110 ( 8.4)
2,324 (10.2)
London
50,823 (10.7)
2,277 (10.6)
253 (19.4)
2,530 (11.1)
South East
71,504 (15.0)
3,226 (15.0)
204 (15.6)
3,430 (15.0)
South West
49,513 (10.4)
2,373 (11.0)
75 ( 5.7)
2,448 (10.7)
Wales
29,306 ( 6.2)
1,273 ( 5.9)
69 ( 5.3)
1,342 ( 5.9)
Place of death*
Care home and hospice
73,967 (13.5)
3,542 (16.8)
148 (11.4)
3,690 (16.5)
Home
128,370 (23.5)
6,683 (31.8)
93 ( 7.1)
6,776 (30.4)
Hospital
345,028 (63.0)
10,799 (51.4)
1,061 (81.5)
11,860 (53.1)
Underlying acute CV cause of deaths**
Stroke
199,730 (35.8)
7,789 (36.2)
501 (38.3)
8,290 (36.3)
Acute coronary syndrome
140,316 (25.1)
5,256 (24.4)
276 (21.1)
5,532 (24.2)
Heart failure
122,138 (21.9)
5,048 (23.5)
232 (17.8)
5,280 (23.1)
Pulmonary embolism
50,744 (9.1)
1,844 (8.6)
223 (17.1)
2,067 (9.1)
Cardiac arrest
29,255 (5.2)
954 (4.4)
83 (6.4)
1,037 (4.5)
Aortic diseases
28,446 (5.1)
888 (4.1)
4 (0.3)
892 (3.9)
Infective endocarditis
13,499 (2.4)
648 (3.0)
28 (2.1)
676 (3.0)
Cardiogenic shock
6,596 (1.2)
205 (1.0)
13 (1.0)
218 (1.0)
VT and VF
2,356 (0.4)
73 (0.3)
3 (0.2)
76 (0.3)
Deep vein thrombosis
480 (0.1)
74 (0.3)
2 (0.2)
76 (0.3)
CV: cardiovascular; VT: ventricular tachycardia: VF: ventricular fibrillation
*The numbers do not add up to the total deaths due to missingness (1.9%).
**Listed CV related conditions may not add up to 100 percent because some
deaths may have multiple CV related conditions.
Table 2. COVID-19 related and total excess acute CV deaths
COVID-19 related
Total*
Total
1,307 (+6%)
1,752 (+8%)
Sex
Men
768 (+7%)
1,009 (+9%)
Women
539 (+5%)
773 (+8%)
Age category (years)
18-49
51 (+7%)
138 (+17%)
50-59
116 (+8%)
186 (+13%)
60-69
185 (+7%)
376 (+15%)
70-79
335 (+7%)
577 (+11%)
80+
620 (+5%)
651 (+6%)
Region
North East
55 (+5%)
54 (+5%)
North West
166 (+5%)
138 (+4%)
Yorkshire and The Humber
119 (+5%)
131 (+6%)
East Midlands
77 (+4%)
89 (+5%)
West Midlands
178 (+8%)
267 (+11%)
East of England
110 (+5%)
119 (+5%)
London
253 (+11%)
296 (+13%)
South East
204 (+6%)
157 (+5%)
South West
75 (+3%)
153 (+7%)
Wales
69 (+5%)
40 (+3%)
Place of death**
Care home and hospice
148 (+6%)
1,065 (+40%)
Home
93 (+2%)
1,728 (+34%)
Hospital
1,061 (+8%)
57 (+0%)
Underlying acute CV cause of deaths
Stroke
501 (+7%)
782 (+10%)
Acute coronary syndrome
276 (+5%)
411 (+8%)
Heart failure
232 (+5%)
447 (+9%)
Pulmonary embolism
223 (+13%)
340 (+19%)
Cardiac arrest
83 (+7%)
23 (+2%)
Aortic diseases
4 (+0%)
8 (+1%)
Infective endocarditis
28 (+4%)
79 (+12%)
Cardiogenic shock
13 (+4%)
40 (+13%)
VT and VF
3 (+2%)
20 (+13%)
Deep vein thrombosis
2 (+3%)
18 (+25%)
CV: cardiovascular; VT: ventricular tachycardia: VF: ventricular fibrillation
*The excess death in subcategories may not add up to the total excess deaths due
to estimation and rounding error when comparing to the respective historical
average.
**The excess death in place of death do not add up to the total excess deaths due
to setting those daily deaths below the expected historical average to zeros in the
respective subgroup
18
Table 3. Excess acute CV deaths by cause and place of death
Care home and hospice
Home
Hospital
COVID-19
related
Total
COVID-19
related
Total
COVID-19
related
Total*
Stroke
82 (+6%)
700 (+48%)
16 (+2%)
349 (+47%)
398 (+7%)
16 (+0%)
Acute coronary syndrome
17 (+6%)
116 (+42%)
19 (+1%)
621 (+42%)
234 (+7%)
25 (+1%)
Heart failure
31 (+4%)
218 (+31%)
31 (+2%)
531 (+31%)
167 (+7%)
32 (+1%)
Pulmonary embolism
11 (+6%)
38 (+22%)
16 (+2%)
198 (+31%)
195 (+21%)
126 (+14%)
Cardiac arrest
5 (+5%)
11 (+11%)
13 (+9%)
80 (+56%)
64 (+6%)
13 (+1%)
Aortic diseases
0 (0%)
0 (+19%)
0 (0%)
16 (+4%)
4 (+1%)
14 (+2%)
Infective endocarditis
2 (+15%)
4 (+29%)
0 (0%)
36 (+22%)
24 (+6%)
35 (+9%)
Cardiogenic shock
0 (0%)
0 (0%)
0 (0%)
0 (0%)
13 (+4%)
41 (+14%)
VT and VF
0 (0%)
0 (0%)
0 (0%)
1 (+3%)
3 (+2%)
14 (+9%)
Deep vein thrombosis
0 (0%)
0 (0%)
0 (0%)
1 (+4%)
2 (+4%)
5 (+9%)
CV: cardiovascular; VT: ventricular tachycardia: VF: ventricular fibrillation
*the positive excess rate in hospital was due to setting those daily deaths below the expected historical average to zeros.
19
Figure 1. Time series of excess acute CV deaths, by place of death
20
Figure 2. Time series of excess acute CV deaths by COVID-19, by cause of death
21
Figure 3. Time series of excess acute CV deaths by cause of death and place of death
22
Supplementary table 1. ICD-10 codes used to define acute cardiovascular causes of death
*omitted all digits afterwards
ACS: acute coronary syndrome; STEMI: ST-elevation myocardial infarction; NSTEACS: non-ST-elevation acute coronary syndrome.
Notes: ACS combines STEMI, NSTEACS, type 2 myocardial infarction and reinfarction; stroke combines acute ischemic and acute
haemorrhagic strokes as well as other non-cerebral strokes and unspecified stroke types
Variable
Version
Diagnoses
STEMI
ICD-10
I210* I211* I212* I213
NSTEACS
ICD-10
I214 I219 I200 (UA)
Type 2 myocardial infarction
ICD-10
I21A1
Reinfarction
ICD-10
I22*
Heart Failure
ICD-10
I50* I42* I25.5 I130 I132 I110
Cardiac arrest
ICD-10
I462 (due to cardiac condition); I468 and I469
(due to non-cardiac condition)
Ventricular tachycardia and
ventricular fibrillation
ICD-10
VF: I4901 I4902; VT: I470 I472
Acute ischemic stroke
ICD-10
I63*
Acute haemorrhagic stroke
ICD-10
I60* I61* I62*
Other non-cerebral strokes
ICD-10
G463 G464 G465 G466 G467
Unspecified stroke type
ICD-10
I64*
Cardiogenic shock
ICD-10
R570
Pulmonary embolism
ICD-10
I26*
Deep Venous Thrombosis
ICD-10
I82.4*
Aortic aneurysm rupture
ICD-10
I713 I715 I718
Aortic dissection
ICD-10
I710*
Infective endocarditis
ICD-10
I33* I38* I39*
ResearchGate has not been able to resolve any citations for this publication.
Article
Full-text available
Objective To characterise the clinical features of patients admitted to hospital with coronavirus disease 2019 (covid-19) in the United Kingdom during the growth phase of the first wave of this outbreak who were enrolled in the International Severe Acute Respiratory and emerging Infections Consortium (ISARIC) World Health Organization (WHO) Clinical Characterisation Protocol UK (CCP-UK) study, and to explore risk factors associated with mortality in hospital. Design Prospective observational cohort study with rapid data gathering and near real time analysis. Setting 208 acute care hospitals in England, Wales, and Scotland between 6 February and 19 April 2020. A case report form developed by ISARIC and WHO was used to collect clinical data. A minimal follow-up time of two weeks (to 3 May 2020) allowed most patients to complete their hospital admission. Participants 20 133 hospital inpatients with covid-19. Main outcome measures Admission to critical care (high dependency unit or intensive care unit) and mortality in hospital. Results The median age of patients admitted to hospital with covid-19, or with a diagnosis of covid-19 made in hospital, was 73 years (interquartile range 58-82, range 0-104). More men were admitted than women (men 60%, n=12 068; women 40%, n=8065). The median duration of symptoms before admission was 4 days (interquartile range 1-8). The commonest comorbidities were chronic cardiac disease (31%, 5469/17 702), uncomplicated diabetes (21%, 3650/17 599), non-asthmatic chronic pulmonary disease (18%, 3128/17 634), and chronic kidney disease (16%, 2830/17 506); 23% (4161/18 525) had no reported major comorbidity. Overall, 41% (8199/20 133) of patients were discharged alive, 26% (5165/20 133) died, and 34% (6769/20 133) continued to receive care at the reporting date. 17% (3001/18 183) required admission to high dependency or intensive care units; of these, 28% (826/3001) were discharged alive, 32% (958/3001) died, and 41% (1217/3001) continued to receive care at the reporting date. Of those receiving mechanical ventilation, 17% (276/1658) were discharged alive, 37% (618/1658) died, and 46% (764/1658) remained in hospital. Increasing age, male sex, and comorbidities including chronic cardiac disease, non-asthmatic chronic pulmonary disease, chronic kidney disease, liver disease and obesity were associated with higher mortality in hospital. Conclusions ISARIC WHO CCP-UK is a large prospective cohort study of patients in hospital with covid-19. The study continues to enrol at the time of this report. In study participants, mortality was high, independent risk factors were increasing age, male sex, and chronic comorbidity, including obesity. This study has shown the importance of pandemic preparedness and the need to maintain readiness to launch research studies in response to outbreaks. Study registration ISRCTN66726260.
Article
Full-text available
Objective To quantify the impact of coronavirus disease 2019 (covid-19) on all cause mortality in Nembro, an Italian city severely affected by the covid-19 pandemic. Design Descriptive study. Setting Nembro, in the Bergamo province of Lombardy, northern Italy. Population Residents of Nembro. Main outcome measures Monthly all cause mortality between January 2012 and April 2020 (data to 11 April), number of confirmed deaths from covid-19 to 11 April 2020, and weekly absolute number of deaths between 1 January and 4 April across recent years by age group and sex. Results Nembro had 11 505 residents as of 1 January 2020. Monthly all cause mortality between January 2012 and February 2020 fluctuated around 10 per 1000 person years, with a maximum of 21.5 per 1000 person years. In March 2020, monthly all cause mortality reached a peak of 154.4 per 1000 person years. For the first 11 days in April, this rate decreased to 23.0 per 1000 person years. The observed increase in mortality was driven by the number of deaths among older people (≥65 years), especially men. From the outbreak onset until 11 April 2020, only 85 confirmed deaths from covid-19 in Nembro were recorded, corresponding to about half of the 166 deaths from all causes observed in that period. Conclusions The study findings show how covid-19 can have a considerable impact on the health of a small community. Furthermore, the results suggest that the full implications of the covid-19 pandemic can only be completely understood if, in addition to confirmed deaths related to covid-19, consideration is also given to all cause mortality in a given region and time frame.
Article
Full-text available
Background The medical, societal, and economic impact of the coronavirus disease 2019 (COVID-19) pandemic has unknown effects on overall population mortality. Previous models of population mortality are based on death over days among infected people, nearly all of whom thus far have underlying conditions. Models have not incorporated information on high-risk conditions or their longer-term baseline (pre-COVID-19) mortality. We estimated the excess number of deaths over 1 year under different COVID-19 incidence scenarios based on varying levels of transmission suppression and differing mortality impacts based on different relative risks for the disease. Methods In this population-based cohort study, we used linked primary and secondary care electronic health records from England (Health Data Research UK–CALIBER). We report prevalence of underlying conditions defined by Public Health England guidelines (from March 16, 2020) in individuals aged 30 years or older registered with a practice between 1997 and 2017, using validated, openly available phenotypes for each condition. We estimated 1-year mortality in each condition, developing simple models (and a tool for calculation) of excess COVID-19-related deaths, assuming relative impact (as relative risks [RRs]) of the COVID-19 pandemic (compared with background mortality) of 1·5, 2·0, and 3·0 at differing infection rate scenarios, including full suppression (0·001%), partial suppression (1%), mitigation (10%), and do nothing (80%). We also developed an online, public, prototype risk calculator for excess death estimation. Findings We included 3 862 012 individuals (1 957 935 [50·7%] women and 1 904 077 [49·3%] men). We estimated that more than 20% of the study population are in the high-risk category, of whom 13·7% were older than 70 years and 6·3% were aged 70 years or younger with at least one underlying condition. 1-year mortality in the high-risk population was estimated to be 4·46% (95% CI 4·41–4·51). Age and underlying conditions combined to influence background risk, varying markedly across conditions. In a full suppression scenario in the UK population, we estimated that there would be two excess deaths (vs baseline deaths) with an RR of 1·5, four with an RR of 2·0, and seven with an RR of 3·0. In a mitigation scenario, we estimated 18 374 excess deaths with an RR of 1·5, 36 749 with an RR of 2·0, and 73 498 with an RR of 3·0. In a do nothing scenario, we estimated 146 996 excess deaths with an RR of 1·5, 293 991 with an RR of 2·0, and 587 982 with an RR of 3·0. Interpretation We provide policy makers, researchers, and the public a simple model and an online tool for understanding excess mortality over 1 year from the COVID-19 pandemic, based on age, sex, and underlying condition-specific estimates. These results signal the need for sustained stringent suppression measures as well as sustained efforts to target those at highest risk because of underlying conditions with a range of preventive interventions. Countries should assess the overall (direct and indirect) effects of the pandemic on excess mortality. Funding National Institute for Health Research University College London Hospitals Biomedical Research Centre, Health Data Research UK.
Article
Full-text available
Background A relatively high mortality of severe coronavirus disease 2019 (COVID‐19) is worrying, the application of heparin in COVID‐19 has been recommended by some expert consensus due to the risk of disseminated intravascular coagulation and venous thromboembolism. However, its efficacy remains to be validated. Methods Coagulation results, medications and outcomes of consecutive patients being classified as severe COVID‐19 in Tongji hospital were retrospectively analysed. The 28‐day mortality between heparin users and nonusers were compared, also in different risk of coagulopaphy which was stratified by the sepsis‐induced coagulopathy (SIC) score or D‐dimer result. Results There were 449 patients with severe COVID‐19 enrolled into the study, 99 of them received heparin (mainly with low molecular weight heparin, LMWH) for 7 days or longer. The D‐dimer, prothrombin time and age were positively, and platelet count was negatively, correlated with 28‐day mortality in multivariate analysis. No difference on 28‐day mortality was found between heparin users and nonusers (30.3% vs 29.7%, P=0.910). But the 28‐day mortality of heparin users were lower than nonusers In patients with SIC score ≥4 (40.0% vs 64.2%, P=0.029), or D‐dimer > 6 fold of upper limit of normal (32.8% vs 52.4%, P=0.017). Conclusions Anticoagulant therapy mainly with LMWH appears to be associated with better prognosis in severe COVID‐19 patients meeting SIC criteria or with markedly elevated D‐dimer.
Article
Background Progressive respiratory failure is the primary cause of death in the coronavirus disease 2019 (Covid-19) pandemic. Despite widespread interest in the pathophysiology of the disease, relatively little is known about the associated morphologic and molecular changes in the peripheral lung of patients who die from Covid-19. Methods We examined 7 lungs obtained during autopsy from patients who died from Covid-19 and compared them with 7 lungs obtained during autopsy from patients who died from acute respiratory distress syndrome (ARDS) secondary to influenza A(H1N1) infection and 10 age-matched, uninfected control lungs. The lungs were studied with the use of seven-color immunohistochemical analysis, micro–computed tomographic imaging, scanning electron microscopy, corrosion casting, and direct multiplexed measurement of gene expression. Results In patients who died from Covid-19–associated or influenza-associated respiratory failure, the histologic pattern in the peripheral lung was diffuse alveolar damage with perivascular T-cell infiltration. The lungs from patients with Covid-19 also showed distinctive vascular features, consisting of severe endothelial injury associated with the presence of intracellular virus and disrupted cell membranes. Histologic analysis of pulmonary vessels in patients with Covid-19 showed widespread thrombosis with microangiopathy. Alveolar capillary microthrombi were 9 times as prevalent in patients with Covid-19 as in patients with influenza (P<0.001). In lungs from patients with Covid-19, the amount of new vessel growth — predominantly through a mechanism of intussusceptive angiogenesis — was 2.7 times as high as that in the lungs from patients with influenza (P<0.001). Conclusions In our small series, vascular angiogenesis distinguished the pulmonary pathobiology of Covid-19 from that of equally severe influenza virus infection. The universality and clinical implications of our observations require further research to define. (Funded by the National Institutes of Health and others.)