Evidence map›Paper›PMID 35611160›Full record

ArticleEClinicalMedicine2022

Impact of first UK COVID-19 lockdown on hospital admissions: Interrupted time series study of 32 million people.

Syed Ahmar Shah, Sinead Brophy, John Kennedy, Louis Fisher, Alex Walker, Brian Mackenna, Helen Curtis, Peter Inglesby, Simon Davy, Seb Bacon and 8 more

Open access · goldAbstract read
In one paragraph

Article in EClinicalMedicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 37 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
37citing papers in PubMed, 2 pooled it
8.0field-weighted citation impact, top 2% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

37 citing papers in PubMed, 2 syntheses or guidelines pooled it, 79 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

18 authors at 8 institutions in 2 countries.

Syed Ahmar ShahUsher Institute, Edinburgh Medical School, The University of Edinburgh, Edinburgh, UK.
Sinead BrophyData Science Building, Medical School, Swansea University, UK.
John KennedyData Science Building, Medical School, Swansea University, UK.
Louis FisherThe DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK.
Alex WalkerThe DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK.
Brian MackennaThe DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK.
Helen CurtisThe DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK.
Peter InglesbyThe DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK.
Simon DavyThe DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK.
Seb BaconThe DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK.
Ben GoldacreThe DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK.
Utkarsh AgrawalSchool of Medicine, University of St. Andrews, St Andrews, UK.
Emily MoorePublic Health Scotland, Glasgow, UK.
Colin R SimpsonSchool of Health, Wellington Faculty of Health, Victoria University of Wellington, Wellington, New Zealand.
John MacleodBristol Medical School, University of Bristol, Bristol, UK.
Roxane CookseyData Science Building, Medical School, Swansea University, UK.
Aziz SheikhUsher Institute, Edinburgh Medical School, The University of Edinburgh, Edinburgh, UK.
Srinivasa Vittal KatikireddiMRC/CSO Social and Public Health Sciences Unit, University of Glasgow, Glasgow, UK.
University of Oxford · GBSwansea University · GBUniversity of Edinburgh · GBMRC/CSO Social and Public Health Sciences Unit · GBPublic Health Scotland · GBUniversity of Bristol · GBUniversity of St Andrews · GBVictoria University of Wellington · NZ

Funding

Medical Research Council MC_PC_19004Medical Research Council MC_PC_19075Medical Research Council MC_PC_20030Medical Research Council MC_PC_20059Medical Research Council MC_UU_00022/2Medical Research Council MR/R008345/1Medical Research Council MR/S004084/1Medical Research Council MR/V015737/1Wellcome Trust
6 · The paper itself

Abstract

Background: Uncontrolled infection and lockdown measures introduced in response have resulted in an unprecedented challenge for health systems internationally. Whether such unprecedented impact was due to lockdown itself and recedes when such measures are lifted is unclear. We assessed the short- and medium-term impacts of the first lockdown measures on hospital care for tracer non-COVID-19 conditions in England, Scotland and Wales across diseases, sexes, and socioeconomic and ethnic groups. Methods: We used OpenSAFELY (for England), EAVEII (Scotland), and SAIL Databank (Wales) to extract weekly hospital admission rates for cancer, cardiovascular and respiratory conditions (excluding COVID-19) from the pre-pandemic period until 25/10/2020 and conducted a controlled interrupted time series analysis. We undertook stratified analyses and assessed admission rates over seven months during which lockdown restrictions were gradually lifted. Findings: Our combined dataset included 32 million people who contributed over 74 million person-years. Admission rates for all three conditions fell by 34.2% (Confidence Interval (CI): -43.0, -25.3) in England, 20.9% (CI: -27.8, -14.1) in Scotland, and 24.7% (CI: -36.7, -12.7) in Wales, with falls across every stratum considered. In all three nations, cancer-related admissions fell the most while respiratory-related admissions fell the least (e.g., rates fell by 40.5% (CI: -47.4, -33.6), 21.9% (CI: -35.4, -8.4), and 19.0% (CI: -30.6, -7.4) in England for cancer, cardiovascular-related, and respiratory-related admissions respectively). Unscheduled admissions rates fell more in the most than the least deprived quintile across all three nations. Some ethnic minority groups experienced greater falls in admissions (e.g., in England, unscheduled admissions fell by 9.5% (CI: -20.2, 1.2) for Whites, but 44.3% (CI: -71.0, -17.6), 34.6% (CI: -63.8, -5.3), and 25.6% (CI: -45.0, -6.3) for Mixed, Other and Black ethnic groups respectively). Despite easing of restrictions, the overall admission rates remained lower in England, Scotland, and Wales by 20.8%, 21.6%, and 22.0%, respectively when compared to the same period (August-September) during the pre-pandemic years. This corresponds to a reduction of 26.2, 23.8 and 30.2 admissions per 100,000 people in England, Scotland, and Wales respectively. Interpretation: Hospital care for non-COVID diseases fell substantially across England, Scotland, and Wales during the first lockdown, with reductions persisting for at least six months. The most deprived and minority ethnic groups were impacted more severely. Funding: This work was funded by the Medical Research Council as part of the Lifelong Health and Wellbeing study as part of National Core Studies (MC_PC_20030). SVK acknowledges funding from the Medical Research Council (MC_UU_00022/2), and the Scottish Government Chief Scientist Office (SPHSU17). EAVE II is funded by the Medical Research Council (MR/R008345/1) with the support of BREATHE - The Health Data Research Hub for Respiratory Health (MC_PC_19004), which is funded through the UK Research and Innovation Industrial Strategy Challenge Fund and delivered through Health Data Research UK. BG has received research funding from the NHS National Institute for Health Research (NIHR), the Wellcome Trust, Health Data Research UK, Asthma UK, the British Lung Foundation, and the Longitudinal Health and Wellbeing strand of the National Core Studies programme.

Indexed as

Covid-19Healthcare DisruptionHealthcare InequalitiesInterrupted time series analysisPandemicSARS-CoV-2

Identifiers

PMID35611160
PMCPMC9121886
OpenAlexW4280505115

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.