Evidence map›Paper›PMID 36447940›Full record

ArticleThe Lancet. Rheumatology2022

Incidence and management of inflammatory arthritis in England before and during the COVID-19 pandemic: a population-level cohort study using OpenSAFELY.

Mark D Russell, James B Galloway, Colm D Andrews, Brian MacKenna, Ben Goldacre, Amir Mehrkar, Helen J Curtis, Ben Butler-Cole, Thomas O'Dwyer, Sumera Qureshi and 9 more

Erratum issuedOpen access · hybridAbstract read
In one paragraph

Article in The Lancet. Rheumatology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
3.7field-weighted citation impact, top 6% 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

13 citing papers in PubMed, 23 citations in OpenAlex.

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  9. Observational
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  12. Barriers to the Diagnosis of Early Inflammatory Arthritis: A Literature Review.Open access rheumatology : research and reviews · 2023
    Review
  13. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

19 authors at 1 institution in 1 country.

Mark D RussellCentre for Rheumatic Diseases, King's College London, London, UK.
James B GallowayCentre for Rheumatic Diseases, King's College London, London, UK.
Colm D AndrewsBennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK.
Brian MacKennaBennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK.
Ben GoldacreBennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK.
Amir MehrkarBennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK.
Helen J CurtisBennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK.
Ben Butler-ColeBennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK.
Thomas O'DwyerBennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK.
Sumera QureshiCentre for Rheumatic Diseases, King's College London, London, UK.
Joanna M LedinghamRheumatology Department, Portsmouth Hospitals University NHS Trust, Portsmouth, UK.
Arti MahtoDepartment of Rheumatology, King's College Hospital NHS Foundation Trust, London, UK.
Andrew I RutherfordDepartment of Rheumatology, King's College Hospital NHS Foundation Trust, London, UK.
Maryam A AdasCentre for Rheumatic Diseases, King's College London, London, UK.
Edward AlveynCentre for Rheumatic Diseases, King's College London, London, UK.
Sam NortonCentre for Rheumatic Diseases, King's College London, London, UK.
Andrew P CopeCentre for Rheumatic Diseases, King's College London, London, UK.
Katie BechmanCentre for Rheumatic Diseases, King's College London, London, UK.
OpenSAFELY Collaborative
King's College London · GB

Funding

Medical Research Council MC_PC_20058Medical Research Council MC_PC_20059Medical Research Council MR/V015737/1Medical Research Council MR/W016729/1Wellcome Trust
6 · The paper itself

Abstract

Background: The impact of the COVID-19 pandemic on the incidence and management of inflammatory arthritis is not understood. Routinely captured data in secure platforms, such as OpenSAFELY, offer unique opportunities to understand how care for patients with inflammatory arthritis was impacted upon by the pandemic. Our objective was to use OpenSAFELY to assess the effects of the pandemic on diagnostic incidence and care delivery for inflammatory arthritis in England and to replicate key metrics from the National Early Inflammatory Arthritis Audit. Methods: In this population-level cohort study, we used primary care and hospital data for 17·7 million adults registered with general practices using TPP health record software, to explore the following outcomes between April 1, 2019, and March 31, 2022: (1) incidence of inflammatory arthritis diagnoses (rheumatoid arthritis, psoriatic arthritis, axial spondyloarthritis, and undifferentiated inflammatory arthritis) recorded in primary care; (2) time to first rheumatology assessment; (3) time to first prescription of a disease-modifying antirheumatic drug (DMARD) in primary care; and (4) choice of first DMARD. Findings: Among 17 683 500 adults, there were 31 280 incident inflammatory arthritis diagnoses recorded between April 1, 2019, and March 31, 2022. The mean age of diagnosed patients was 55·4 years (SD 16·6), 18 615 (59·5%) were female, 12 665 (40·5%) were male, and 22 925 (88·3%) of 25 960 with available ethnicity data were White. New inflammatory arthritis diagnoses decreased by 20·3% in the year commencing April, 2020, relative to the preceding year (5·1 Interpretation: Inflammatory arthritis diagnoses decreased markedly during the early phase of the pandemic. The impact on rheumatology assessment times and DMARD prescribing in primary care was less marked than might have been anticipated. This study demonstrates the feasibility of using routinely captured, near real-time data in the secure OpenSAFELY platform to benchmark care quality on a national scale, without the need for manual data collection. Funding: None.

Identifiers

PMID36447940
PMCPMC9691150
OpenAlexW4308074585

What OpenQuestion holds

Textmetadata
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.