Evidence map›Paper›PMID 39591388›Full record

ArticlePLoS medicine2024

Routine measurement of cardiometabolic disease risk factors in primary care in England before, during, and after the COVID-19 pandemic: A population-based cohort study.

Frederick K Ho, Caroline Dale, Mehrdad A Mizani, Thomas Bolton, Ewan R Pearson, Jonathan Valabhji, Christian Delles, Paul Welsh, Shinya Nakada, Daniel Mackay and 12 more

Abstract read
In one paragraph

Article in PLoS medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
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

5 citing papers in PubMed.

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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

22 authors.

Frederick K HoSchool of Health and Wellbeing, University of Glasgow, Glasgow, United Kingdom.ORCID https://orcid.org/0000-0001-7190-9025
Caroline DaleDepartment of Pharmacology & Therapeutics, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool, United Kingdom.
Mehrdad A MizaniBritish Heart Foundation Data Science Centre, Health Data Research UK, London, United Kingdom.ORCID https://orcid.org/0000-0002-2441-895X
Thomas BoltonBritish Heart Foundation Data Science Centre, Health Data Research UK, London, United Kingdom.ORCID https://orcid.org/0000-0002-2998-7975
Ewan R PearsonBritish Heart Foundation Data Science Centre, Health Data Research UK, London, United Kingdom.
Jonathan ValabhjiDivision of Metabolism, Digestion and Reproduction, Imperial College London, London, United Kingdom.
Christian DellesSchool of Cardiovascular and Metabolic Health, University of Glasgow, Glasgow, United Kingdom.ORCID https://orcid.org/0000-0003-2238-2612
Paul WelshSchool of Cardiovascular and Metabolic Health, University of Glasgow, Glasgow, United Kingdom.ORCID https://orcid.org/0000-0002-7970-3643
Shinya NakadaSchool of Health and Wellbeing, University of Glasgow, Glasgow, United Kingdom.
Daniel MackaySchool of Health and Wellbeing, University of Glasgow, Glasgow, United Kingdom.
Jill P PellSchool of Health and Wellbeing, University of Glasgow, Glasgow, United Kingdom.
Chris TomlinsonInstitute of Health Informatics, University College London, London, United Kingdom.ORCID https://orcid.org/0000-0002-0903-5395
Steffen E PetersenBritish Heart Foundation Data Science Centre, Health Data Research UK, London, United Kingdom.ORCID https://orcid.org/0000-0003-4622-5160
Benjamin BraySchool of Population Health and Environmental Sciences, King's College London, London, United Kingdom.
Mark AshworthDepartment of Population Health Sciences, King's College London, London, United Kingdom.
Kazem RahimiNuffield Department of Women's & Reproductive Health, University of Oxford, Oxford, United Kingdom.ORCID https://orcid.org/0000-0002-4807-4610
Mamas MamasSchool of Medicine, Keele University, Keele, United Kingdom.
Julian HalcoxSwansea University Medical School, Faculty of Medicine, Health and Life Science, Swansea University, Swansea, United Kingdom.ORCID https://orcid.org/0000-0001-6926-2947
Cathie SudlowDivision of Population Health & Genomics, University of Dundee, Dundee, United Kingdom.ORCID https://orcid.org/0000-0002-7725-7520
Reecha SofatDepartment of Pharmacology & Therapeutics, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool, United Kingdom.
Naveed SattarInstitute of Health Informatics, University College London, London, United Kingdom.ORCID https://orcid.org/0000-0002-1604-2593
CVD-COVID-UK/COVID-IMPACT Consortium

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThis study estimated to what extent the number of measurements of cardiometabolic risk factors (e.g., blood pressure, cholesterol, glycated haemoglobin) were impacted by the COVID-19 pandemic and whether these have recovered to expected levels. METHODS AND

findingsA cohort of individuals aged ≥18 years in England with records in the primary care-COVID-19 General Practice Extraction Service Data for Pandemic Planning and Research (GDPPR) were identified. Their records of 12 risk factor measurements were extracted between November 2018 and March 2024. Number of measurements per 1,000 individuals were calculated by age group, sex, ethnicity, and area deprivation quintile. The observed number of measurements were compared to a composite expectation band, derived as the union of the 95% confidence intervals of 2 estimates: (1) a projected trend based on data prior to the COVID-19 pandemic; and (2) an assumed stable trend from before pandemic. Point estimates were calculated as the mid-point of the expectation band. A cohort of 49,303,410 individuals aged ≥18 years were included. There was sharp drop in all measurements in March 2020 to February 2022, but overall recovered to the expected levels during March 2022 to February 2023 except for blood pressure, which had prolonged recovery. In March 2023 to March 2024, blood pressure measurements were below expectation by 16% (-19 per 1,000) overall, in people aged 18 to 39 (-23%; -18 per 1,000), 60 to 79 (-17%; -27 per 1,000), and ≥80 (-31%; -57 per 1,000). There was suggestion that recovery in blood pressure measurements was socioeconomically patterned. The second most deprived quintile had the highest deviation (-20%; -23 per 1,000) from expectation compared to least deprived quintile (-13%; -15 per 1,000).

conclusionsThere was a substantial reduction in routine measurements of cardiometabolic risk factors following the COVID-19 pandemic, with variable recovery. The implications for missed diagnoses, worse prognosis, and health inequality are a concern.

Indexed as

Cardiometabolic Risk FactorsCOVID-19Primary Health CareAdolescentAdultAgedAged, 80 and overBlood PressureCardiovascular DiseasesCholesterolCohort StudiesEnglandFemaleGlycated HemoglobinHumansMaleCholesterolGlycated Hemoglobin

Identifiers

PMID39591388
PMCPMC11593757

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Registered trials

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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.