Evidence map›Paper›PMID 33006568›Full record

ArticleJMIR research protocols2020

Investigation of Cardiovascular Health and Risk Factors Among the Diverse and Contemporary Population in London (the TOGETHER Study): Protocol for Linking Longitudinal Medical Records.

Kanika Dharmayat, Maria Woringer, Nikolaos Mastellos, Della Cole, Josip Car, Sumantra Ray, Kamlesh Khunti, Azeem Majeed, Kausik K Ray, Sreenivasa Rao Kondapally Seshasai

Open access · goldAbstract read
In one paragraph

Article in JMIR research protocols, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact, top 88% 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

1 citing paper in PubMed, 1 citations in OpenAlex.

  1. Article
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

10 authors at 5 institutions in 1 country.

Kanika DharmayatDepartment of Primary Care and Public Health, Imperial Centre for Cardiovascular Disease Prevention, Imperial College London, London, United Kingdom.ORCID https://orcid.org/0000-0003-1371-5868
Maria WoringerDepartment of Primary Care and Public Health, Imperial Centre for Cardiovascular Disease Prevention, Imperial College London, London, United Kingdom.ORCID https://orcid.org/0000-0002-8206-028X
Nikolaos MastellosDepartment of Primary Care and Public Health, Imperial Centre for Cardiovascular Disease Prevention, Imperial College London, London, United Kingdom.ORCID https://orcid.org/0000-0003-4573-3657
Della ColeCardiovascular Sciences Research Centre, St George's, University of London, London, United Kingdom.ORCID https://orcid.org/0000-0003-3142-1580
Josip CarGlobal eHealth Unit, Department of Primary Care and Public Health, Imperial College London, London, United Kingdom.ORCID https://orcid.org/0000-0001-8969-371X
Sumantra RayNNEdPro Global Centre for Nutrition and Health in Cambridge, University of Cambridge, Cambridge, United Kingdom.ORCID https://orcid.org/0000-0003-3295-168X
Kamlesh KhuntiPrimary Care Diabetes and Vascular Medicine, University of Leicester, Leicester, United Kingdom.ORCID https://orcid.org/0000-0003-2343-7099
Azeem MajeedDepartment of Primary Care and Public Health, Imperial College London, London, United Kingdom.ORCID https://orcid.org/0000-0002-2357-9858
Kausik K Ray *Department of Primary Care and Public Health, Imperial Centre for Cardiovascular Disease Prevention, Imperial College London, London, United Kingdom.ORCID https://orcid.org/0000-0003-0508-0954
Sreenivasa Rao Kondapally Seshasai *St George's Hospital NHS Foundation Trust, London, United Kingdom.ORCID https://orcid.org/0000-0002-5948-6522
Imperial College London · GBSt George's Hospital · GBSt George's, University of London · GBUniversity of Cambridge · GBUniversity of Leicester · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundGlobal trends in cardiovascular disease (CVD) exhibit considerable interregional and interethnic differences, which in turn affect long-term CVD risk across diverse populations. An in-depth understanding of the interplay between ethnicity, socioeconomic status, and CVD risk factors and mortality in a contemporaneous population is crucial to informing health policy and resource allocation aimed at mitigating long-term CVD risk. Generating bespoke large-scale and reliable data with sufficient numbers of events is expensive and time-consuming but can be circumvented through utilization and linkage of data routinely collected in electronic health records (EHR).

objectiveWe aimed to characterize the burden of CVD risk factors across different ethnicities, age groups, and socioeconomic groups, and study CVD incidence and mortality by EHR linkage in London.

methodsThe proposed study will initially be a cross-sectional observational study unfolding into prospective CVD ascertainment through longitudinal follow-up involving linked data. The government-funded National Health System (NHS) Health Check program provides an opportunity for the systematic collation of CVD risk factors on a large scale. NHS Health Check data on approximately 200,000 individuals will be extracted from consenting general practices across London that use the Egton Medical Information Systems (EMIS) EHR software. Data will be analyzed using appropriate statistical techniques to (1) determine the cross-sectional burden of CVD risk factors and their prospective association with CVD outcomes, (2) validate existing prediction tools in diverse populations, and (3) develop bespoke risk prediction tools across diverse ethnic groups.

resultsEnrollment began in January 2019 and is ongoing with initial results to be published mid-2021.

conclusionsThere is an urgent need for more real-life population health studies based on analyses of routine health data available in EHRs. Findings from our study will help quantify, on a large scale, the contemporaneous burden of CVD risk factors by geography and ethnicity in a large multiethnic urban population. Such detailed understanding (especially interethnic and sociodemographic variations) of the burden of CVD risk and its determinants, including heredity, environment, diet, lifestyle, and socioeconomic factors, in a large population sample, will enable the development of tailored and dynamic (continuously learning from new data) risk prediction tools for diverse ethnic groups, and thereby enable the personalized provision of prevention strategies and care. We anticipate that this systematic approach of linking routinely collected data from EHRs to study CVD can be conducted in other settings as EHRs are being implemented worldwide. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/17548.

Indexed as

cardiovascular healthcardiovascular risk factorselectronic health records

Identifiers

PMID33006568
PMCPMC7568219
OpenAlexW3045260523

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.