Evidence map›Paper›PMID 35351727›Full record

ArticleBMJ open2022

Impact of chronic kidney disease on case ascertainment for hospitalised acute myocardial infarction: an English cohort study.

Patrick Bidulka, Jemima Scott, Dominic M Taylor, Udaya Udayaraj, Fergus Caskey, Lucy Teece, Michael Sweeting, John Deanfield, Mark de Belder, Spiros Denaxas and 3 more

Open access · goldAbstract read
In one paragraph

Article in BMJ open, 2022. 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
1.1field-weighted citation impact, top 22% 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

5 citing papers in PubMed, 7 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

13 authors at 7 institutions in 1 country.

Patrick Bidulka *Department of Non-Communicable Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UK patrick.bidulka1@lshtm.ac.uk.ORCID 0000-0001-7644-2030
Jemima Scott *Population Health Sciences, University of Bristol, Bristol, UK.
Dominic M TaylorPopulation Health Sciences, University of Bristol, Bristol, UK.
Udaya UdayarajOxford Kidney Unit, Churchill Hospital, Oxford, Oxfordshire, UK.
Fergus CaskeyPopulation Health Sciences, University of Bristol, Bristol, UK.
Lucy TeeceBiostatistics Research Group, Department of Health Sciences, University of Leicester, Leicester, Leicestershire, UK.
Michael SweetingBiostatistics Research Group, Department of Health Sciences, University of Leicester, Leicester, Leicestershire, UK.
John DeanfieldNational Institute for Cardiovascular Outcomes Research (NICOR), Barts Health NHS Trust, London, UK.
Mark de BelderNational Institute for Cardiovascular Outcomes Research (NICOR), Barts Health NHS Trust, London, UK.
Spiros DenaxasInstitute of Health Informatics, Faculty of Population Health Sciences, University College London, London, UK.
Clive WestonGlangwili General Hospital, Carmarthen, Carmarthenshire, UK.
David Adlam *Department of Cardiovascular Sciences, University of Leicester and NIHR Leicester Biomedical Research Centre, Leicester, Leicestershire, UK.
Dorothea Nitsch *Department of Non-Communicable Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UK.
North Bristol NHS Trust · GBUniversity of Leicester · GBBarts Health NHS Trust · GBLondon School of Hygiene & Tropical Medicine · GBChurchill Hospital · GBGlangwili General Hospital · GBHealth Data Research UK · GB

Funding

British Heart Foundation SP/16/5/32415Department of HealthMedical Research Council MC_PC_20059Medical Research Council MR/K006584/1
6 · The paper itself

Abstract

objectivesAcute myocardial infarction (AMI) case ascertainment improves for the UK general population using linked health data sets. Because care pathways for people with chronic kidney disease (CKD) change based on disease severity, AMI case ascertainment for these people may differ compared with the general population. We aimed to determine the association between CKD severity and AMI case ascertainment in two secondary care data sets, and the agreement in estimated glomerular filtration rate (eGFR) between the same data sets.

methodsWe used a cohort study design. Primary care records for people with CKD or risk factors for CKD, identified using the National CKD Audit (2015-2017), were linked to the Myocardial Ischaemia National Audit Project (MINAP, 2007-2017) and Hospital Episode Statistics (HES, 2007-2017) secondary care registries. People with an AMI recorded in either MINAP, HES or both were included in the study cohort. CKD status was defined using eGFR, derived from the most recent serum creatinine value recorded in primary care. Moderate-severe CKD was defined as eGFR <60 mL/min/1.73 m

resultsWe identified 6748 AMIs: 23% were recorded in both MINAP and HES, 66% in HES only and 11% in MINAP only. Compared with people at risk of CKD or with mild CKD, AMIs in people with moderate-severe CKD were more likely to be recorded in both MINAP and HES (42% vs 11%, respectively), or MINAP only (22% vs 5%), and less likely to be recorded in HES only (36% vs 84%). People with AMIs recorded in HES only or MINAP only had increased odds of death during hospitalisation compared with those recorded in both (adjusted OR 1.61, 95% CI 1.32 to 1.96 and OR 1.60, 95% CI 1.26 to 2.04, respectively). Agreement between eGFR at AMI admission (MINAP) and in primary care was poor (kappa (K) 0.42, SE 0.012).

conclusionsAMI case ascertainment is incomplete in both MINAP and HES, and is associated with CKD severity.

Indexed as

Myocardial InfarctionRenal Insufficiency, ChronicCohort StudiesGlomerular Filtration RateHumansRegistriesAuditCARDIOLOGYMyocardial infarctionNEPHROLOGYSTATISTICS & RESEARCH METHODS

Identifiers

PMID35351727
PMCPMC8961119
OpenAlexW4220753402

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.