Evidence mapPaperPMID 33234585Full record

ArticleCMAJ open

Feasibility of identifying and describing the burden of early-onset metabolic syndrome in primary care electronic medical record data: a cross-sectional analysis.

Jamie J Boisvenue, Carlo U Oliva, Donna P Manca, Jeffrey A Johnson, Roseanne O Yeung

Erratum issuedAbstract read
In one paragraph

Article in CMAJ open. 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 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.

  1. Article
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

5 authors.

Jamie J BoisvenueSchool of Public Health (Boisvenue, Johnson, Yeung), and Department of Computing Science (Oliva), Faculty of Science, and Department of Family Medicine (Manca), Faculty of Medicine & Dentistry, University of Alberta; Northern Alberta Primary Care Research Network (Manca); Division of Endocrinology and Metabolism (Yeung), Department of Medicine, Faculty of Medicine & Dentistry, University of Alberta, Edmonton, Alta. boisvenu@ualberta.ca.
Carlo U OlivaSchool of Public Health (Boisvenue, Johnson, Yeung), and Department of Computing Science (Oliva), Faculty of Science, and Department of Family Medicine (Manca), Faculty of Medicine & Dentistry, University of Alberta; Northern Alberta Primary Care Research Network (Manca); Division of Endocrinology and Metabolism (Yeung), Department of Medicine, Faculty of Medicine & Dentistry, University of Alberta, Edmonton, Alta.
Donna P MancaSchool of Public Health (Boisvenue, Johnson, Yeung), and Department of Computing Science (Oliva), Faculty of Science, and Department of Family Medicine (Manca), Faculty of Medicine & Dentistry, University of Alberta; Northern Alberta Primary Care Research Network (Manca); Division of Endocrinology and Metabolism (Yeung), Department of Medicine, Faculty of Medicine & Dentistry, University of Alberta, Edmonton, Alta.
Jeffrey A JohnsonSchool of Public Health (Boisvenue, Johnson, Yeung), and Department of Computing Science (Oliva), Faculty of Science, and Department of Family Medicine (Manca), Faculty of Medicine & Dentistry, University of Alberta; Northern Alberta Primary Care Research Network (Manca); Division of Endocrinology and Metabolism (Yeung), Department of Medicine, Faculty of Medicine & Dentistry, University of Alberta, Edmonton, Alta.
Roseanne O YeungSchool of Public Health (Boisvenue, Johnson, Yeung), and Department of Computing Science (Oliva), Faculty of Science, and Department of Family Medicine (Manca), Faculty of Medicine & Dentistry, University of Alberta; Northern Alberta Primary Care Research Network (Manca); Division of Endocrinology and Metabolism (Yeung), Department of Medicine, Faculty of Medicine & Dentistry, University of Alberta, Edmonton, Alta.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe prevalence of metabolic syndrome is growing worldwide, yet remains underinvestigated in Canadian young adults. We sought to explore the use of a harmonized case definition specific to early-onset metabolic syndrome and determine its feasibility in assessing the prevalence of metabolic syndrome among electronic medical record (EMR) data of young adults in Northern Alberta.

methodsWe conducted a cross-sectional study using a sample of EMR data from young adult patients aged 18-40 years and residing in Northern Alberta, who had an encounter with a participating primary care clinic between June 29, 2015, and June 29, 2018. Physical examination, laboratory investigation and disease diagnosis data were collected. A case definition and algorithm were developed to assess the feasibility of identifying metabolic syndrome, including measures for body mass index (BMI), blood pressure (BP), dysglycemia, hypertriglyceridemia, high-density lipoprotein cholesterol, diabetes and hypertension.

resultsAmong 15 766 young adults, the case definition suggested the prevalence of metabolic syndrome was 4.4%, 95% confidence interval (CI) 4.1%-4.7%. The most frequent 3-factor combination (41.6%, 95% CI 37.9%-45.3%) of metabolic syndrome criteria consisted of being overweight or obese, having elevated BP and hypertriglyceridemia. Half of metabolic syndrome cases (51.3%, 95% CI 47.6%-55.0%) were missing measures for fasting blood glucose, and one-fifth were missing a hemoglobin A

interpretationWe have shown that our case definition is feasible in identifying early-onset metabolic syndrome using EMR data; however, the degree of missing data limits the feasibility in assessing prevalence. Further investigation is required to validate this case definition for metabolic syndrome in the EMR data, which may involve comparing this definition to other validated metabolic syndrome case definitions.

Indexed as

AdolescentAdultAlbertaBlood GlucoseBlood PressureBody Mass IndexCholesterol, HDLCross-Sectional StudiesDiabetes MellitusElectronic Health RecordsFeasibility StudiesFemaleGlycated HemoglobinHumansHypertensionHypertriglyceridemiaBlood GlucoseCholesterol, HDLGlycated HemoglobinTriglycerides

Identifiers

PMID33234585
PMCPMC7721254

What Socratic holds

Textmetadata
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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 Socratic graph.