Evidence map›Paper›PMID 27889901›Full record

ArticleJournal of community genetics2017

A novel approach to screening for familial hypercholesterolemia in a large public venue.

Megan Campbell, Jessa Humanki, Heather Zierhut

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of community genetics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed, 1 pooled it
–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

14 citing papers in PubMed, 1 synthesis or guideline pooled it.

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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

3 authors.

Megan CampbellDepartment of Genetics, Cell Biology, and Development, University of Minnesota-Twin Cities, 320 Church Street SE, 6-160 Jackson Hall, Minneapolis, MN, 55455, USA.
Jessa HumankiDepartment of Genetics, Cell Biology, and Development, University of Minnesota-Twin Cities, 320 Church Street SE, 6-160 Jackson Hall, Minneapolis, MN, 55455, USA.
Heather ZierhutDepartment of Genetics, Cell Biology, and Development, University of Minnesota-Twin Cities, 320 Church Street SE, 6-160 Jackson Hall, Minneapolis, MN, 55455, USA. zier0034@umn.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The primary aim of this study was to test the feasibility of a public health screening program to identify individuals at high risk of familial hypercholesterolemia through a novel screening approach at a large public venue. A finger-prick, non-fasting lipid panel was obtained, and a survey which consisted of 44 open- and close-ended questions divided into four sections: medical and family history of FH, opinions of cascade genetic testing, patient activation, and demographics was completed. A total of 971 participants met criteria and completed a cholesterol screen. In total, five individuals met either the Simon Broome Register or the Dutch Lipid Clinic Network criteria for possible familial hypercholesterolemia. Participants were generally positive towards genetic testing, and the vast majority listed they had no barriers to communication of genetic testing information to family members. However, the most common barrier listed was lack of communication skills. Our results suggest that a public health screening program for FH is viable at a large public venue. We argue that further research is needed to expand this study to a fully operational screening program.

Indexed as

CholesterolFamilial hypercholesterolemiaGenetic communicationGenetic informationGenetic screeningGenetic testing

Identifiers

PMID27889901
PMCPMC5222759

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.