Evidence map›Paper›PMID 35666397›Full record

ArticleEJNMMI research2022

Quantifying sodium [

Samuel Debono, Jennifer Nash, Alexander J Fletcher, Maaz B J Syed, Scott I Semple, Edwin J R van Beek, Alison Fletcher, Sebastien Cadet, Michelle C Williams, Damini Dey and 4 more

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in EJNMMI research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.5field-weighted citation impact, top 37% 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

2 citing papers in PubMed, 3 citations in OpenAlex.

  1. Article
  2. Aortic sodium [Heart (British Cardiac Society) · 2023
    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

14 authors at 3 institutions in 2 countries.

Samuel DebonoThe University of Edinburgh Centre for Cardiovascular Science, Chancellor's Building, University of Edinburgh, 49 Little France Crescent, Edinburgh, EH16 4SB, UK. samuel.debono@ed.ac.uk.ORCID http://orcid.org/0000-0002-7834-8766
Jennifer NashThe University of Edinburgh Centre for Cardiovascular Science, Chancellor's Building, University of Edinburgh, 49 Little France Crescent, Edinburgh, EH16 4SB, UK.
Alexander J FletcherThe University of Edinburgh Centre for Cardiovascular Science, Chancellor's Building, University of Edinburgh, 49 Little France Crescent, Edinburgh, EH16 4SB, UK.
Maaz B J SyedThe University of Edinburgh Centre for Cardiovascular Science, Chancellor's Building, University of Edinburgh, 49 Little France Crescent, Edinburgh, EH16 4SB, UK.
Scott I SempleThe University of Edinburgh Centre for Cardiovascular Science, Chancellor's Building, University of Edinburgh, 49 Little France Crescent, Edinburgh, EH16 4SB, UK.
Edwin J R van BeekThe University of Edinburgh Centre for Cardiovascular Science, Chancellor's Building, University of Edinburgh, 49 Little France Crescent, Edinburgh, EH16 4SB, UK.
Alison FletcherEdinburgh Imaging Facility, Queen's Medical Research Institute, University of Edinburgh, Edinburgh, UK.
Sebastien CadetDivision of Artificial Intelligence, Department of Medicine, Cedars-Sinai Medical Centre, Biomedical Imaging Research Institute, Los Angeles, USA.
Michelle C WilliamsThe University of Edinburgh Centre for Cardiovascular Science, Chancellor's Building, University of Edinburgh, 49 Little France Crescent, Edinburgh, EH16 4SB, UK.
Damini DeyDivision of Artificial Intelligence, Department of Medicine, Cedars-Sinai Medical Centre, Biomedical Imaging Research Institute, Los Angeles, USA.
Piotr J SlomkaDivision of Artificial Intelligence, Department of Medicine, Cedars-Sinai Medical Centre, Biomedical Imaging Research Institute, Los Angeles, USA.
Rachael O ForsytheThe University of Edinburgh Centre for Cardiovascular Science, Chancellor's Building, University of Edinburgh, 49 Little France Crescent, Edinburgh, EH16 4SB, UK.
Marc R DweckThe University of Edinburgh Centre for Cardiovascular Science, Chancellor's Building, University of Edinburgh, 49 Little France Crescent, Edinburgh, EH16 4SB, UK.
David E NewbyThe University of Edinburgh Centre for Cardiovascular Science, Chancellor's Building, University of Edinburgh, 49 Little France Crescent, Edinburgh, EH16 4SB, UK.
University of Edinburgh · GBCedars-Sinai Medical Center · USThe Queen's Medical Research Institute · GB

Funding

British Heart Foundation CH/09/002/26360British Heart Foundation FS/14/78/31020British Heart Foundation FS/18/31/33676British Heart Foundation FS/ICRF/20/26002British Heart Foundation PG/21/10461Medical Research Council G0701127
6 · The paper itself

Abstract

backgroundAortic microcalcification activity is a recently described method of measuring aortic sodium [

methodsTwenty-five patients with abdominal aortic aneurysms underwent an sodium [

resultsThe aortic microcalcification activity method was much quicker to perform than the TBR method (14 versus 40 min, p < 0.001). There was moderate-to-good agreement between TBR and aortic microcalcification activity measurements for maximum (interclass correlation co-efficient, 0.67) and mean (interclass correlation co-efficient, 0.88) values. These correlations sequentially improved with the application of thresholding (intraclass correlation coefficient 0.93, 95% confidence interval 0.89-0.95) and variable diameter (intraclass correlation coefficient 0.97, 95% confidence interval 0.94-0.99) techniques. The optimised method had good intra-observer (mean 1.57 ± 0.42, bias 0.08, co-efficient of repeatability 0.36 and limits of agreement - 0.43 to 0.43) and inter-observer (mean 1.57 ± 0.42, bias 0.08, co-efficient of repeatability 0.47 and limits of agreement - 0.53 to 0.53) repeatability.

conclusionsAortic microcalcification activity is a quick and simple method which demonstrates good intra-observer and inter-observer repeatabilities and provides measures of sodium [

Indexed as

AneurysmsImage analysisPositron emission tomographyRadiotracer

Identifiers

PMID35666397
PMCPMC9170850
OpenAlexW4281773189

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.