Evidence map›Paper›PMID 23250657›Full record

ReviewCurrent cardiology reports2013

Imaging of inflammation and calcification in aortic stenosis.

Marc R Dweck, Nikhil V Joshi, James H F Rudd, David E Newby

Abstract readReview
PubMed Publisher
In one paragraph

Review in Current cardiology reports, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
0.8field-weighted citation impact, top 24% 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

0 citing papers in PubMed, 8 citations in OpenAlex.

No citing paper in PubMed yet.

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

4 authors at 2 institutions in 1 country.

Marc R DweckCentre for Cardiovascular Science, University of Edinburgh, Little France Crescent, UK. MDweck@staffmail.ed.ac.uk
Nikhil V Joshi
James H F Rudd
David E Newby
University of Edinburgh · GBUniversity of Cambridge · GB

Funding

British Heart Foundation CH/09/002British Heart Foundation FS/10/026British Heart Foundation FS/10/026/28209British Heart Foundation FS/12/29/29463British Heart Foundation PG/09/083/27667Chief Scientist Office ETM/160Medical Research Council G0701127
6 · The paper itself

Abstract

Aortic stenosis is a common clinical condition that is set to increase in prevalence with an ageing population. However, reliable methods for predicting disease progression and effective medical therapies are lacking. Inflammation and calcification are believed to have a key role but until recently the relative contributions of these processes at the different stages of the disease process were unknown. Recent studies have suggested that combined positron emission tomography and computed tomography (PET/CT) is a feasible and reproducible method for measuring the degree of inflammation and calcification in the valves of patients with aortic stenosis. For the first time this provides us with a potential method of measuring disease activity, which might then allow prediction of progression and act as a surrogate endpoint in studies of novel therapies. In this review, we will examine the basis for PET/CT scanning and discuss the studies that have investigated its use in aortic stenosis. We will cover the work that is still required in order to validate this technique and how it might impact on future clinical research and practice. Finally, we will examine alternative imaging methods that might also provide insight in to the underlying pathogenesis of this important and common clinical condition.

Indexed as

Aortic Valve StenosisCalcinosisFeasibility StudiesHeart Valve DiseasesHumansInflammationMultimodal ImagingPositron-Emission TomographyTomography, X-Ray Computed

Identifiers

PMID23250657
OpenAlexW2052784801

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.