Evidence map›Paper›PMID 38864982›Full record

ReviewCurrent cardiology reports2024

Optical Coherence Tomography in the Assessment and Management of Cardiac Allograft Vasculopathy.

Arka Chatterjee, Madhan Shanmugasundaram, Kwan S Lee, Toshinobu Kazui, Indranee N Rajapreyar, Deepak Acharya

Abstract readReview
PubMed Publisher
In one paragraph

Review in Current cardiology reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

6 authors.

Arka ChatterjeeDivision of Cardiology, University of Arizona College of Medicine, 1501 N Campbell Avenue, Tucson, AZ, 85719, USA. arkachatterjee@arizona.edu.
Madhan ShanmugasundaramDivision of Cardiology, University of Arizona College of Medicine, 1501 N Campbell Avenue, Tucson, AZ, 85719, USA.
Kwan S LeeDivision of Cardiology, Mayo Clinic Arizona, Phoenix, AZ, USA.
Toshinobu KazuiDepartment of Cardiothoracic Surgery, University of Arizona College of Medicine, Tucson, AZ, USA.
Indranee N RajapreyarDivision of Cardiology, Tufts Medical Center, Boston, MA, USA.
Deepak AcharyaDivision of Cardiology, University of Arizona College of Medicine, 1501 N Campbell Avenue, Tucson, AZ, 85719, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purpose of reviewCardiac Allograft vasculopathy (CAV) is a major barrier to improving outcomes after heart transplantation. Coronary angiography has very low sensitivity to detect early CAV and intravascular ultrasound (IVUS) only improves it to some extent. In this article, we detail the current evidence surrounding use of Optical Coherence tomography (OCT) in patients with CAV. RECENT

findingsOCT has the ability to recognize CAV at earlier stages with intimal thickness < 150 μm, can characterize CAV in almost pathologic / microscopic detail - plaque characteristics are better visualized and novel early features such as layered fibrotic plaques and microchannels have been identified. Progression of CAV can be monitored also, with promise shown in automated serial measurements also. OCT has significantly advanced our understanding of the pathophysiology-as well as permits precise monitoring and surveillance of the disease. Potential treatment options could also be evaluated using OCT.

Indexed as

AllograftsCoronary Artery DiseaseHeart TransplantationTomography, Optical CoherenceCoronary AngiographyCoronary VesselsHumansUltrasonography, InterventionalCardiac allograft vasculopathyOptical coherence tomography

Identifiers

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.