Evidence map›Paper›PMID 39857018›Full record

ReviewDiagnostics (Basel, Switzerland)2025

PET-CT Imaging in Hypertrophic Cardiomyopathy: A Narrative Review on Risk Stratification and Prognosis.

Patrícia Marques-Alves, Lino Gonçalves, Maria João Ferreira

Abstract readReview
In one paragraph

Review in Diagnostics (Basel, Switzerland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Protein phosphatase 2A impairs cardiac uptake of glucose in the mammalian heart.Naunyn-Schmiedeberg's archives of pharmacology · 2026
    Article
  2. Article
  3. Article
  4. Review
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.

Patrícia Marques-AlvesCardiology Department, Coimbra Hospital and University Center, 3004-561 Coimbra, Portugal.ORCID 0000-0002-2639-4058
Lino GonçalvesCardiology Department, Coimbra Hospital and University Center, 3004-561 Coimbra, Portugal.ORCID 0000-0001-9255-3064
Maria João FerreiraCardiology Department, Coimbra Hospital and University Center, 3004-561 Coimbra, Portugal.ORCID 0000-0001-8952-8618

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Hypertrophic cardiomyopathy (HCM) is a heterogeneous cardiac disease and one of its major challenges is the limited accuracy in stratifying the risk of sudden cardiac death (SCD). Positron emission tomography (PET), through the evaluation of myocardial blood flow (MBF) and metabolism using fluorodeoxyglucose (FDG) uptake, can reveal microvascular dysfunction, ischemia, and increased metabolic demands in the hypertrophied myocardium. These abnormalities are linked to several factors influencing disease progression, including arrhythmia development, ventricular dilation, and myocardial fibrosis. Fibroblast activation can also be evaluated using PET imaging, providing further insights into early-stage myocardial fibrosis. Conflicting findings underscore the need for further research into PET's role in risk stratification for HCM. If PET can establish a connection between parameters such as abnormal MBF or increased FDG uptake and SCD risk, it could enhance predictive accuracy. Additionally, PET holds significant potential for monitoring therapeutic outcomes. The aim of this review is to provide a comprehensive overview of the most significant data on disease progression, risk stratification, and prognosis in patients with HCM using cardiac PET-CT imaging.

Indexed as

hypertrophic cardiomyopathyPET-CT imagingsudden cardiac death

Identifiers

PMID39857018
PMCPMC11763384

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.