Evidence map›Paper›PMID 28474325›Full record

ReviewHeart failure reviews2017

A multidimensional sight on cardiac failure: uncovered from structural to molecular level.

Vijay Urmaliya, Gustavo Franchelli

Abstract readReview
PubMed Publisher
In one paragraph

Review in Heart failure reviews, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Review
  2. Article
  3. 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

2 authors.

Vijay UrmaliyaDiscovery Sciences, Janssen Research & Development, Beerse, Belgium. vurmaliy@its.jnj.com.
Gustavo FranchelliR.E.D. Laboratories NV/SA, Zellik, Belgium.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Heart failure is one of the leading causes of death, with high mortality rate within 5 years after diagnosis. Treatment and prognosis options for heart failure primarily targeted on hemodynamic and neurohumoral components that drive progressive deterioration of the heart. However, given the multifactorial background that eventually leads to the "phenotype" named heart failure, better insight into the various components may lead to personalized treatment opportunities. Indeed, currently used criteria to diagnose and/or classify heart failure are possibly too focused on phenotypic improvement rather than the molecular driver of the disease and could therefore be further refined by integrating the leap of molecular and cellular knowledge. The ambiguity of the ejection fraction-based classification criteria became evident with development of advanced molecular techniques and the dawn of omics disciplines which introduced the idea that disease is caused by a myriad of cellular and molecular processes rather than a single event or pathway. The fact that different signaling pathways may underlie similar clinical manifestations calls for a more holistic study of heart failure. In this context, the systems biology approach can offer a better understanding of how different components of a system are altered during disease and how they interact with each other, potentially leading to improved diagnosis and classification of this condition. This review is aimed at addressing heart failure through a multilayer approach that covers individually some of the anatomical, morphological, functional, and tissue aspects, with focus on cellular and subcellular features as an alternative insight into new therapeutic opportunities.

Indexed as

Heart FailureHeart VentriclesDiagnostic ImagingHumansMolecular BiologySeverity of Illness IndexStroke VolumeVentricular RemodelingCardiac dysfunctionHeart failureHypertrophyPathophysiologyRemodelingSystems biology

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.