Evidence map›Paper›PMID 34068270›Full record

ArticleBioengineering (Basel, Switzerland)2021

On the Left Ventricular Remodeling of Patients with Stenotic Aortic Valve: A Statistical Shape Analysis.

Salvatore Cutugno, Tommaso Ingrassia, Vincenzo Nigrelli, Salvatore Pasta

Open access · goldAbstract read
In one paragraph

Article in Bioengineering (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
1.3field-weighted citation impact, top 19% 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

6 citing papers in PubMed, 11 citations in OpenAlex.

  1. Article
  2. Full-field surrogate modeling of cardiac electrophysiology encoding geometric variability.Computer methods in applied mechanics and engineering · 2026
    Article
  3. Article
  4. Article
  5. Article
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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 1 institution in 1 country.

Salvatore CutugnoDipartimento di Ingegneria (DING), Università degli Studi di Palermo, Viale delle Scienze Ed.8, 90128 Palermo, Italy.
Tommaso IngrassiaDipartimento di Ingegneria (DING), Università degli Studi di Palermo, Viale delle Scienze Ed.8, 90128 Palermo, Italy.
Vincenzo NigrelliDipartimento di Ingegneria (DING), Università degli Studi di Palermo, Viale delle Scienze Ed.8, 90128 Palermo, Italy.
Salvatore PastaDipartimento di Ingegneria (DING), Università degli Studi di Palermo, Viale delle Scienze Ed.8, 90128 Palermo, Italy.ORCID 0000-0002-4841-2560
University of Palermo · IT

Funding

Ricerca Finalizzata from the Italian Ministry of Health grant number GR-2011-02348129
6 · The paper itself

Abstract

The left ventricle (LV) constantly changes its shape and function as a response to pathological conditions, and this process is known as remodeling. In the presence of aortic stenosis (AS), the degenerative process is not limited to the aortic valve but also involves the remodeling of LV. Statistical shape analysis (SSA) offers a powerful tool for the visualization and quantification of the geometrical and functional patterns of any anatomic changes. In this paper, a SSA method was developed to determine shape descriptors of the LV under different degrees of AS and thus to shed light on the mechanistic link between shape and function. A total of n=86 patients underwent computed tomography (CT) for the evaluation of valvulopathy were segmented to obtain the LV surface and then were automatically aligned to a reference template by rigid registrations and transformations. Shape modes of the anatomical LV variation induced by the degree of AS were assessed by principal component analysis (PCA). The first shape mode represented nearly 50% of the total variance of LV shape in our patient population and was mainly associated to a spherical LV geometry. At Pearson's analysis, the first shape mode was positively correlated to both the end-diastolic volume (p<0.01, R=0.814) and end-systolic volume (p<0.01, and R=0.922), suggesting LV impairment in patients with severe AS. A predictive model built with PCA-related shape modes achieved better performance in stratifying the occurrence of adverse events with respect to a baseline model using clinical demographic data as risk predictors. This study demonstrated the potential of SSA approaches to detect the association of complex 3D shape features with functional LV parameters.

Indexed as

aortic valve stenosisleft ventriclestatistical shape analysis

Identifiers

PMID34068270
PMCPMC8153107
OpenAlexW3162326629

What OpenQuestion holds

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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.