Evidence map›Paper›PMID 25875818›Full record

ArticlePloS one2015

A new 4D trajectory-based approach unveils abnormal LV revolution dynamics in hypertrophic cardiomyopathy.

Andrea Madeo, Paolo Piras, Federica Re, Stefano Gabriele, Paola Nardinocchi, Luciano Teresi, Concetta Torromeo, Claudia Chialastri, Michele Schiariti, Geltrude Giura and 5 more

Abstract read
In one paragraph

Article in PloS one, 2015. 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. Observational
  2. Article
  3. Article
  4. 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

15 authors.

Andrea MadeoDipartimento di Scienze Cardiovascolari, Respiratorie, Nefrologiche, Anestesiologiche e Geriatriche, Sapienza-Università di Roma, Rome, Italy; Centro per le Cardiomiopatie Ospedale S. Camillo-Forlanini, Roma, Italy.
Paolo PirasDipartimento di Scienze Cardiovascolari, Respiratorie, Nefrologiche, Anestesiologiche e Geriatriche, Sapienza-Università di Roma, Rome, Italy; Dipartimento di Scienze, Università Roma Tre, Rome, Italy; Center for Evolutionary Ecology, Rome, Italy; Dipartimento di Ingegneria Strutturale e Geotecnica, Sapienza-Università di Roma, Rome, Italy.
Federica ReCentro per le Cardiomiopatie Ospedale S. Camillo-Forlanini, Roma, Italy.
Stefano GabrieleDipartimento di Architettura, LaMS-Modeling & Simulation Lab, Università Roma Tre, Rome, Italy.
Paola NardinocchiDipartimento di Ingegneria Strutturale e Geotecnica, Sapienza-Università di Roma, Rome, Italy.
Luciano TeresiDipartimento di Matematica e Fisica, LaMS-Modeling & Simulation Lab, Università Roma Tre, Rome, Italy.
Concetta TorromeoDipartimento di Scienze Cardiovascolari, Respiratorie, Nefrologiche, Anestesiologiche e Geriatriche, Sapienza-Università di Roma, Rome, Italy.
Claudia ChialastriCentro per le Cardiomiopatie Ospedale S. Camillo-Forlanini, Roma, Italy.
Michele SchiaritiDipartimento di Scienze Cardiovascolari, Respiratorie, Nefrologiche, Anestesiologiche e Geriatriche, Sapienza-Università di Roma, Rome, Italy.
Geltrude GiuraDipartimento di Scienze Cardiovascolari, Respiratorie, Nefrologiche, Anestesiologiche e Geriatriche, Sapienza-Università di Roma, Rome, Italy.
Antonietta EvangelistaOspedale San Giovanni Calibita Fatebenefratelli-Isola Tiberina, Rome, Italy.
Tania DominiciDipartimento di Scienze Cardiovascolari, Respiratorie, Nefrologiche, Anestesiologiche e Geriatriche, Sapienza-Università di Roma, Rome, Italy.
Valerio VaranoDipartimento di Matematica e Fisica, LaMS-Modeling & Simulation Lab, Università Roma Tre, Rome, Italy.
Elisabetta ZacharaCentro per le Cardiomiopatie Ospedale S. Camillo-Forlanini, Roma, Italy.
Paolo Emilio PudduDipartimento di Scienze Cardiovascolari, Respiratorie, Nefrologiche, Anestesiologiche e Geriatriche, Sapienza-Università di Roma, Rome, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The assessment of left ventricular shape changes during cardiac revolution may be a new step in clinical cardiology to ease early diagnosis and treatment. To quantify these changes, only point registration was adopted and neither Generalized Procrustes Analysis nor Principal Component Analysis were applied as we did previously to study a group of healthy subjects. Here, we extend to patients affected by hypertrophic cardiomyopathy the original approach and preliminarily include genotype positive/phenotype negative individuals to explore the potential that incumbent pathology might also be detected. Using 3D Speckle Tracking Echocardiography, we recorded left ventricular shape of 48 healthy subjects, 24 patients affected by hypertrophic cardiomyopathy and 3 genotype positive/phenotype negative individuals. We then applied Generalized Procrustes Analysis and Principal Component Analysis and inter-individual differences were cleaned by Parallel Transport performed on the tangent space, along the horizontal geodesic, between the per-subject consensuses and the grand mean. Endocardial and epicardial layers were evaluated separately, different from many ecocardiographic applications. Under a common Principal Component Analysis, we then evaluated left ventricle morphological changes (at both layers) explained by first Principal Component scores. Trajectories' shape and orientation were investigated and contrasted. Logistic regression and Receiver Operating Characteristic curves were used to compare these morphometric indicators with traditional 3D Speckle Tracking Echocardiography global parameters. Geometric morphometrics indicators performed better than 3D Speckle Tracking Echocardiography global parameters in recognizing pathology both in systole and diastole. Genotype positive/phenotype negative individuals clustered with patients affected by hypertrophic cardiomyopathy during diastole, suggesting that incumbent pathology may indeed be foreseen by these methods. Left ventricle deformation in patients affected by hypertrophic cardiomyopathy compared to healthy subjects may be assessed by modern shape analysis better than by traditional 3D Speckle Tracking Echocardiography global parameters. Hypertrophic cardiomyopathy pathophysiology was unveiled in a new manner whereby also diastolic phase abnormalities are evident which is more difficult to investigate by traditional ecocardiographic techniques.

Indexed as

AdultCardiomyopathy, HypertrophicDiastoleEchocardiography, Three-DimensionalEndocardiumFemaleGenotypeHealthy VolunteersHeart VentriclesHumansMaleMiddle AgedPhenotypePrincipal Component AnalysisROC Curve

Identifiers

PMID25875818
PMCPMC4395437

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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.