Evidence map›Paper›PMID 24105865›Full record

ArticleInteractive cardiovascular and thoracic surgery2014

Left ventricular mass regression after sutureless implantation of the Perceval S aortic valve bioprosthesis: preliminary results.

Giuseppe Santarpino, Steffen Pfeiffer, Francesco Pollari, Giovanni Concistrè, Ferdinand Vogt, Theodor Fischlein

Abstract read
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Article in Interactive cardiovascular and thoracic surgery, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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

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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

5 citing papers in PubMed.

  1. Article
  2. Article
  3. Benefits and Pitfalls of the Perceval Sutureless Bioprosthesis.Frontiers in cardiovascular medicine · 2021
    Review
  4. Early results of the SorinJournal of thoracic disease · 2017
    Article
  5. 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.

Giuseppe SantarpinoDepartment of Cardiac Surgery, Klinikum Nürnberg, Nuremberg, Germany.
Steffen Pfeiffer
Francesco Pollari
Giovanni Concistrè
Ferdinand Vogt
Theodor Fischlein

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesLeft ventricular (LV) hypertrophy in aortic stenosis (AS) is considered a compensatory response helping maintain systolic function, but constitutes a risk factor for cardiac morbidity and mortality. The aim of this study was to assess the degree of LV mass regression after sutureless implantation of the Perceval S aortic valve bioprosthesis (Sorin Group, Saluggia, Italy).

methodsBetween March 2010 and July 2012, 78 patients with symptomatic AS underwent isolated aortic valve replacement (AVR) with the Perceval bioprosthesis. Mean age was 77.1 ± 5.3 years, 46 patients were female (59%) and mean logistic EuroSCORE was 11 ± 7.5%. Echocardiography was performed preoperatively, at discharge, and at follow-up (mean 13.5 ± 7.3 months). LV mass was calculated using the Devereux formula and indexed to body surface area.

resultsThere was 1 in-hospital non-cardiac death and 3 late deaths. LV mass index decreased from 148.4 ± 46 g/m(2) at baseline to 119.7 ± 38.5 g/m(2) at follow-up (P = 0.002). No significant changes were observed in LV hypertrophy and/or relative wall thickness >0.42 as well as in LV ejection fraction. Mean aortic gradient decreased from 49.5 ± 15.8 mmHg at baseline to 11.6 ± 5.1 mmHg at discharge and 8.3 ± 4.4 mmHg at follow-up (P < 0.001), resulting in significant clinical improvement. No moderate or severe paravalvular leakage was observed at discharge and at follow-up.

conclusionsIn AS patients, isolated AVR with the Perceval sutureless bioprosthesis is associated with significant LV mass regression at 1-year follow-up. However, longer-term follow-up is necessary to confirm these findings.

Indexed as

BioprosthesisHeart Valve ProsthesisVentricular Function, LeftVentricular RemodelingAgedAged, 80 and overAortic ValveAortic Valve StenosisEchocardiography, DopplerFemaleHeart Valve Prosthesis ImplantationHemodynamicsHospital MortalityHumansHypertrophy, Left VentricularMaleAortic valve replacementEchocardiographyHeart valve bioprosthesisLeft ventricleRight ventricle

Identifiers

PMID24105865
PMCPMC3867027

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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.