Evidence map›Paper›PMID 33586008›Full record

ArticleHeart and vessels2021

Impact of the Trifecta bioprosthetic valve in patients with low-flow severe aortic stenosis.

Tohru Takaseya, Atsunobu Oryoji, Kazuyoshi Takagi, Tomofumi Fukuda, Koichi Arinaga, Shinichi Hiromatsu, Eiki Tayama

Open access · hybridAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Heart and vessels, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.5field-weighted citation impact, top 36% 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

1 citing paper in PubMed, 3 citations in OpenAlex.

  1. 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

7 authors at 1 institution in 1 country.

Tohru TakaseyaDepartment of Surgery, Kurume University, Asahi-machi 67, Kurume-shi, Fukuoka, Japan. ttakaseya@med.kurume-u.ac.jp.
Atsunobu OryojiDepartment of Surgery, Kurume University, Asahi-machi 67, Kurume-shi, Fukuoka, Japan.
Kazuyoshi TakagiDepartment of Surgery, Kurume University, Asahi-machi 67, Kurume-shi, Fukuoka, Japan.
Tomofumi FukudaDepartment of Surgery, Kurume University, Asahi-machi 67, Kurume-shi, Fukuoka, Japan.
Koichi ArinagaDepartment of Surgery, Kurume University, Asahi-machi 67, Kurume-shi, Fukuoka, Japan.
Shinichi HiromatsuDepartment of Surgery, Kurume University, Asahi-machi 67, Kurume-shi, Fukuoka, Japan.
Eiki TayamaDepartment of Surgery, Kurume University, Asahi-machi 67, Kurume-shi, Fukuoka, Japan.
Kurume University · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Aortic stenosis (AS) is the most common valve disorder in advanced age. Previous reports have shown that low-flow status of the left ventricle is an independent predictor of cardiovascular mortality after surgery. The Trifecta bioprosthesis has recently shown favorable hemodynamic performance. This study aimed to evaluate the effect of the Trifecta bioprosthesis, which has a large effective orifice area, in patients with low-flow severe AS who have a poor prognosis. We retrospectively evaluated 94 consecutive patients with severe AS who underwent aortic valve replacement (AVR). Patients were divided into two groups according to the stroke volume index (SVI): low-flow (LF) group (SVI < 35 ml/m

Indexed as

Aortic Valve StenosisBioprosthesisHeart Valve ProsthesisHeart Valve Prosthesis ImplantationAortic ValveHemodynamicsHumansProsthesis DesignRetrospective StudiesTreatment OutcomeAortic valve replacementLeft ventricular dysfunctionPatient-prosthesis mismatchTrifecta bioprosthesis

Identifiers

PMID33586008
PMCPMC8260398
OpenAlexW3132907949

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.