Evidence map›Paper›PMID 33934528›Full record

ArticleESC heart failure2021

Easy-to-use preload stress echocardiography by using combined dynamic postural stress can identify high-risk patients with heart failure with reduced ejection fraction.

Nao Shibata, Kensuke Katsumoto, Ayu Shono, Makiko Suzuki, Keiko Sumimoto, Yusuke Tanaka, Kentaro Yamashita, Shun Yokota, Makiko Suto, Kumiko Dokuni and 2 more

Open access · goldAbstract read
In one paragraph

Article in ESC heart failure, 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
0.2field-weighted citation impact, top 50% 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, 1 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

12 authors at 1 institution in 1 country.

Nao ShibataDivision of Cardiovascular Medicine, Department of Internal Medicine, Kobe University Graduate School of Medicine, 7-5-2, Kusunoki-cho, Chuo-ku, Kobe, 650-0017, Japan.
Kensuke KatsumotoDivision of Cardiovascular Medicine, Department of Internal Medicine, Kobe University Graduate School of Medicine, 7-5-2, Kusunoki-cho, Chuo-ku, Kobe, 650-0017, Japan.ORCID 0000-0001-6764-6293
Ayu ShonoDivision of Cardiovascular Medicine, Department of Internal Medicine, Kobe University Graduate School of Medicine, 7-5-2, Kusunoki-cho, Chuo-ku, Kobe, 650-0017, Japan.
Makiko SuzukiDivision of Cardiovascular Medicine, Department of Internal Medicine, Kobe University Graduate School of Medicine, 7-5-2, Kusunoki-cho, Chuo-ku, Kobe, 650-0017, Japan.
Keiko SumimotoDivision of Cardiovascular Medicine, Department of Internal Medicine, Kobe University Graduate School of Medicine, 7-5-2, Kusunoki-cho, Chuo-ku, Kobe, 650-0017, Japan.
Yusuke TanakaDivision of Cardiovascular Medicine, Department of Internal Medicine, Kobe University Graduate School of Medicine, 7-5-2, Kusunoki-cho, Chuo-ku, Kobe, 650-0017, Japan.
Kentaro YamashitaDivision of Cardiovascular Medicine, Department of Internal Medicine, Kobe University Graduate School of Medicine, 7-5-2, Kusunoki-cho, Chuo-ku, Kobe, 650-0017, Japan.
Shun YokotaDivision of Cardiovascular Medicine, Department of Internal Medicine, Kobe University Graduate School of Medicine, 7-5-2, Kusunoki-cho, Chuo-ku, Kobe, 650-0017, Japan.
Makiko SutoDivision of Cardiovascular Medicine, Department of Internal Medicine, Kobe University Graduate School of Medicine, 7-5-2, Kusunoki-cho, Chuo-ku, Kobe, 650-0017, Japan.
Kumiko DokuniDivision of Cardiovascular Medicine, Department of Internal Medicine, Kobe University Graduate School of Medicine, 7-5-2, Kusunoki-cho, Chuo-ku, Kobe, 650-0017, Japan.
Hidekazu TanakaDivision of Cardiovascular Medicine, Department of Internal Medicine, Kobe University Graduate School of Medicine, 7-5-2, Kusunoki-cho, Chuo-ku, Kobe, 650-0017, Japan.
Ken-Ichi HirataDivision of Cardiovascular Medicine, Department of Internal Medicine, Kobe University Graduate School of Medicine, 7-5-2, Kusunoki-cho, Chuo-ku, Kobe, 650-0017, Japan.
Kobe University · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

aimsHaemodynamic assessment during stress testing is not commonly performed in patients with heart failure with reduced ejection fraction (HFrEF) because of its invasiveness, lower feasibility, and safety concerns. This study aimed to assess the haemodynamic characteristics of patients with HFrEF in response to non-invasive preload stress during dynamic postural alterations achieved by combining both semi-sitting position and passive leg-lifting and to evaluate whether combined postural stress could be used for risk stratification in these patients. METHODS AND

resultsFor this study, 101 patients with HFrEF and 35 age-matched and sex-matched healthy controls were prospectively recruited. After all standard echocardiographic measurements were obtained in the left decubitus position, all subjects underwent postural stress testing, which consisted of changing from semi-sitting position to passive leg-lifting. During a median follow-up period of 12.2 months, 21 (21%) patients developed adverse cardiovascular events. In patients without adverse cardiovascular events, the stroke volume index (SVi) significantly changed from 28 ± 8 to 35 ± 10 mL/m

conclusionsThe combined assessment of dynamic postural stress is a non-invasive, simple, quick, and easy-to-use clinical tool for assessing preload reserve and risk stratification in HFrEF patients.

Indexed as

Echocardiography, StressHeart FailureHumansPrognosisStroke VolumeVentricular Function, LeftHeart failure with reduced ejection fractionPassive leg-liftingPostural stressPreload reserveSemi-sitting positionStress echocardiography

Identifiers

PMID33934528
PMCPMC8318424
OpenAlexW3159039904

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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.