Evidence map›Paper›PMID 38488337›Full record

ArticleESC heart failure2024

Optimal combination of right ventricular functional parameters using echocardiography in pulmonary arterial hypertension.

Qimou Li, Yu Zhang, Xiaopei Cui, Weida Lu, Qiushang Ji, Mei Zhang

Open access · goldAbstract read
In one paragraph

Article in ESC heart failure, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
5.4field-weighted citation impact, top 4% 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

10 citing papers in PubMed, 13 citations in OpenAlex.

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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

6 authors at 2 institutions in 2 countries.

Qimou LiNational Key Laboratory for Innovation and Transformation of Luobing Theory, Shandong University, Jinan, China.
Yu ZhangNational Key Laboratory for Innovation and Transformation of Luobing Theory, Shandong University, Jinan, China.
Xiaopei CuiDepartment of Geriatric Medicine and Shandong Key Laboratory Cardiovascular Proteomics, Qilu Hospital, Cheeloo College of Medicine, Shandong University, Jinan, China.
Weida LuDepartment of Geriatric Medicine and Shandong Key Laboratory Cardiovascular Proteomics, Qilu Hospital, Cheeloo College of Medicine, Shandong University, Jinan, China.
Qiushang JiNational Key Laboratory for Innovation and Transformation of Luobing Theory, Shandong University, Jinan, China.
Mei ZhangNational Key Laboratory for Innovation and Transformation of Luobing Theory, Shandong University, Jinan, China.ORCID https://orcid.org/0000-0001-6295-5070
Shandong University · CNQilu Hospital of Shandong University · CN

Funding

National Natural Science Foundation of China 82170419
6 · The paper itself

Abstract

aimsNovel echocardiographic parameters of right ventricular (RV) function, including speckle-tracking-derived, three-dimensional, and RV-pulmonary artery coupling parameters, have emerged for the evaluation of pulmonary arterial hypertension (PAH). The relative role of these parameters in the risk stratification of PAH patients is unclear. We compared the performance of multiple RV parameters and sought to establish an optimal model for identifying the risk profile of patients with PAH. METHODS AND

resultsComprehensive risk assessments were performed for 70 patients with PAH. The risk profile of every patient was determined based on the guideline recommendations. Conventional parameters, including fractional area change (FAC) and tricuspid annular plane systolic excursion (TAPSE), novel speckle-tracking-derived RV longitudinal strain (RVLS), and three-dimensional RV ejection fraction (3D-RVEF), were used to evaluate RV function. Pressure-strain loops were measured for the assessment of RV myocardial work, including RV global wasted work (RVGWW). RV-pulmonary artery coupling was assessed by indexing RV parameters to the estimated pulmonary artery systolic pressure (PASP). The median age was 34 (30-43) years, and 62 (88.6%) patients were female. Forty-five patients were classified into the low-risk group, while 25 patients were classified into the intermediate-high-risk group. Most RV parameters could be used to determine the risk profile and exhibited significantly improved diagnostic performance after indexing to PASP (including FAC/PASP, TAPSE/PASP, and 3D-RVEF/PASP). RVLS/PASP showed the best performance, with an area under the curve of 0.895. In multivariate analysis (Model 1), only RVGWW (>90.5 mmHg%), RVLS (> -16.7%), and TAPSE (<17.5 mm) remained significant (all P < 0.05). Model 1 outperformed every single RV parameter, with a significantly larger area under the curve (all P < 0.05). With PASP indexing in Model 2, RVLS/PASP > -0.275 [odds ratio (OR) 20.63, 95% confidence interval (CI) 4.62-92.11, P < 0.001] and RVGWW > 90.5 mmHg% (OR 6.17, 95% CI 1.37-27.76, P = 0.018) independently identified a higher risk profile. The addition of RVGWW to two models determined incremental value in identification (continuous net reclassification improvement 1.058, 95% CI 0.639-1.477, P < 0.001).

conclusionsThe combination models for RV function outperformed any single parameter in identifying the risk profile of patients with PAH. Comprehensive assessment of RV-pulmonary artery coupling using multiparametric methods is clinically meaningful in patients with PAH.

Indexed as

Heart VentriclesVentricular Function, RightAdultEchocardiographyEchocardiography, Three-DimensionalFemaleHumansMaleMiddle AgedPulmonary Arterial HypertensionPulmonary ArteryRetrospective StudiesRisk AssessmentStroke VolumeVentricular Dysfunction, RightPulmonary arterial hypertensionRight ventricular dysfunctionRight ventricular–pulmonary artery couplingRisk stratificationSpeckle‐tracking echocardiography

Identifiers

PMID38488337
PMCPMC11424360
OpenAlexW4392882937

What OpenQuestion holds

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LicenceCC BY-NC
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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.