Evidence map›Paper›PMID 34993075›Full record

ArticleQuantitative imaging in medicine and surgery2022

Application value of myocardial work technology by non-invasive echocardiography in evaluating left ventricular function in patients with chronic heart failure.

Yanan Li, Qiang Zheng, Cunying Cui, Yuanyuan Liu, Yanbin Hu, Danqing Huang, Ying Wang, Jun Liu, Lin Liu

Open access · diamondAbstract read
In one paragraph

Article in Quantitative imaging in medicine and surgery, 2022. 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
1.7field-weighted citation impact, top 14% 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

5 citing papers in PubMed, 11 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

9 authors at 3 institutions in 1 country.

Yanan LiDepartment of Ultrasound, Henan Province People's Hospital, Fuwai Central China Cardiovascular Hospital, People's Hospital of Zhengzhou University, Zhengzhou, China.
Qiang Zheng *School of Computer and Control Engineering, Yantai University, Yantai, China.
Cunying CuiDepartment of Ultrasound, Henan Province People's Hospital, Fuwai Central China Cardiovascular Hospital, People's Hospital of Zhengzhou University, Zhengzhou, China.
Yuanyuan LiuDepartment of Ultrasound, Henan Province People's Hospital, Fuwai Central China Cardiovascular Hospital, People's Hospital of Zhengzhou University, Zhengzhou, China.
Yanbin HuDepartment of Ultrasound, Henan Province People's Hospital, Fuwai Central China Cardiovascular Hospital, People's Hospital of Zhengzhou University, Zhengzhou, China.
Danqing HuangDepartment of Ultrasound, Henan Province People's Hospital, Fuwai Central China Cardiovascular Hospital, People's Hospital of Zhengzhou University, Zhengzhou, China.
Ying WangDepartment of Ultrasound, Henan Province People's Hospital, Fuwai Central China Cardiovascular Hospital, People's Hospital of Zhengzhou University, Zhengzhou, China.
Jun LiuDepartment of Cardiology, Henan Province People's Hospital, Fuwai Central China Cardiovascular Hospital, People's Hospital of Zhengzhou University, Zhengzhou, China.
Lin Liu *Department of Ultrasound, Henan Province People's Hospital, Fuwai Central China Cardiovascular Hospital, People's Hospital of Zhengzhou University, Zhengzhou, China.
Zhengzhou University · CNZhengzhou People's Hospital · CNYantai University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAccurate evaluation of left ventricular (LV) systolic function is the premise for diagnosing and treating chronic heart failure. This study aimed to explore the incremental value of echocardiographic myocardial work in evaluating the LV systolic dysfunction in patients with chronic heart failure.

methodsA total of 206 participants were enrolled, including 155 patients with chronic heart failure and 51 healthy controls (HC). The chronic heart failure patients were divided into three groups according to LV ejection fraction (LVEF): Heart failure with preserved ejection fraction (HFpEF group, 54 cases, LVEF ≥50%), heart failure with mid-range ejection fraction (HFmrEF group, 50 cases, 40%≤ LVEF <50%), and heart failure with reduced ejection fraction (HFrEF group, 51 cases, LVEF <40%). Except for the conventional echocardiographic parameters, the left ventricular myocardial work parameters, including the global myocardial work index (GWI), global constructive work (GCW), global wasted work (GWW), and global work efficiency (GWE), were calculated in the study participants. One-way analysis of variance test followed by Fisher's least significant difference (LSD)

resultsAll conventional echocardiographic parameters were significantly different between the HFmrEF and HFrEF groups, but only E/e', left atrium showed notable differences between the HFpEF and HC groups (P<0.05). All myocardial work parameters were markedly different between the four groups (P<0.05). LVEF and GWI were more important than the other parameters according to the multi-classification machine learning model. The multi-classification diagnostic performances of LVEF, GWI, and LVEF + GWI were 82%, 88%, and 98%, respectively, which confirmed that GWI + LVEF could complementarily improve the diagnosis accuracy in classifying the four groups, with a performance increase of approximately 10% than each individually.

conclusionsGWI can play a complementary role to LVEF in the early diagnosis of HFpEF patients from the HC group and improve the clinical evaluation accuracy in chronic heart failure patients. Echocardiographic myocardial work should be utilized along with conventional LVEF to evaluate the systolic function of chronic heart failure patients in clinical practice.

Indexed as

chronic heart failure (CHF)Echocardiographyleft ventricular functionmyocardial work

Identifiers

PMID34993075
PMCPMC8666727
OpenAlexW3191951475

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Registered trials

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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.