Evidence map›Paper›PMID 40718768›Full record

ArticlePeerJ2025

Combining echocardiography with carotid ultrasound parameters in predicting major adverse cardiovascular events among older individuals with coronary artery disease.

Tianli Jia, Xiaoxiao Li, Qianqian Xie

Abstract read
In one paragraph

Article in PeerJ, 2025. 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
–field-weighted citation impact
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. 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

3 authors.

Tianli Jia *Department of Ultrasound Medicine, Yantai Yuhuangding Hospital, Yantai, Shandong, China.
Xiaoxiao Li *Department of Ultrasound Medicine, Yantai Yuhuangding Hospital, Yantai, Shandong, China.
Qianqian XieDepartment of Ultrasound Medicine, Yantai Yuhuangding Hospital, Yantai, Shandong, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: To investigate the predictive value of combining echocardiography with carotid ultrasound for major adverse cardiovascular events (MACE) among older individuals with coronary artery disease. Methods: A total of 138 elderly individuals diagnosed with coronary artery disease and admitted to our facility from June 2020 to June 2021 were included in this study. These patients were categorized into two groups: a non-MACE group consisting of 84 patients and a MACE group with 54 patients, based on whether they experienced MACE within three years following their discharge. Additionally, a validation cohort of 141 patients was assembled, which was also divided into a non-MACE group with 90 patients and a MACE group with 51 patients. Upon admission, all participants underwent both transthoracic echocardiography and carotid ultrasound assessments. We then conducted a comparative analysis of the ultrasound parameters between the two groups. Results: The MACE group had higher left ventricular end-diastolic diameter (LVEDD), carotid intima-media thickness (IMT), and Crouse score, and lower left ventricular ejection fraction (LVEF) and A-wave velocity (all Conclusion: Echocardiography and carotid ultrasound parameters can be used to predict the occurrence of MACE within 3 years in elderly patients with coronary artery disease, and combined detection can effectively improve the accuracy of prediction.

Indexed as

Carotid ArteriesCarotid Intima-Media ThicknessCoronary Artery DiseaseEchocardiographyAgedAged, 80 and overFemaleHumansMalePredictive Value of TestsRisk FactorsUltrasonographyUltrasonography, Carotid ArteriesCarotid artery ultrasoundCoronary artery diseaseEchocardiographyElderlyMajor adverse cardiovascular eventsPredictive value

Identifiers

PMID40718768
PMCPMC12296572

What OpenQuestion holds

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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.