Evidence map›Paper›PMID 38946662›Full record

ArticleESC heart failure2024

Integration of two-dimensional echocardiography: A novel risk indicator for ST-segment elevation myocardial infarction.

Hongli Gao, Kai Wang, Xinyi Wang, Deli Zeng, Zijun Chen

Abstract 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 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

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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

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

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4 · The record

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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

5 authors.

Hongli GaoDepartment of Cardiology, The Affiliated Yongchuan Hospital of Chongqing Medical University, Chongqing, China.
Kai WangDepartment of Cardiology, The Affiliated Yongchuan Hospital of Chongqing Medical University, Chongqing, China.ORCID 0000-0001-9052-1691
Xinyi WangDepartment of Cardiology, The Affiliated Yongchuan Hospital of Chongqing Medical University, Chongqing, China.
Deli ZengDepartment of Cardiology, The Affiliated Yongchuan Hospital of Chongqing Medical University, Chongqing, China.
Zijun ChenDepartment of Cardiology, The Affiliated Yongchuan Hospital of Chongqing Medical University, Chongqing, China.ORCID 0000-0001-9442-4936

Funding

Science and Technology Bureau of Yongchuan, Chongqing 2022yc-jckx20005
6 · The paper itself

Abstract

aimsWe aim to integrate the parameters of two-dimensional (2D) echocardiography and identify the high-risk population for all-cause mortality in patients with acute ST-segment elevation myocardial infarction (STEMI) undergoing percutaneous coronary intervention (PCI).

methodsThe study involved a retrospective cohort population with STEMI who were admitted to Yongchuan Hospital of Chongqing Medical University between January 2016 and January 2019. Baseline data were collected, including 2D echocardiography parameters and left ventricular ejection fraction (LVEF). The parameters of 2D echocardiography were subjected to cluster analysis. Logistic regression models were employed to assess univariate and multivariate adjusted odds ratios (ORs) of cluster information in relation to all-cause mortality. Four logistic regression models were generated, utilizing cluster information, clinical variables, clinical variables in conjunction with LVEF, and clinical variables in conjunction with LVEF and cluster information as predictive variables, respectively. The area under the curve (AUC) were utilized to evaluate the incremental risk stratification value of cluster information.

resultsThe study included 633 participants with 28.8% female, a mean age of 65.68 ± 11.98 years. Over the course of a 3-year follow-up period, 108 (17.1%) patients experienced all-cause mortality. Utilizing cluster analysis of 2D echocardiography parameters, the patients were categorized into two distinct clusters, with statistically significant differences observed in most clinical variables, echocardiography, and survival outcomes between the clusters. Multivariate regression analysis revealed that cluster information was independently associated with the risk of all-cause mortality with adjusted OR 7.33 (95% confidence interval [CI] 3.99-14.06, P < 0.001). The inclusion of LVEF enhanced the predictive capacity of the model utilized with clinical variables with AUC 0.848 (95% CI 0.809-0.888) versus AUC 0.872 (95% CI 0.836-0.908) (P < 0.001), and the addition of cluster information further improved its predictive performance with AUC 0.906 (95% CI 0.878-0.934, P < 0.001). This cluster analysis was translated into a free available online calculator (https://app-for-mortality-prediction-cluster.streamlit.app/).

conclusionsThe 2D echocardiographic diagnostic information based on cluster analysis had good prognostic value for STEMI population, which was helpful for risk stratification and individualized intervention.

Indexed as

EchocardiographyPercutaneous Coronary InterventionST Elevation Myocardial InfarctionVentricular Function, LeftAgedCause of DeathChinaFemaleFollow-Up StudiesHumansMaleMiddle AgedPrognosisRetrospective StudiesRisk AssessmentRisk FactorsCluster analysisEchocardiographyMyocardial infarctionRisk stratification

Identifiers

PMID38946662
PMCPMC11424358

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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.