Evidence map›Paper›PMID 40219555›Full record

ArticleBeijing da xue xue bao. Yi xue ban = Journal of Peking University. Health sciences2025

[Predictive value of coronary microcirculation dysfunction after revascularization in patients with acute myocardial infarction for acute heart failure during hospitalization].

Lan Wang, Yuliang Ma, Weimin Wang, Tiangang Zhu, Wenying Jin, Hong Zhao, Chengfu Cao, Jing Wang, Bailin Jiang

Abstract readEnglish Abstract
In one paragraph

Article in Beijing da xue xue bao. Yi xue ban = Journal of Peking University. Health sciences, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Lan WangDepartment of Cardiology, Peking University People' s Hospital, Beijing Key Laboratory of Early Prediction and Intervention of Acute Myocardial Infarction, Center for Cardiovascular Translational Research, Beijing 100044, China.
Yuliang MaDepartment of Cardiology, Peking University People' s Hospital, Beijing Key Laboratory of Early Prediction and Intervention of Acute Myocardial Infarction, Center for Cardiovascular Translational Research, Beijing 100044, China.
Weimin WangDepartment of Cardiology, Peking University People' s Hospital, Beijing Key Laboratory of Early Prediction and Intervention of Acute Myocardial Infarction, Center for Cardiovascular Translational Research, Beijing 100044, China.
Tiangang ZhuDepartment of Cardiology, Peking University People' s Hospital, Beijing Key Laboratory of Early Prediction and Intervention of Acute Myocardial Infarction, Center for Cardiovascular Translational Research, Beijing 100044, China.
Wenying JinDepartment of Cardiology, Peking University People' s Hospital, Beijing Key Laboratory of Early Prediction and Intervention of Acute Myocardial Infarction, Center for Cardiovascular Translational Research, Beijing 100044, China.
Hong ZhaoDepartment of Cardiology, Peking University People' s Hospital, Beijing Key Laboratory of Early Prediction and Intervention of Acute Myocardial Infarction, Center for Cardiovascular Translational Research, Beijing 100044, China.
Chengfu CaoDepartment of Cardiology, Peking University People' s Hospital, Beijing Key Laboratory of Early Prediction and Intervention of Acute Myocardial Infarction, Center for Cardiovascular Translational Research, Beijing 100044, China.
Jing WangDepartment of Cardiology, Peking University People' s Hospital, Beijing Key Laboratory of Early Prediction and Intervention of Acute Myocardial Infarction, Center for Cardiovascular Translational Research, Beijing 100044, China.
Bailin JiangDepartment of Anesthesiology, Peking University People' s Hospital, Beijing 100044, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo study incident and clinical characteristics of the coronary microcirculation dysfunction (CMD) in patients with acute myocardial infarction (AMI) after percutaneous coronary intervention (PCI) by myocardial contrast echocardiography (MCE) and to explore the predictive value of CMD for in-hospital acute heart failure event.

methodsOne hundred and forty five patients with AMI who had received PCI and completed MCE during hospitalization in Peking University People' s Hospital from November 2015 to July 2021 were enrolled in our study. The patients were divided into CMD group and normal group according to the coronary microcirculation status detected by MCE. Clinical data and MCE data of the two groups were collected and analyzed. The acute heart failure event during hospitalization was described. A multivariate Logistic regression model was built to analyze the risk of acute heart failure in patients with CMD. A receiver operating characteristic (ROC) curve was drawn to evaluate the value of CMD in predicting acute heart failure event.

resultsCMD detected by MCE occurred in 87 patients (60%). Compared with normal group, patients with CMD had higher troponin I (TnI) peak level [52.8 (8.1, 84.0) μg/L

conclusionThe incidence of CMD detected by MCE in patients with AMI post-PCI was 60%. Patients with CMD have a higher risk of acute left heart failure during hospitalization.

Indexed as

Coronary CirculationHeart FailureMicrocirculationMyocardial InfarctionPercutaneous Coronary InterventionAgedEchocardiographyFemaleHospitalizationHumansMaleMiddle AgedPredictive Value of TestsTroponin ITroponin ICoronary microcirculation dysfunctionHeart failureMyocardial contrast echocardiographyMyocardial infarction

Identifiers

PMID40219555
PMCPMC11992466

What OpenQuestion holds

Textmetadata
Read underepoch 390

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.