Evidence map›Paper›PMID 39895550›Full record

Observational studyJournal of the American Heart Association2025

Development and Validation of Risk Stratification for Heart Failure After Acute Coronary Syndrome Based on Dynamic S100A8/A9 Levels.

Jie Ma, Ke Ma, Jing Chen, Xinying Yang, Fei Gao, Hai Gao, Hui Zhang, Xin-Liang Ma, Jie Du, Ping Li and 1 more

Registry-linked trialAbstract readMulticenter StudyObservational StudyValidation Study
In one paragraph

Observational study in Journal of the American Heart Association, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT03752515 (A Chinese Registry to Determine the Genetics Risk Factors and Serumal Biomarkers for Acute Coronary Syndrome), which is not on this map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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.

NCT03752515 unknown statusnot on this map

A Chinese Registry to Determine the Genetics Risk Factors and Serumal Biomarkers for Acute Coronary Syndrome

TypeobservationalSponsorBeijing Institute of Heart, Lung and Blood Vessel DiseasesRan2015 to 2025Enrolled2,000ConditionsCoronary Artery Disease, Acute Coronary Syndrome, Acute Myocardial Infarction, Unstable Angina
3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Research Progress of BMAL1 in Heart Failure.Journal of the American Heart Association · 2025
    Review
  4. 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

11 authors.

Jie MaBeijing Anzhen Hospital of Capital Medical University Beijing China.ORCID 0000-0002-8999-3832
Ke MaBeijing Anzhen Hospital of Capital Medical University Beijing China.ORCID 0000-0001-6768-1259
Jing ChenBeijing Anzhen Hospital of Capital Medical University Beijing China.ORCID 0000-0002-0172-0873
Xinying YangBeijing Anzhen Hospital of Capital Medical University Beijing China.
Fei GaoBeijing Anzhen Hospital of Capital Medical University Beijing China.
Hai GaoBeijing Anzhen Hospital of Capital Medical University Beijing China.
Hui ZhangDepartment of Preventive Medicine, Feinberg School of Medicine Northwestern University Chicago IL USA.ORCID 0000-0001-6825-5649
Xin-Liang MaDepartment of Emergency Medicine Thomas Jefferson University Philadelphia PA USA.ORCID 0000-0002-9041-0876
Jie DuBeijing Anzhen Hospital of Capital Medical University Beijing China.
Ping LiBeijing Anzhen Hospital of Capital Medical University Beijing China.
Yulin LiBeijing Anzhen Hospital of Capital Medical University Beijing China.ORCID 0000-0001-7909-0763

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe early assessment of heart failure (HF) risk in patients with acute coronary syndrome (ACS) can help reduce mortality. S100A8/A9 is not only rapidly released after myocardial ischemia, but is also involved in reperfusion injury, which is an important predictor of HF after ACS. We attempted to construct a reliable HF risk stratification tool for evaluating patients with ACS after reperfusion therapy based on S100A8/A9 dynamic changes. METHODS AND

resultsThis prospective study included 3 independent cohorts of patients with ACS who received reperfusion therapy. The discovery cohort was divided into 2 subgroups: the longitudinal subgroup (n=264) with serum S100A8/A9 levels measured at admission and on days 1, 2, 3, and 4 postadmission, respectively, and the 2-point subgroup (n=798) with S100A8/A9 levels measured at admission and on day 1 postadmission, respectively. Validation cohorts 1 (n=1399) and 2 (n=1183) both had S100A8/A9 levels measured on day 1 postadmission. HF events included in-hospital HF events after the initial presentation and long-term HF events after discharge. The median follow-up for the discovery cohort, validation cohort 1, and validation cohort 2 was 4.2, 2.6, and 1.8 years, respectively. In the discovery cohort, S100A8/A9's predictive ability at day 1 surpassed other time points. Through the S100A8/A9-guided risk stratification, patients deemed high risk (>7900 ng/mL) exhibited a higher 1-year HF event rate (46% versus 2%, 38% versus 5%) than patients at low risk (<2100 ng/mL) in both validation cohorts. Among patients without left ventricular dysfunction after ACS, β-blocker therapy correlated with reduced 1-year HF events in intermediate-to- high-risk patients but not in low-risk patients.

conclusionsS100A8/A9 levels on day 1 accurately classified patients at varying risks of HF, serving as a robust tool for HF risk prediction and treatment guidance. REGISTRATION: URL: https://www.clinicaltrials.gov; Unique identifier: NCT03752515.

Indexed as

Acute Coronary SyndromeCalgranulin ACalgranulin BHeart FailureAgedBiomarkersFemaleHumansMaleMiddle AgedPredictive Value of TestsPrognosisProspective StudiesReproducibility of ResultsRisk AssessmentRisk FactorsBiomarkersCalgranulin ACalgranulin BS100A8 protein, humanS100A9 protein, humanacute coronary syndromeheart failureS100A8/A9β‐blocker

Identifiers

PMID39895550
PMCPMC12074705

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Registered trials

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.