Evidence map›Paper›PMID 39701981›Full record

ArticleBMC cardiovascular disorders2024

Prediction of major adverse cardiovascular events following acute myocardial infarction using electrocardiogram DETERMINE score.

Zeyan Liu, Jinglin Cheng, Shu Zhou, Xuexiang Li, Min Yang, Ye Zhang

Abstract readValidation Study
In one paragraph

Article in BMC cardiovascular disorders, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed, 1 pooled it
–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

3 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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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

6 authors.

Zeyan LiuDepartment of Emergency Internal Medicine, Second Affiliated Hospital of Anhui Medical University, Hefei, China. jy02893741@163.com.
Jinglin ChengDepartment of Emergency Internal Medicine, Second Affiliated Hospital of Anhui Medical University, Hefei, China.
Shu ZhouDepartment of Emergency Internal Medicine, Second Affiliated Hospital of Anhui Medical University, Hefei, China.
Xuexiang LiDepartment of Emergency Internal Medicine, Second Affiliated Hospital of Anhui Medical University, Hefei, China.
Min YangDepartment of Intensive Care Unit II, Second Affiliated Hospital of Anhui Medical University, Hefei, China. yangmin@ahmu.edu.cn.
Ye ZhangDepartment of Anesthesiology and Perioperative Medicine, Second Affiliated Hospital of Anhui Medical University, Hefei, China. zhangye_hassan@sina.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAcute myocardial infarction (AMI) remains a major cause of mortality and morbidity globally, with a high incidence of major adverse cardiovascular events (MACE) post-primary percutaneous coronary intervention (PPCI). The DETERMINE score, derived from electrocardiographic (ECG) markers, has shown promise as a predictor of adverse outcomes, but its clinical utility requires further validation.

objectiveTo evaluate the predictive value of the DETERMINE score for MACE and provide early clinical warnings for high-risk patients.

methodsThis bidirectional cohort study included AMI patients from the Second Affiliated Hospital of Anhui Medical University between 2019 and 2023. The training cohort comprised 545 patients between January 2019 and January 2023, while the validation cohort consisted of 122 patients between February 2023 and July 2023. The primary endpoint was MACE within one-year post-PPCI. The relationship between the DETERMINE score and MACE was analyzed using Cox regression, trend tests, and restricted cubic splines to assess linear and nonlinear associations. Patients were stratified into risk groups based on tertiles or optimal cutoffs, and Kaplan-Meier survival curves compared MACE incidence across groups. Predictive accuracy was evaluated through time-dependent C-index, ROC curves, decision curve analysis, and calibration, and compared to other prognostic scores, including the Selvester, GRACE, and SYNTAX scores, as well as left ventricular ejection fraction (LVEF). Subgroup analyses by sex, age, and culprit artery involvement were also conducted.

resultsCox multivariate regression indicated that the DETERMINE score was an independent risk factor for MACE (HR = 1.56, 95% CI 1.38-1.75, P < 0.001). Trend test and RCS showed a positive correlation and non-linear relationship between the DETERMINE score and MACE (P-trend < 0.001, P-overall < 0.001, P-nonlinear: 0.003). Kaplan-Meier survival analysis revealed that, in both the training and validation datasets, groups with a higher DETERMINE score showed a higher cumulative risk of MACE. The DETERMINE score outperformed traditional prognostic scores (Selvester, GRACE, SYNTAX) in terms of predictive accuracy, with an AUROC of 0.840 at 12 months in the training cohort. The score also provided a substantial clinical net benefit, particularly over longer follow-up periods. Subgroup analyses confirmed its predictive power across different demographics and clinical presentations.

conclusionThe DETERMINE score has outstanding predictive power for MACE post-PPCI, which can guide the early identification of high-risk patients with poor prognosis of AMI in clinical practice.

Indexed as

ElectrocardiographyMyocardial InfarctionPercutaneous Coronary InterventionPredictive Value of TestsAgedChinaDecision Support TechniquesFemaleHumansIncidenceMaleMiddle AgedPrognosisReproducibility of ResultsRisk AssessmentRisk FactorsAcute myocardial infarctionDETERMINE scoreMajor adverse cardiovascular events

Identifiers

PMID39701981
PMCPMC11658445

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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.