Observational studyBMJ open2025
Predictive value of novel inflammatory markers combined with GRACE score for in-hospital outcome in patients with ST-segment elevation myocardial infarction: a retrospective observational study.
Observational study in BMJ open, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
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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.
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.
Who cites it
7 citing papers in PubMed.
- Early Inflammatory Biomarkers, Ventricular Dysfunction and In-Hospital Mortality in Patients with ST-Elevation Myocardial Infarction Undergoing Primary Percutaneous Coronary Intervention.Diagnostics (Basel, Switzerland) · 2026Article
- Age-Dependent Inflammatory, Lipid, and Echocardiographic Phenotypes in Acute Myocardial Infarction: Associations with In-Hospital Adverse Clinical Events.Biomedicines · 2026Article
- The AHEAD-NLR score: a novel inflammatory-comorbidity integrated tool for predicting long-term mortality in patients with heart failure after acute myocardial infarction.Scientific reports · 2026Article
- Machine learning redevelopment of GRACE, ACEF, and TIMI scores for 6-month mortality.Frontiers in artificial intelligence · 2026Article
- The Role of Fast Blood Glucose to Albumin Ratio in Predicting Gout Relief Among Patients With Acute Gout Attack.International journal of endocrinology · 2026Article
- Cross-Talk Between Neutrophils and Macrophages Post-Myocardial Infarction: From Inflammatory Drivers to Therapeutic Targets.International journal of molecular sciences · 2025Review
- Machine Learning Approach on Predictive Model Establishment for In-Hospital Mortality in Acute Myocardial Infarction Patients Post-Percutaneous Coronary Intervention: Solutions for Databases With Dimensionality Reduction and Class Imbalance.Reviews in cardiovascular medicine · 2025Article
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectivesTo assess the prognostic efficacy of innovative inflammatory indicators, specifically the neutrophil-to-lymphocyte ratio (NLR) and the platelet-to-lymphocyte ratio (PLR), in conjunction with the Global Registry of Acute Coronary Events (GRACE) score, for predicting adverse in-hospital outcomes among patients diagnosed with ST-segment elevation myocardial infarction (STEMI). DESIGN AND
settingThis study is a single-centre retrospective analysis of patients with STEMI treated at the Cardiology Department of Tianjin Third Central Hospital between 1 January 2018 and 31 December 2023. All data were sourced from the hospital's medical record system. OUTCOME MEASURES: The integration of the GRACE score with NLR and PLR facilitated the creation of an innovative predictive model. The model's predictive efficacy for in-hospital major adverse cardiovascular event (MACE) occurrence was assessed through receiver operating characteristic (ROC) curve analysis and multivariate logistic regression. Additionally, the Net Reclassification Improvement and Integrated Discrimination Improvement were computed to quantify enhancements in predictive value.
resultsPatients were stratified into the MACE (N=167) and the non-MACE group (N=1011) based on the incidence of MACE. A comparison of baseline characteristics between the two groups revealed 13 potential confounding variables. The NLR and PLR levels were converted into binary variables using ROC curve analysis. Univariate logistic regression indicated that both NLR and PLR were significant risk factors for MACE during hospitalisation. After adjusting for confounders, multivariate logistic regression confirmed NLR as an independent predictor of MACE risk in this cohort. Furthermore, both NLR and PLR augmented the predictive accuracy of the GRACE score, with their combined use offering a significant improvement in its predictive capacity.
conclusionsThe NLR possesses the capability to independently forecast the risk of MACE during the hospitalisation period for patients diagnosed with STEMI. The incorporation of the PLR and NLR with the GRACE score serves to augment its predictive precision.
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