ArticleBMC cardiovascular disorders2024
Shock index creatinine: a new predictor of mortality in acute coronary syndrome patients.
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 6 papers, 1 of them a synthesis that pooled it.
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Who cites it
6 citing papers in PubMed, 1 synthesis or guideline pooled it.
- In-hospital mortality risk prediction models for patients with acute coronary syndrome: a systematic review and meta-analysis.Frontiers in cardiovascular medicine · 2025Pooled it
- Right ventricular-pulmonary arterial uncoupling: an underrecognized predictor of in-hospital outcomes in acute myocardial infarction.BMC cardiovascular disorders · 2026Article
- Development and Temporal Validation of a Logistic Regression-Based Risk Score for Identifying Life-Threatening Chest Pain at Emergency Department Triage: A Retrospective Cohort Study.Vascular health and risk management · 2026Observational
- AI-Based Predictive Models for Cardiogenic Shock in STEMI: Real-World Data for Early Risk Assessment and Prognostic Insights.Journal of clinical medicine · 2025Article
- Anemia, Hyperglycemia, and Reduced Left Ventricular Ejection Fraction Improve the GRACE Score's Predictability for In-hospital Mortality in Acute Coronary Syndrome; Single-Centre Cross-Sectional Study.Open access emergency medicine : OAEM · 2025Article
- Decoding cardiogenic shock: assessing shock index and its variants as prognostic indicators for in-hospital mortality.ESC heart failure · 2024Article
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3 authors.
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No grant is acknowledged in the PubMed record.
Abstract
backgroundThe Shock Index Creatinine (SIC) scoring is a recently developed tool for risk stratification patients. These updated scoring was already used in ST-Elevation Myocardial Infarction (STEMI) patients. However its utility in predicting outcomes for patients with Acute Coronary Syndrome (ACS) remains unclear. This study aims to evaluate and update the current SIC score to predict in-hospital mortality among patients with ACS. PATIENTS AND
methodsA retrospective cohort, Single-centered study enrolled 1349 ACS patients aged ≥ 18 years old diagnosed with ACS was conducted between January 2018 to January 2022 who met for inclusion and exclusion criteria. Study subjects were analyzed for in-hospital mortality and evaluated using binary linear regression analysis. The area under the curve (AUC) of SIC score was obtain to predict the sensitivity and specificity.
resultsMultivariate analysis showed that SIC score was significantly associated with in-hospital mortality. High SIC score (SIC ≥ 25) had significantly higher in-hospital mortality (p < 0.001) with odds ratio for (95% CIs) were 2.655 (1.6-4.31). Receiver operating characteristics (ROC) curve analysis determine the predictive power of SIC score for in-hospital mortality. SIC had an acceptable predictive value for in-hospital mortality (AUC = 0.789, 95% CI: 0.748-0.831, p < 0.001). The SIC score for sensitivity and specificity were, respectively, 71.5% and 74.4%, with optimal cutoff of SIC ≥ 25.
conclusionSIC had acceptable predictive value for in-hospital mortality in patients with all ACS spectrums. SIC was a useful parameter for predicting in-hospital mortality, particularly with a score ≥ 25. This is the first study to evaluate SIC in all spectrums of ACS.
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