Continuous Monitoring of Coronary Care Mortality Using the Global Registry for Acute Coronary Events (GRACE) Score

Ciambrone, Graciana; Higa, Cláudio; Gambarte, Jimena; Novo, Fedor; Nogues, Ignacio; Borracci, Raúl A.

doi:10.1097/hpc.0000000000000208

Cited by 2 publications

(1 citation statement)

References 14 publications

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“…Prospektivna longitudinalna studija za procenu validnosti GRACE skora u praćenju mortaliteta kod AKS sprovedena je između januara 2012. i decembra 2017 na kardiološkim odeljenjima bolnica u Buenos Airesu, u Argentini [20]. U analizu je uključeno ukupno 1.255 ispitanika sa AKS.…”

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The importance of GRACE score in health care planning of patients after acute myocardial infarction

Dordevic¹,

Davidović²,

Resimić³

et al. 2021

Sestrinska reč

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Introduction: Acute myocardial infarction (AIM) is ischemic myocardial necrosis and is associated with a number of adverse outcomes that complicate patient health care. Assessment of patient status, risk factors, and adverse outcomes has a significant impact on patient care planning after AIM. The GRACE (Global Registry of Acute Coronary Events) score is of great importance in risk stratification in these patients. Objective: To determine the importance of determining the GRACE score in order to set priorities in the planning of patient care after acute myocardial infarction. Method: A retrospective study examined 50 patients, both sexes, aged 28 to 75 years, with a diagnosis of acute myocardial infarction, undergoing percutaneous coronary intervention (PKI), who were treated at the Zvezdara Clinical Hospital in Belgrade during the research period, from January to March 2020. Data were taken from the medical records of these patients. During the study, AIM type, comorbidities, CVD risk factors, GRACE score and frequency of complex nursing interventions in patients with low, moderate, and high-risk of adverse cardiac events were monitored. Results: Out of a total of 50 examinees with AIM treated with PKI, 74% had STEMI and 26% NSTEMI. 84% of patients had positive family history, 64% hypertension, 2% diabetes, 48% obesity, 52% were smokers and 6% of them were using alcohol. The values of the GRACE score were increased as follows: in four patients more than 140, while in one of them a moderate value was recorded, and in one low value of the GRACE score. In the course of six months, three patients, who had high GRACE scores on hospitalization, had a lethal outcome. Complex nursing interventions in the intensive care unit are more common in patients who have high GRACE score values after AIM. Conclusion: The GRACE score can be used as an important guideline in planning the health care of patients after an acute myocardial infarction.

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Section: Diskusijaunclassified

The importance of GRACE score in health care planning of patients after acute myocardial infarction

Dordevic¹,

Davidović²,

Resimić³

et al. 2021

Sestrinska reč

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Prediction of in-hospital mortality risk for patients with acute ST-elevation myocardial infarction after primary PCI based on predictors selected by GRACE score and two feature selection methods

Tang,

Liu,

et al. 2024

Front. Cardiovasc. Med.

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IntroductionAccurate in-hospital mortality prediction following percutaneous coronary intervention (PCI) is crucial for clinical decision-making. Machine Learning (ML) and Data Mining methods have shown promise in improving medical prognosis accuracy.MethodsWe analyzed a dataset of 4,677 patients from the Regional Vascular Center of Primorsky Regional Clinical Hospital No. 1 in Vladivostok, collected between 2015 and 2021. We utilized Extreme Gradient Boosting, Histogram Gradient Boosting, Light Gradient Boosting, and Stochastic Gradient Boosting for mortality risk prediction after primary PCI in patients with acute ST-elevation myocardial infarction. Model selection was performed using Monte Carlo Cross-validation. Feature selection was enhanced through Recursive Feature Elimination (RFE) and Shapley Additive Explanations (SHAP). We further developed hybrid models using Augmented Grey Wolf Optimizer (AGWO), Bald Eagle Search Optimization (BES), Golden Jackal Optimizer (GJO), and Puma Optimizer (PO), integrating features selected by these methods with the traditional GRACE score.ResultsThe hybrid models demonstrated superior prediction accuracy. In scenario (1), utilizing GRACE scale features, the Light Gradient Boosting Machine (LGBM) and Extreme Gradient Boosting (XGB) models optimized with BES achieved Recall values of 0.944 and 0.954, respectively. In scenarios (2) and (3), employing SHAP and RFE-selected features, the LGB models attained Recall values of 0.963 and 0.977, while the XGB models achieved 0.978 and 0.99.DiscussionThe study indicates that ML models, particularly the XGB optimized with BES, can outperform the conventional GRACE score in predicting in-hospital mortality. The hybrid models' enhanced accuracy presents a significant step forward in risk assessment for patients post-PCI, offering a potential alternative to existing clinical tools. These findings underscore the potential of ML in optimizing patient care and outcomes in cardiovascular medicine.

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Continuous Monitoring of Coronary Care Mortality Using the Global Registry for Acute Coronary Events (GRACE) Score

Cited by 2 publications

References 14 publications

The importance of GRACE score in health care planning of patients after acute myocardial infarction

The importance of GRACE score in health care planning of patients after acute myocardial infarction

Prediction of in-hospital mortality risk for patients with acute ST-elevation myocardial infarction after primary PCI based on predictors selected by GRACE score and two feature selection methods

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