GRACE Score Research Articles

Outcomes of Urgent Coronary Artery Bypass Graft Surgery Following Non-ST Elevation Myocardial Infarction

Background: Non-ST elevation myocardial infarction (NSTEMI) significantly reduces patient survival, a condition that is essential for the optimization of results and the restoration of effective vascular flow multivessel coronary artery disease, Emergency coronary artery bypass grafting (CABG) is frequently contemplated. In the aftermath of NSTEMI, the objective of this investigation is to assess the results of urgent CABG, to prioritize risk stratification through the use of the Global Registry of Acute Coronary Events (GRACE) score Methods: An analysis of 60 consecutive patients who underwent emergent CABG following NSTEMI was conducted retrospectively. Data on patients were obtained from a prospectively compiled database, and the GRACE score was implemented to evaluate the probability of mortality. Patients were divided into three risk categories: low (<10%), intermediate (10-19%), and high (≥20%), based on their predicted mortality percentages. Results: Patients in the high-risk group (Group 3) exhibited significantly lower Euro Scores and ejection fractions (EF) than those in the low and intermediate groups, as demonstrated by the study. Additionally, the cross-clamp time was notably longer in Group 3, highlighting the urgency of intervention in this population The postoperative complications' overall incidence did not differ significantly between the groups. Even though Group 3 exhibited an increased in-hospital mortality rate. Conclusions: The findings underscore the importance of timely intervention and tailored management strategies for NSTEMI patients, more specifically, the individuals who have been classified as high-risk by the GRACE score. This study contributes to the growing body of literature supporting urgent CABG as a lifesaving procedure and emphasizes the need for further research to optimize outcomes in this vulnerable patient population. The results advocate for a multidisciplinary approach to enhance perioperative care and improve survival rates among NSTEMI patients undergoing CABG.

QTc interval prolongation impact on in-hospital mortality in acute coronary syndromes patients using artificial intelligence and machine learning

Abstract Background Prediction of mortality in hospitalized patients is a crucial and important problem. Several severity scoring systems over the past few decades and machine learning models for mortality prediction have been developed to predict in-hospital mortality. Our aim in this study was to apply machine learning (ML) algorithms using QTc interval to predict in-hospital mortality in ACS patients and compare them to the validated conventional risk scores. Results This study was retrospective, using supervised learning, and data mining. Out of a cohort of 500 patients admitted to a tertiary care hospital from September 2018 to August 2020, who presented with ACS. Prediction models for in-hospital mortality in ACS patients were developed using 3 ML algorithms. We employed the ensemble learning random forest (RF) model, the Naive Bayes (NB) model and the rule-based projective adaptive resonance theory (PART) model. These models were compared to one another and to two conventional validated risk scores; the Global Registry of Acute Coronary Events (GRACE) risk score and Thrombolysis in Myocardial Infarction (TIMI) risk score. Out of the 500 patients included in our study, 164 (32.8%) patients presented with unstable angina, 148 (29.6%) patients with non-ST-elevation myocardial infarction (NSTEMI) and 188 (37.6%) patients were having ST-elevation myocardial infarction (STEMI). 64 (12.8%) patients died in-hospital and the rest survived. Performance of prediction models was measured in an area under the receiver operating characteristic curve (AUC) ranged from 0.83 to 0.93 using all available variables compared to the GRACE score (0.9 SD 0.05) and the TIMI score (0.75 SD 0.02). Using QTc as a stand-alone variable yielded (0.67 SD 0.02) with a cutoff value 450 using Bazett’s formula, whereas using QTc in addition to other variables of personal and clinical data and other ECG variables, the result was 0.8 SD 0.04. Results of RF and NB models were almost the same, but PART model yielded the least results. There was no significant difference of AUC values after replacing the missing values and applying class balancer. Conclusions The proposed method can effectively predict patients at high risk of in-hospital mortality early in the setting of ACS using only clinical and ECG data. Prolonged QTc interval can be used as a risk predictor of in-hospital mortality in ACS patients.

Abstract 4115231: Higher Global Registry of Acute Coronary Events Score is Associated with Lower Invasive Coronary Angiograpy Use

Background: Use of invasive coronary angiography (ICA) and the selection of other interventions in patients who present with NSTEMI should be guided by clinical risk stratification. National guidelines recommend ICA use in patients with intermediate and high risk scores. The Global Registry of Acute Coronary Events (GRACE) score is a commonly used risk score that is based on clinical characteristics available at the time of admission. Aim: Examine if patients with NSTEMI with higher risk stratification scores are more likely to have ICA. Methods: This cross-sectional study included all patients who presented with NSTEMI to an academic medical center that serves a rural population over a 12-month period. Data were derived from the American College of Cardiology Chest Pain – MI Registry data collected by trained abstractors at the facility and were verifed by the study team. Additional data needed to calculate the GRACE Score were abstracted by the study team. GRACE Scores were categorized into low (1-88), moderate (89-118), and high (119-263) risk. Multivariable logistic regression was used to test if higher GRACE scores are more associated with ICA use controlling for patient factors not included in the GRACE Score and further examined by GRACE score category. Results: The total sample size was 434 patients (Mean age 65±13.8, 36% female and 36% Black). Patients transferred from outlying facilities accounted for 40% of the sample. ICA was performed for 94% of the patients. Increasing GRACE score was associated with lower ICA use (aOR 0.98, 95% CI 0.97-0.99). Odds of ICA use between the low-risk group and the intermediate risk group (aOR 0.60, 95% CI 0.19-1.91) did not significantly differ. Patients in the high-risk category were less likely to undergo ICA compated to low-risk patients (aOR 0.22, 95% CI 0.07-0.62). Conclusions: Use of ICA decreased as GRACE score increased in this patient sample, suggesting that additional factors beyond GRACE score likely influence ICA use in patients who presented with NSTEMI during this time period. Influence of patient factors as well as provider and patient risk aversion on ICA selection must be explored to better understand incongruence with guideline recommendations.

Abstract 4137274: Optimal Timing of Pharmacoinvasive Strategy and its Impact on Clinical in Patients with ST-Elevation Myocardial Infarction: a Real-World Perspective

Background: Pharmacoinvasive strategy remains the cornerstone therapy for ST-elevation myocardial infarction (STEMI) where primary percutaneous coronary intervention (PCI) is unfeasible. Guidelines recommend PCI within 2 to 24 hours post-fibrinolysis. However, meta-analysis suggests that a shorter interval (<4h) between fibrinolysis and PCI (lysis-PCI time) significantly reduces the 30-day risk of death and reinfarction. Real-world applicability is limited due to trial exclusions of elderly patients and those with chronic kidney disease. This study aims to evaluate the impact of lysis-PCI timing on in-hospital mortality and major adverse cardiovascular events (MACE). Hypothesis: We hypothesize that shorter lysis-PCI times (<9h) increase in-hospital mortality and MACE, especially in patients over 80 years. Goals: To determine the impact of lysis-PCI timing on in-hospital mortality and MACE in STEMI patients. Methods: This retrospective cohort study of 1,043 STEMI patients in Brasília, Brazil, used multivariable categorical logistic regression models to assess the association of three lysis-PCI intervals (<9h; 9-18h; >18h) with in-hospital mortality and 4p-MACE (death, acute myocardial infarction, stroke, heart failure). Propensity score matching (1:1) was used to adjust for cardiovascular risk factors. Statistical significance was set at p<0.05. Results: The lysis-PCI timing groups showed no significant differences in admission Killip class, GRACE score, or age. However, the <9h group had higher incidences of in-hospital mortality (p=0.004), heart failure (p=0.002), cardiogenic shock (p=0.001), cardiac arrest within 24 hours (p=0.003), minor bleeding (p=0.006), and MACE (p=0.002). Multivariable categorical logistic regression revealed that each 4-h delay in lysis-PCI time reduced the risk of death (HR 0.560, 95% CI 0.381-0.771; p=0.001) and MACE (HR 0.877, 95% CI 0.811-0.948; p=0.001). These findings remained consistent after propensity score analysis (death: HR 0.721, 95% CI 0.516-0.956; p=0.034). Among patients older than 80, shorter lysis-PCI times were associated with increased mortality and MACE, even after propensity adjustment (Figure 1). Conclusion(s): Shorter lysis-PCI times (<9h) are associated with higher in-hospital mortality and MACE across all age groups, with a pronounced effect in patients over 80 years. These findings underscore the need for careful consideration of lysis-PCI timing, especially in elderly populations.

Abstract 4138355: Machine Learning for Prediction of All-Cause Mortality in Acute Coronary Syndrome

Background: Acute coronary syndrome (ACS) remains one of the leading causes of death globally. Accurate and reliable mortality risk prediction of ACS patients is essential for developing targeted treatment strategies. Existing traditional models offer moderate discriminative value, and do not incorporate contemporary predictors of ACS prognosis. Machine learning (ML) models have emerged as an alternate method that may offer improved risk assessment. This study aims to compare machine learning models with traditional risk scores for predicting all-cause mortality in patients with ACS. Methods: PubMed, EMBASE, Web of Science and Cochrane databases were searched until 1 st November 2023 for studies comparing ML models with traditional statistical methods for event prediction of ACS patients. The primary outcome was comparative discrimination measured by C-statistics with 95% confidence intervals between ML models and traditional methods in estimating the risk of all-cause mortality. Results: Ten studies were included (239627 patients). The summary C-statistic of all ML models across all endpoints was 0.89 (95% CI, 0.86-0.92), compared to traditional methods 0.82 (95% CI, 0.79-0.85). The difference in C-statistic between all ML models and traditional methods was 0.07 (p<0.05). Three models undertook external validation, and calibration was inconsistently reported. Conclusion: ML models demonstrated superior discrimination of all-cause mortality for ACS patients compared to traditional risk scores. Despite outperforming well-established prognostic tools such as the GRACE and TIMI scores, current clinical applications of ML approaches remain uncertain, particularly in view of the methodological limitations of existing studies and the need for greater model validation.

Lung Ultrasound in the Acute Phase of ST-Segment-Elevation Acute Myocardial Infarction: 1-Year Prognosis and Improvement in Risk Prediction.

Lung ultrasound (LUS) has emerged as a useful tool in the acute phase of patients admitted for ST-segment-elevation myocardial infarction. However, its long-term significance remains uncertain, and risk scores do not include LUS findings as a predictor. This study aims to assess the 1-year prognostic value of LUS and its ability to enhance existing risk scores. This is a multicenter prospective cohort study involving 373 patients with ST-segment-elevation myocardial infarction. LUS was performed during the first 24 hours after angiography. LUS results were assessed both as a categorical (wet/dry lung) and continuous variable (LUS score). The primary end point comprised the following major adverse cardiovascular events: all-cause mortality or hospitalization for heart failure, acute coronary syndrome, or stroke within 1 year. We also evaluated whether LUS could enhance the predictive value of the GRACE (Global Registry of Acute Coronary Events) score. Major adverse cardiovascular events occurred in 51 (13.7%) patients over a median follow-up of 368 days. After multivariate analysis, the LUS score was an independent predictor (hazard ratio [HR], 1.06 [95% CI, 1.01-1.10]; P=0.009] for each additional B-line), whereas the categorical classification was an independent predictor in patients with ST-segment-elevation myocardial infarction Killip I (HR, 3.12 [95% CI, 1.34-7.31]; P=0.009). Incorporating LUS into GRACE resulted in a net reclassification index of 31.6% and a significant increase in the area under the curve; GRACE alone scored 0.705 compared with GRACE+LUS 0.791 (P=0.002). Detecting B-lines on LUS at the acute phase predicts major adverse cardiovascular events at 1 year in patients with ST-segment-elevation myocardial infarction and enhances the predictive value of the GRACE score. REGISTRATION: URL: https://www.clinicaltrials.gov; Unique identifier: NCT04526535.

Comparison of GRACE and TIMI risk scores in the prediction of in hospital outcome among NSTEMI patients: a single centre study

Abstract Background Major component of ACS, Non-ST segment elevation myocardial infarction (NSTEMI), has more than twice the incidence compared to ST-segment elevation myocardial infarction (STEMI). GRACE (Global Registry of Acute Coronary Events) and TIMI (Thrombolysis in Myocardial Infarction) risk scores are the two most popular prediction models in ACS due to TIMI’s advantage in its simplicity in clinical application and GRACE’s favorable discriminating power. Nevertheless, limited evidence compared the usefulness of these two major risk scores and their association with in-hospital events. Purpose To compare between the predictive ability of GRACE & TIMI risk scores for In hospital outcomes among the NSTEMI patients . Methods This prospective observational study was carried out from 8th march 2020 to 7th March 2022. Total 2152 acute NSTEMI patients were included. Both GRACE & TIMI risk score were calculated. For GRACE score, patients who scored ≤108 points were low risk,109-139 points were medium risk, ≥140 points were high risk . For TIMI scores patients with 0-2 scores were low risk , 3-4 scores were medium risk and 5-7 score were High risk. In Hospital outcomes were defined as the in hospital composite events which includes acute left ventricular failure, cardiogenic shock, arrhythmia & mortality. Results Among the 2152 patients majority were male (73.5%) with mean age of the study population were 58.33 ± .25 years. Mean Grace score & TIMI score of the study population were 137.81±16.38& 3.29±.97 respectively. Most of the patients were categorized in to Medium risk groups by both GRACE & TIMI risk scores , 70% & 51.3% respectively. However, high risk group percentage were higher in GRACE score group(41.3%) in comparison to TIMI score group(10.3%). GRACE score showed better predictive ability than TIMI score for in-hospital outcomes as evaluated by ROC curve( AUC of GRACE vs TIMI, In hospital ALVF:0.89vs 0.59, P<0.001; Cardiogenic Shock 0.72 vs 0.57, P=0.002; Mortality: 0.75 vs 0.59, P=0.002; arrhythmia 0.72 vs0.63, P=0.003). Conclusion GRACE showed better predictive accuracy than TIMI in NSTEMI patients for in-hospital outcomes. The sequential use of TIMI and GRACE scores provide an easy and promising discriminative tool in predicting outcomes in NSTEMI patients , thus improve the identification of high-risk patients.Pic :ROC curve for prediction of ALVFPic: ROC curve for Mortality prediction

Albumin creatinine index added to the grace score increases its discriminative capacity for mortality at 12 years of follow-up in patients with acute coronary syndrome

Abstract introduction There is currently no information on the prognostic value of the GRACE score with the additional addition of the albumin-creatinine index (ABI) for the prediction of very long-term mortality in unselected populations of acute coronary syndromes (ACS). Objectives To evaluate the additive value of the albumin-creatinine index in spontaneous urine sample to the GRACE score for the prediction of 12-year mortality from all causes in an unselected cohort of patients with acute coronary syndrome. Material and methods A prospective cohort study was carried out, which included patients admitted to a Community Hospital with a diagnosis of ACS. These patients had their IAC measured in a single spontaneous urine sample based on the principle of immunoturbidimetry in the first 24 hours of admission. The end point of the analysis was all-cause mortality at follow-up. The GRACE 2.0 score was calculated for all patients in the study. The scores were compared according to the following metrics: their power to discriminate between events and non-events (ROC Areas), calibration or goodness of fit, evaluating the agreement between the proportion of events and non-events expected by both scores observed by Hosmer Lemeshow Test. The comparison between the areas under the ROC Curves was carried out using De Long's test with the MEDCALC program version 19.1.7. The net reclassification index and its 95% CI (GRACE score + IAC/GRACE score) were evaluated. Results 600 patients with ACS were analyzed, with an average age of 64 years. The GRACE score risk subgroups were divided by the established cut-off values: low risk (0 to 108), intermediate (109 to 139) and high risk (greater than 139). The area under the curve of the Grace score for mortality during follow-up was 0.79 (95% CI 0.69-0.89), while the area under the ROC curve of the GRACE + IAC score was 0.81 (95% CI 0.74-0.87). ). Comparing the two areas by the De Long test, the difference was statistically significant (P < 0.0001; 95% CI 0.07- 0.015). On the other hand, contingency tables were developed and the Hosmer Lemeshow Test (goodness of fit) was performed on the GRACE score and the GRACE + IAC score, observing agreement between expected events and non-events, throughout all subgroups of risk. In addition, reclassifications were made into deceased and survivors by applying the GRACE + IAC score on the GRACE score. The net reclassification rate was 28% (95% CI 21-35). The chi square of its Mc Nemar Test was 3.69 p < 0.0002. The absolute comprehensive discriminatory improvement was 0.01 (95% CI 0.009-0.02) and the corresponding relative value was 8.2% (95% CI 7.9-8.5). Conclusions In this unselected ACS cohort, the albumin-creatinine index added to the GRACE score significantly increases its ability to discriminate mortality from all causes in a 12-year follow-up.Comparison between ROC curvesHosmer Lemeshow test

Examining prognostic scores for short-term major adverse cardiovascular events prediction following primary PCI: a comparative analysis

Abstract Background Accurately predicting short-term MACE (major adverse cardiac events) following primary PCI remains a clinical challenge. This study aims to assess the effectiveness of four established risk scores in predicting short-term MACE after primary PCI (percutaneous coronary intervention). Methodology We enrolled a cohort of consecutive adult patients diagnosed with STEMI (ST elevation myocardial infarction) undergoing primary PCI in this prospective observational study. Patients were followed at the interval of 3 months up for up to 12 months, and MACE events were recorded. Additionally, we obtained TIMI, PAMI, CADILLAC, and GRACE scores. Results A total of 2839 patients (79.3% male, mean age 55.6 ± 11.2 years) were included. Over a median follow-up of 244 days, the composite MACE rate was 18.3% (519). All-cause mortality was 13.5% (384), re-infarction requiring revascularization was 4.3% (121), heart failure-related re-hospitalization was 2.6% (74), stent thrombosis occurred in 5.6% (160), and CVA (cerebrovascular accident) events were documented in 1% (28). The AUC (area under the curve) for TIMI, PAMI, CADILLAC, and GRACE scores were 0.658 [0.630-0.685], 0.658 [0.632-0.684], 0.669 [0.644-0.695], and 0.675 [0.649-0.701], respectively, for the prediction of MACE. On multivariable Cox regression, medium and high-risk categories based on GRACE score were independent predictors of MACE with adjusted HR (hazard ratio) of 1.52 [1.21-1.92]; p<0.001 and 1.92 [1.34-2.75]; p<0.001, respectively. Conclusion A significant proportion of patients experienced short-term MACE after primary PCI. While none of the assessed scores demonstrated significant predictive power, the GRACE score exhibited comparatively better predictive ability than TIMI, PAMI, and CADILLAC scores

Development and validation of a prognostic score integrating remote heart failure symptoms and clinical variables for mortality risk prediction after myocardial infarction. The PragueMi score

Abstract Background While heart failure (HF) symptoms are associated with adverse prognosis after myocardial infarction (MI), they are not routinely used for patients’ stratification. Purpose The primary objective of this study was to develop and validate a score to predict mortality risk after MI, combining remotely recorded HF symptoms and clinical risk factors, and to compare it against the guideline-recommended GRACE score. Methods A cohort study design using prospectively collected data from consecutive patients hospitalized for MI at a large tertiary heart centre between June 2017 and September 2022 was used. Results Data from 1,135 patients (aged 64±12 years, 26.7% women), were split into derivation (70%) and validation cohort (30%). Components of the 23-item Kansas City Cardiomyopathy Questionnaire (KCCQ) questionnaire and clinical variables were used as possible predictors. The best model included the following variables – age, heart failure history, admission creatinine and heart rate, ejection fraction at hospital discharge, and HF symptoms 1 month after discharge including walking impairment, leg swelling, and change in HF symptoms. Based on these variables, the PragueMi score was developed. In the validation cohort, the PragueMi score showed superior discrimination to the GRACE score for 6 months (AUC 90.1, 95% CI 81.8-98.4 vs. 77.4, 95% CI 62.2-92.5, p=0.04) and 1-year risk prediction (AUC 89.7, 95% CI 83.5-96.0 vs. 76.2, 95% CI 64.7-87.7, p=0.004). Conclusion The PragueMi score combining heart failure symptoms and clinical variables performs better than the currently recommended GRACE score.

Predictors of periprocedural myocardial infarction following percutaneous coronary intervenction in NSTEMI

Abstract Background Percutaneous coronary intervention (PCI) has demonstrated a significant positive prognostic impact on outcomes in patients with Non-ST-elevation myocardial infarction (NSTEMI). However, PCI is associated with an increased risk of periprocedural complications, among which periprocedural myocardial infarction (PMI). Although risk factors of periprocedural events are only well established in patients undergoing PCI for chronic coronary syndrome with normal baseline cardiac troponin (cTn) levels, evidence on predictors of additional post-PCI myocardial infarction in patients with acute coronary syndrome who present elevated cTn levels at baseline (pre-PCI) is missing. Purpose To identify the predictors of PMI in patients affected by NSTEMI undergoing PCI. Methods We prospectively evaluated all NSTEMI patients admitted to our coronary care unit from 2017 to 2022 who underwent PCI. NSTEMI patients were managed according to the current European guidelines criteria. The diagnosis of PMI (type 4a myocardial infarction) was based on the Fourth Universal Definition of Myocardial Infarction. We only enrolled patients with stable (≤ 20% variation) or falling pre-procedure baseline cTn values. A multivariable logistic regression analysis was performed to investigate the factors independently associated with the occurrence of PMI after PCI. For the analysis, we selected the main known predictors of PMI after elective PCI, specifically age, serum creatinine, GRACE score > 140, multivessel disease, coronary bifurcation PCI, left main or proximal left anterior descending PCI, multivessel PCI and stent length ≥ 60 mm. Results The final court of the study included 1412 patients. PMI was recognized in 240 patients (17.0%). Although the patients who developed PMI had a higher risk profile as documented by a higher mean age, a higher complexity of atherosclerotic disease, and thus a significant technical difficulty of PCI compared to other patients, according to the multivariable model, only age [OR: 1.02 (95% CI: 1.01-1.04); p=0.006], coronary bifurcation PCI [OR: 3.71 (95% CI: 2.70-5.10); p<0.001], and stent length ≥ 60 mm [OR: 1.87 (95% CI: 1.30-2.68); p=0.001] were independent predictors of PMI. Interestingly, despite previous studies have demonstrated a predictive role of procedural complexity features, this was not completely confirmed by our analysis, in which left main or proximal left anterior descending PCI [OR: 0.92 (95% CI: 0.66-1.26); p=0.596] and multivessel PCI [OR: 0.83 (95% CI: 0.56-1.23); p=0.357] were not associated with an increased risk of periprocedural ischemic complications. Conclusions Among NSTEMI patients undergoing PCI, age, coronary bifurcation PCI and stent length ≥ 60 mm represent independent predictive factors of type 4a MI. This finding may have important clinical implications for clinical practice, providing valuable insights for the identification of higher-risk patients that can benefit from a more aggressive treatment.

Coronary Computed Tomographic Angiography (CCTA) in non-ST elevation acute coronary syndromes

Abstract Background In patients presenting with an acute coronary syndrome (ACS), a diverse range of coronary artery disease is observed from structurally normal vessels to non-obstructive atherosclerosis and severe/obstructive coronary artery disease (CAD). In current clinical practice guidelines, the main diagnostic route for optimal management of patients with non-ST segment elevation acute coronary syndrome is invasive coronary angiography. However, in 30-40% of cases, no significant coronary lesions are evident. The purpose of this study is to describe the role of coronary computed tomographic angiography (CCTA) in non-ST elevation acute coronary syndromes in low and intermediate risk patients. Methods We describe the results of 504 patients evaluated with a protocol that includes the use of CCTA in patients with ACS. Patients over 18 years of age with a diagnosis of ACS without ST elevation who did not meet high-risk criteria (hemodynamic instability, dynamic changes in the ST segment or T wave, ventricular arrhythmia, GRACE score >140, refractory angina, heart failure or cardiorespiratory arrest) were included. They underwent CCTA as the initial coronary evaluation. Data collection was carried out between May 11, 2022 and February 20, 2024. Results 504 patients were included, with a mean age of 58 years, of which 44% were women and 56% men. Among the admission diagnoses, 26% were NSTEMI and 74% were unstable angina according to the 4th universal definition of acute myocardial infarction (AMI). The median high-sensitivity cardiac troponin T value was 7 nanograms per liter (interquartile range, 7 to 15) for the first troponin measurement. CCTA was performed in 93% of the patients. It was observed that 28% did not have any coronary lesions or plaques. 36% had non-obstructive coronary artery disease (plaques <50%). The rest had significant lesions in at least one vessel (27%), predominantly in the left anterior descending artery, or were nondiagnostic (9%). 31% had myocardial bridges, while in 13% of the patients a high-risk plaque was found. 38% of the patients included underwent invasive coronary angiography and 23% required revascularisation. Conclusion This study shows that the prevalence of ACS with coronary arteries without significant lesions by CCTA was 28%, which suggests CCTA could have a predominant role in the diagnostic algorithm of acute coronary syndromes without high-risk criteria, implying a decrease in the need of invasive studies in these patients. Only 38% required invasive coronary angiography, while revascularisation was performed in 23% of the patients. Furthermore, CCTA allowed a better detection of non-obstructive coronary artery disease (NOCAD) in 36% of the patients, and a more complete characterization of the atherosclerotic plaque, which could prompt to an initiation of preventive therapies or the optimization of medical treatment in these patients.Table 1CCTA findings

Clinical outcomes of risk score-guided dual antiplatelet therapy in patients with acute coronary syndrome who underwent percutaneous coronary intervention

Abstract Objective We aimed to investigate the effect of risk score-guided dual antiplatelet therapy (DAPT) in patients with acute coronary syndrome (ACS) who underwent percutaneous coronary intervention (PCI) from real-world clinical practice in Korea. Methods 984 patients with ACS undergoing PCI with bioabsorbable-polymer everolimus eluting stent were enrolled from 20 hospitals in the multicenter, observational study. The analysis was conducted on 834 patients who took medications according to risk score-guided DAPT and were follow-up after 1 year. GRACE score and PRECISE-DAPT score were used for risk score-guided DAPT and medication for antiplatelets was conducted as follow (Figure 1). Results The mean age was 64.0 ± 10.5 years, 77.6% were men. 43.7% had acute myocardial infarction, 62.5% hypertension and 37.6% diabetes. Multivessel and left main artery disease were about in 56.2%. Trans-radial PCI was performed in 76.3%. Aspirin was taken in almost all patients (99.1%) and clopidogrel was most frequently prescribed as a DAPT (clopidogrel 64.9%, Ticagrelor 28.1%, prasugrel 6.6%). All-cause mortality and NACE (consisting of all-cause mortality, myocardial infarction, revascularization, stent thrombosis, stroke, and major/minor bleeding) were 1.2%, and 5.4% respectively at 1 year. Stent thrombosis was occurred only in 4 patients (0.5%). Bleeding complications were developed in 19 case (2.3%). Among the bleeding sites, the access site was the most common 7 (0.8%), followed by the gastrointestinal tract 4 (0.5%). Major bleeding was occurred (BARC types 3 to 5 bleeding) in 3 cases (0.4%) and BARC type 2 was most common (1.2%) (Figure 2 and Table 1). Conclusion Bleeding complications and ischemic events were very low in real-world patients with ACS undergoing PCI during 1 year follow-up, when the management was performed according to the risk scoring-guided DAPT.Figure 1Figure 2 and Table 1

Can a chest pain virtual ward be used to safely manage patients with low-risk acute coronary syndrome?

Abstract Background Acute coronary syndrome (ACS) accounts for approximately 2-6% of emergency department (ED) presentations and contributes at least 20% of the overall acute hospital admissions(1-3). Patients presenting with low-risk ACS may be suitable for remote monitoring(4) while awaiting angiogram in chest pain virtual ward(CPVW) thereby improving patient flow and resource utilisation. Purpose We aimed to assess outcomes for patients with low-risk ACS admitted in a district general hospital with a view to establish an onboarding pathway for CPVW whilst ensuring a safe monitoring without effecting the readmission rate or all-cause mortality. Methods We retrospectively analysed the Myocardial Ischaemia National Audit Project (MINAP) registry of from March 2022 to April 2023 for patients who presented to ED with a diagnosis of confirmed ACS. Patients were stratified into low-risk (GRACE score <140, HEART score <4, non-dynamic ECG, non-dynamic troponin, without ongoing chest pain), all other patients were deemed intermediate-to-high-risk ACS. Baseline demographics, the total length of acute admission days, waiting time before and after coronary investigation ,adverse events (escalation of therapy, death)whilst awaiting for invasive inpatient angiogram were calculated. The primary endpoint was 30-day readmission and all-cause mortality. Results 1077 patients were coded as ACS diagnosis in ED. 561(52.1%) had a confirmed diagnosis of ACS. Data to allow stratification was available for 538 patients, included in final analysis. 377(70.1%) were male with a mean age of 66.8 ± SD 13.1 years. A significant number of patients had other comorbidities, including hypertension (66.1%), diabetes (45.3%), hyperlipidaemia (51.3%), and previous history of IHD (46.5%). Total number of patients stratified into low-risk ACS was 55(10.2%), intermediate-to-high-risk group contained 483(89.8%) patients. The median total-length-of-stay (LOS) for low-risk ACS patients was 4 days(IQR 2-7), waiting time to have an inpatient angiogram was 3 days(IQR 0-5), and discharge time post-angiogram was 1 day(IQR 0-2). 4 patients(7.3%) in low-risk cohort required CCU admission for GTN infusion due to ongoing chest pain, among them 3 patients(5.5%) had abnormal coronary angiogram. 5 patients(9.1%) in low-risk cohort were readmitted due to chest pain post-angiogram and no patients had 30-days or 1-year all-cause mortality. The result depicts 51 patients from low-risk cohort would have been eligible for CPVW reducing the LOS from median 4 days to 1-2 days, this is a saving of 102-153 acute bed days per year. Assuming the costing of a bed day is £320 this equates to £32,640 - £48,960 cost saving without any adverse outcomes. Conclusion Our data suggests that there is a large cost saving with minimal risk in managing patients with low-risk ACS via a CPVW. This pathway of management is likely to have benefit in patient flow and resource utilisation in our district general hospital trust.Comparison of different ACS cohortsCPVW flow-diagram

Pre-discharge prediction of long-term prognosis in patients after ST-segment elevation myocardial infarction - the ValAMI-P risk score

Abstract Background Despite contemporary management of ST-segment elevation myocardial infarction (STEMI) patients, cardiovascular death (CV death) and re-admission for acute heart failure (aHF) are frequent complications during follow-up. Several clinical, electrocardiographic, and echocardiographic variables have been identified as risk factors of major adverse cardiovascular events (MACE) in this setting. We aim to study the usefulness of a risk score using universally available clinical, electrocardiographic, and echocardiographic variables at discharge to stratify the risk of MACE during follow-up. Methods We prospectively included 712 patients treated with primary percutaneous coronary intervention after STEMI. We registered clinical, ECG and echocardiography-derived pre-discharge data. Left ventricular ejection fraction (LVEF) was categorized according to current recommendations. The primary endpoint was time to first MACE, defined as CV death or aHF, whichever occurred first. We created a risk score (ValAMI-P) including variables independently associated with MACE in multivariable analysis. Patients were classified in three groups (low, intermediate, and high risk) according to the ValAMI-P score. Results Mean age was 60±12 years, most patients (78.5%) were male, and smoking was the most prevalent risk factor (54.4%). During an 8.1-year median follow-up, 154 MACE (21.6%) were registered. In multivariable analysis, age (HR 1.03 [1.01-1.05], p=0.001), previous hypertension (HR 1.49 [1.04-2.12], p=0.029), GRACE score (HR 1.01 [1.01-1.02], p<0.001), mildly reduced LVEF (41-49%; HR 1.92 [1.18-3.11], p=0.008), reduced LVEF (≤40%; HR 5.2 [3.53-7.65], p<0.001) and the number of leads with Q-wave and residual ST-segment elevation at pre-discharge ECG (Q-STE; HR 1.13 [1.03-1.25], p=0.013) associated with long-term MACE. After classification according to the ValAMI-P risk score, patients with intermediate (8-13 points) and high (≥14 points) score depicted an increased risk of MACE (31% and 50%, respectively) compared to patients with low ValAMI-P risk score (≤7 points; 13%; p<0.001 for all comparisons). Conclusions The ValAMI-P risk score, which comprises widely available clinical, ECG and echocardiographic variables at discharge, can identify patients at increased long-term risk of MACE after STEMI.ValAMI-P risk score after STEMI

Machine learning for prediction of all-cause mortality in acute coronary syndrome

Abstract Background Acute coronary syndrome (ACS) remains one of the leading causes of death globally. Accurate and reliable mortality risk prediction of ACS patients is essential for developing targeted treatment strategies and improve prognostication. Traditional models for risk stratification such as the Global Registry of Acute Coronary Events (GRACE) and the Thrombolysis In Myocardial Infarction (TIMI) risk scores offer moderate discriminative value, and do not incorporate contemporary predictors of ACS prognosis. Machine learning (ML) models have emerged as an alternate method that may offer improved risk assessment. This study aims to compare machine learning models with traditional risk scores for predicting all-cause mortality in patients with ACS. Methods PubMed, EMBASE, Web of Science and Cochrane databases were searched until 1st November 2023 for studies comparing ML models with traditional statistical methods for event prediction of ACS patients. The primary outcome was comparative discrimination measured by C-statistics with 95% confidence intervals between ML models and traditional methods in estimating the risk of all-cause mortality. Results Ten studies were included (239627 patients). The summary C-statistic of all ML models across all endpoints was 0.89 (95% CI, 0.86-0.92), compared to traditional methods 0.82 (95% CI, 0.79-0.85). The difference in C-statistic between all ML models and traditional methods was 0.07 (p<0.05). Three models undertook external validation, and calibration was inconsistently reported. Conclusion ML models demonstrated superior discrimination of all-cause mortality for ACS patients compared to traditional risk scores. Despite outperforming well-established prognostic tools such as the GRACE and TIMI scores, current clinical applications of ML approaches remain uncertain, particularly in view of the methodological limitations of existing models and the need for greater validation.

Iron deficiency and all-cause mortality after myocardial infarction

Abstract Introduction Iron deficiency (ID) is commonly associated with cardiovascular diseases, including myocardial infarction (MI). However, the data on the clinical significance of ID in patients with MI are conflicting. This may be related to the use of various ID criteria. Purpose Our study aimed to compare the association of different ID criteria with all-cause mortality after MI. Methods Consecutive patients hospitalized at a large tertiary heart center for type 1 MI without previous history of coronary artery disease were included. We evaluated the association of different iron metabolism parameters measured on the first day after hospital admission with all-cause mortality during the follow-up. Results Of a cohort of 1,156 patients included (aged 64±12 years, 25% women), 194 (16.8%) died during the median follow-up of 3.4 years (IQR 626-1782 days). A total of 51,7% of post-MI patients had low iron levels (≤13 µmol/L), and 16,3% of them had iron level ≤12.8 µmol/L and soluble transferrin receptor (sTfR) ≥3 mg/L. After multivariate adjustment, iron level ≤13 µmol/L (HR 1.67, 95% CI 1.19-2.34) and the combination of iron level ≤12.8 µmol/L and sTfR ≥3 mg/L (HR 2.56, 95% CI 1.64-3.99) were associated with an increased risk of mortality. This information provided additional predictive value to the GRACE score. No association between ferritin level and mortality was found. Compared to the model which contains iron level, the addition of sTfR improved risk stratification (net reclassification improvement 0.61, 95% CI 0.52-0.69) by reclassifying patients into a higher-risk group. Conclusion ID is common among patients with the first MI. The criteria based on iron and soluble transferrin receptor levels provide the best prediction of mortality, and should be evaluated in future interventional studies with intravenous iron therapy.Kaplan-Meier survival for iron levelsK-M survival for combined ID parameters

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.

Accurate 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. We 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. The 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. The 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.

Addition of Tilburg frailty indicator to the classic Global Registry of Acute Coronary Events risk score improves its prognostic value in elderly patients with acute coronary syndrome.

Since the proper risk stratification in the growing population of patients with acute coronary syndrome (ACS) is challenging, the potential advantage of adding the elements of geriatric assessment to the commonly used Global Registry of Acute Coronary Events (GRACE) scale in predicting the risk of 6-month death requires investigation. The study group included 196 patients aged ≥65 years (mean age 74.4 years), hospitalized for ACS. The risk of 6-months mortality was assessed with the GRACE scale, the frailty syndrome (FS) using the Tilburg Frailty Indicator questionnaire, the cognitive impairment (CI) using the Polish adaptation of the Mini Mental State Examination and multimorbidity with the CAD specific index. After 6 months, a follow-up telephone call was performed. To enable the assessment of whether adding TFI, MMSE, CAD specific index to the GRACE scale improves its prognostic value, normalization was carried out. In relation to GRACE (AUC 0.713), combination of GRACE (norms) and TFI (norms) had higher predictive power for 6 months mortality (AUC = 0.737). The risk of death was seven times greater [RR = 7.02] in patients with >55.8 points in the test based on GRACE and TFI score. In the multivariable logistic regression analysis the model based on GRACE 2.0, TFI and MMSE (the lowest AIC value) was best-performing in risk of death prediction. Adding the FS assessment to the traditional GRACE scale improves its prognostic value in elderly with ACS.

The predictive role of Systemic Inflammation Response Index (SIRI), Neutrophil-Lymphocyte Ratio (NLR), and Platelet-Lymphocyte Ratio (PLR) in the prognosis of acute coronary syndrome in a tertiary care hospital

Background& Objective: Acute coronary syndrome (ACS) is a major cause of mortality globally, with significant morbidity and economic impact. This study aimed to correlate the neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), and systemic inflammatory response index (SIRI) values in ACS patients with their prognosis via the GRACE scoring criteria and to propose the SIRI as a superior inflammatory marker for predicting ACS prognosis. MethodsEthical approval was obtained for a retrospective cross-sectional study, which included patients from the outpatient department and Tamilnadu Accident Emergency Initiative Ward at Government Medical College, Omandurar Government Estate, who were diagnosed with ACS according to American College of Cardiology guidelines from January 2022 to December 2023. We excluded patients with familial hypercholesterolemia, platelet disorders, infections, inflammatory conditions, or incomplete health records. Data on demographics, clinical findings, blood counts, ECGs, cardiac enzymes, echocardiography, serum creatinine, and vital signs were collected and analyzed to calculate the NLR, PLR, SIRI, and GRACE scores. Statistical analyses included Kolmogorov‒Smirnov and Anderson‒Darling tests, Spearman correlation, Kruskal‒Wallis one-way ANOVA, GLM modeling, k-fold cross-validation, and receiver operating characteristic (ROC) curve analysis. ResultsAfter applying the exclusion criteria, 247 ACS patients were included in the analysis. Significant associations were found between the NLR and the PLR, SIRI, and GRACE scores. The SIRI demonstrated the strongest association, whereas the PLR had the weakest association. All three variables significantly influenced prognostic risk, as determined by the GRACE score. GLM models highlighted the predictive significance of the NLR, PLR, and SIRI in estimating GRACE scores, with the SIRI showing potential superiority. K-fold cross-validation confirmed the superior predictive accuracy and ability of the SIRI to explain a larger proportion of variance in GRACE scores than the NLR and PLR. ConclusionsThe SIRI emerges as a promising prognostic marker for ACS, outperforming the NLR and PLR. Its ease of calculation from routine hemogram tests underscores its potential clinical utility for risk stratification in ACS management. Further validation and integration into existing risk assessment models could enhance prognosis assessment in ACS patients.