Comparación del valor predictivo pronóstico de los scores TIMI, PAMI, CADILLAC y GRACE en el SCACEST sometido a ICP primario o de rescate

The association between GRACE score at admission for myocardial infarction and the incidence of sudden cardiac arrests in long-term follow-up - the MADDEC study

Background. Sudden cardiac arrest (SCA), often also leading to sudden cardiac death (SCD), is a common complication in coronary artery disease. Despite the effort there is a lack of applicable prediction tools to identify those at high risk. We tested the association between the validated GRACE score and the incidence of SCA after myocardial infarction. Material and methods. A retrospective analysis of 1,985 patients treated for myocardial infarction (MI) between January 1st 2015 and December 31st 2018 and followed until the 31st of December of 2021. The main exposure variable was patients' GRACE score at the point of admission and main outcome variable was incident SCA after hospitalization. Their association was analyzed by subdistribution hazard (SDH) model analysis. The secondary endpoints included SCA in patients with no indication to implantable cardioverter-defibrillator (ICD) device and incident SCD. Results. A total of 1985 patients were treated for MI. Mean GRACE score at baseline was 118.7 (SD 32.0). During a median follow-up time of 5.3 years (IQR 3.8-6.1 years) 78 SCA events and 52 SCDs occurred. In unadjusted analyses one SD increase in GRACE score associated with over 50% higher risk of SCA (SDH 1.55, 95% CI 1.29-1.85, p < 0.0001) and over 40% higher risk for SCD (1.42, 1.12-1.79, p = 0.0033). The associations between SCA and GRACE remained statistically significant even with patients without indication for ICD device (1.57, 1.30-1.90, p < 0.0001) as well as when adjusting with patients LVEF and omitting the age from the GRACE score to better represent the severity of the cardiac event. The association of GRACE and SCD turned statistically insignificant when adjusting with LVEF. Conclusions. GRACE score measured at admission for MI associates with long-term risk for SCA.

Comparative Analysis of the Effectiveness of Riskometer Scales in Predicting the Risk of in-Hospital Mortality in Patients With ST-Segment Elevation Myocardial Infarction After Percutaneous Coronary Intervention

AIM

Comparative evaluation of the effectiveness of riskometer scales in predicting in-hospital death (IHD) in patients with ST-segment elevation myocardial infarction (STEMI) after percutaneous coronary intervention (PCI) and the development of new models based on machine learning methods.

MATERIAL AND METHODS

A single-center cohort retrospective study was conducted using data from 4,675 electronic medical records of patients with STEMI (3,202 men and 1,473 women) with a median age of 63 years who underwent emergency PCI. Two groups of patients were isolated: group 1 included 318 (6.8%) patients who died in hospital; group 2 consisted of 4,359 (93.2%) patients with a favorable outcome. The GRACE, CADILLAC, TIMI-STe, PAMI, and RECORD scales were used to assess the risk of IHD. Prognostic models of IHD predicted by the sums of these scale scores were developed using single- and multivariate logistic regression, stochastic gradient boosting, and artificial neural networks (ANN). Risk of adverse events was stratified based on the ANN model data by calculating the median values of predicted probabilities of IHD in the compared groups.

RESULTS

Comparative analysis of the prognostic value of individual scales for the STEMI patients showed differences in the quality of the risk stratification for IHD after PCI. The GRACE scale had the highest prognostic accuracy, while the PAMI scale had the lowest accuracy. The CADILLAC and TIMI-STe scales had acceptable and comparable prognostic abilities, while the RECORD scale showed a significant proportion of false-positive results. The integrative ANN model, the predictors of which were the scores of 5 scales, was superior in the prediction accuracy to the algorithms of single- and multivariate logistic regression and stochastic gradient boosting. Based on the ANN model data, the probability of IHD was stratified into low (<0.3%), medium (0.3-9%), high (9-17%), and very high (>17%) risk groups.

CONCLUSION

The GRACE, CADILLAC and TIMI-STe scales have advantages in the stratification accuracy of IHD risk in patients with STEMI after PCI compared to the PAMI and RECORD scales. The integrated ANN model that combines the prognostic resource of the five analyzed scales, had better quality criteria, and the stratification algorithm based on the data of this model was characterized by accurate identification of STEMI patients with high and very high risk of IHD after PCI.

Short- and long-term performance of risk calculation tools for mortality in patients with acute coronary syndrome

Background

The mortality rate of acute coronary syndrome (ACS) remains high. Therefore, patients with ACS should undergo early risk stratification, for which various risk calculation tools are available. However, it remains uncertain whether the predictive performance varies over time between risk calculation tools for different target periods. This study aimed to compare the predictive performance of risk calculation tools in estimating short- and long-term mortality risks in patients with ACS, while considering different observation periods using time-dependent receiver operating characteristic (ROC) analysis.

Methods

This study included 404 consecutive patients with ACS who underwent coronary angiography at our hospital from March 2017 to January 2021. The ACTION and GRACE scores for short-term risk stratification purposes and CRUSADE scores for long-term risk stratification purposes were calculated for all participants. The participants were followed up for 36 months to assess mortality. Using time-dependent ROC analysis, we evaluated the area under the curve (AUC) of the ACTION, CRUSADE, and GRACE scores at 1, 6, 12, 24, and 36 months.

Results

Sixty-six patients died during the observation periods. The AUCs at 1, 6, 12, 24, and 36 months of the ACTION score were 0.942, 0.925, 0.889, 0.856, and 0.832; those of the CRUSADE score were 0.881, 0.883, 0.862, 0.876, and 0.862; and those of the GRACE score 0.949, 0.928, 0.888, 0.875, and 0.860, respectively.

Conclusions

The ACTION and GRACE scores were excellent risk stratification tools for mortality in the short term. The prognostic performance of each risk score was almost similar in the long term, but the CRUSADE score might be a superior risk stratification tool in the longer term than 3 years.

External validation of the GRACE risk score in patients with myocardial infarction in Hungary

Background

Literature confirms that the Global Registry of Acute Coronary Events (GRACE) risk score provides a better risk evaluation than clinical judgment in patients with acute myocardial infarction. We aimed to externally validate the GRACE risk score in unselected patients with myocardial infarction in Hungary.

Methods

Data from the comprehensive Hungarian Myocardial Infarction Registry (HUMIR), a national registry that collects data on consecutive acute myocardial infarction (AMI) patients, were used. Hospitals registered 102,939 infarction events in the HUMIR between January 1, 2014, and December 31, 2020. The data required to calculate GRACE risk score were available for 75,199 events. We studied the 6-months, 1-year, and 3-year outcomes. We calculated widely used metrics to characterise calibration (calibration curve, calibration intercept and slope, Eavg, Emax, and E90) and discrimination (c-score, equivalent to AUC, and Somer's D_xy).

Results

The risk of low-risk patients was underestimated, and the risk of high-risk patients was overestimated. However, the deviation was small, especially for the three-year survival (E90 was 0.15, 0.22, and 0.08). Discrimination was good, with an AUC of approximately 0.8, and was very similar in all the periods.

Conclusions

These data confirmed the usefulness of GRACE risk score in selecting high-risk patients with myocardial infarction in the Hungarian population.

Association between the number of Academic Research Consortium for High Bleeding Risk (ARC-HBR) criteria and clinical outcomes in patients with acute coronary syndrome

BACKGROUND

Academic Research Consortium for High Bleeding Risk (ARC-HBR) criteria have been used to identify high-risk patients undergoing percutaneous coronary intervention (PCI) in current clinical practice. This study aimed to evaluate the association between the number of ARC-HBR criteria and clinical outcomes in patients with acute coronary syndrome (ACS) after an emergent PCI.

METHODS

We assessed 338 consecutive patients with ACS who underwent successful emergent PCI between January 2017 and December 2020. The ARC-HBR score was calculated by assigning 1 point to each major criterion and 0.5 points to each minor criterion. The patients were classified into low (ARC-HBR score<1), intermediate (1≤ARC-HBR score<2), and high (ARC-HBR score≥2) bleeding risk groups. We investigated the association between the ARC-HBR score and major adverse cardiovascular events (MACEs), defined as a composite of all-cause death, non-fatal myocardial infarction, and non-fatal stroke. We also compared the diagnostic ability of the ARC-HBR score and Controlled Abciximab and Device Investigation to Lower Late Angioplasty Complications (CADILLAC) risk score.

RESULTS

The mean age of the patients was 67.6±12.4years, and 78.4% were men. During the median follow-up of 864 (557-1309) days, 70 patients developed MACEs. Kaplan-Meier curves showed that the cumulative incidence of MACE was significantly higher as the ARC-HBR score increased in a stepwise manner (log-rank p<0.001). There were no significant differences in the area under the receiver operating characteristic curve (AUC) for predicting MACE within two years after an emergent PCI between the ARC-HBR and CADILLAC risk scores (AUC: 0.763 vs. 0.777).

CONCLUSIONS

ARC-HBR score was independently associated with an increased risk of MACE in patients with ACS after an emergent PCI. Moreover, it had a similar diagnostic ability for predicting MACE within two years compared to the CADILLAC risk score.

Comparison of Different Risk Scores for Prediction of In-Hospital Mortality in STEMI Patients Treated with PPCI

Background

Several risk scores have been developed to predict and analyze in-hospital mortality and short- and long-term outcomes of ST-elevation myocardial infarction (STEMI) patients after primary percutaneous coronary intervention (PPCI); these can classify patients as having a high or low risk of death or complications.

Objective

To compare the prognostic precision of four risk scores for predicting in-hospital mortality in patients with STEMI treated with PPCI.

Methods

We performed a retrospective cohort analysis of patients with STEMI who underwent PPCI between 2012 and 2019 (N = 1346). GRACE (Global Registry of Acute Cardiac Events), CADILLAC (Controlled Abciximab and Device Investigation to Lower Late Angioplasty Complications), Zwolle, and TIMI (Thrombolysis in Myocardial Infarction) risk scores were calculated for each patient according to different variables. We evaluated the predictive accuracy of these scores for in-hospital mortality using the C statistic, which was obtained using logistic regression and receiver operating characteristic curves.

Results

The GRACE, CADILLAC, Zwolle, and TIMI risk scores all had good predictive precision for in-hospital mortality, with C statistics ranging from 0.842 to 0.923. The GRACE and CADILLAC risk scores were found to be superior.

Conclusions

All GRACE, CADILLAC, Zwolle, and TIMI risk scores showed a high predictive value for in-hospital mortality due to all causes in patients with STEMI treated with PPCI. The GRACE and CADILLAC risk scores revealed a better accuracy for predicting in-hospital mortality than the Zwolle and TIMI risk scores.

Evaluation and Comparison of the STIMUL Extended and Simplified Risk Scores for Predicting Two-Year Death in Patients Following ST-Segment Elevation Myocardial Infarction

Background and Objectives: The management of ST-segment elevation myocardial infarction (STEMI) requires a patient’s long-term risk to be estimated. The objective of this study was to develop extended and simplified models of two-year death risk estimation following STEMI that include and exclude cardiac troponins as prognostic factors and to compare their performance with each other. Materials and Methods: Extended and simplified multivariable logistic regression models were elaborated using 1103 patients with STEMI enrolled and followed up in the STIMUL (ST-segment elevation Myocardial Infarctions in Ukraine and their Lethality) registry. Results: The extended STIMUL risk score includes seven independent risk factors: age; Killip class ≥ II at admission; resuscitated cardiac arrest; non-reperfused infarct-related artery; troponin I ≥ 150.0 ng/L; diabetes mellitus; and history of congestive heart failure. The exclusion of cardiac troponin in the simplified model did not influence the predictive value of each factor. Both models divide patients into low, moderate, and high risk groups with a C-statistic of 0.89 (95% CI 0.84–0.93; p < 0.001) for the extended STIMUL model and a C-statistic of 0.86 (95% CI 0.83–0.99; p < 0.001) for the simplified model. However, the addition of the level of troponin I to the model increased its prognostic value by 10.7%. Conclusions: The STIMUL extended and simplified risk estimation models perform well in the prediction of two-year death risk following STEMI. The simplified version may be useful when clinicians do not know the value of cardiac troponins among the population of STEMI patients.

Development and Validation of a Nomogram of In-hospital Major Adverse Cardiovascular and Cerebrovascular Events in Patients With Acute Coronary Syndrome

Background and Objective: This study aims to develop and validate a nomogram for the occurrence of in-hospital major adverse cardiovascular and cerebrovascular events (MACCE) in acute coronary syndrome (ACS) patients. Methods: A total of 1,360 ACS patients admitted between November 2014 and October 2019 from Zhongda Hospital and Yancheng Third People's Hospital were included. Patients admitted in Zhongda Hospital before 2018 were split into the training cohort (n = 793). Those admitted after 2018 in Zhongda Hospital and patients from Yancheng Third People's Hospital were split into the validation cohort (n = 567). Twenty eight clinical features routinely assessed including baseline characteristics, past medical history and auxiliary examinations were used to inform the models to predict in-hospital MACCE (all-cause mortality, reinfarction, stroke, and heart failure) in ACS patients. The best-performing model was tested in the validation cohort. The accuracy and clinical applicability were tested by the area under the receiver operating characteristic curve (AUC), calibration plots, and decision curve analyses (DCA). Results: The in-hospital MACCE occurred in 93 (6.83%) patients. The final prediction model consists of four variables: age, Killip grading, fasting blood-glucose (FBG) and whether percutaneous coronary intervention (PCI) was performed at early stage. A nomogram was used to present the final result. Individualized nomogram exhibited comparable discrimination to the Global Registry of Acute Coronary Events (GRACE) score [AUC: 0.807 (95% CI 0.736-0.878) vs. 0.761 (95% CI 0.69-0.878)], P = 0.10) and a better discrimination than the Evaluation of the Methods and Management of Acute Coronary Events (EMMACE) score [AUC: 0.807 (95% CI 0.736-0.878) vs. 0.723(95% CI 0.648-0.798), P = 0.01] in predicting the risk of in-hospital MACCE in ACS patients. A good prediction performance was maintained in the validation cohort (AUC =0.813, 95% CI 0.738-0.889). The prediction model also exhibited decent calibration (P = 0.972) and clinical usefulness. Conclusion: The nomogram may be a simple and effective tool in predicting the occurrence of in-hospital MACCE in ACS patients. Further longitudinal studies are warranted to validate its value in guiding clinical decision-making and optimizing the treatment of high-risk patients.

Predicting 30-day mortality after ST elevation myocardial infarction: Machine learning- based random forest and its external validation using two independent nationwide datasets

BACKGROUND

Various prognostic models for mortality prediction following ST-segment elevation myocardial infarction (STEMI) have been developed over the past two decades. Our group has previously demonstrated that machine learning (ML)-based models can outperform known risk scores for 30-day mortality post-STEMI. The study aimed to redevelop an ML-based random forest prediction model for 30-day mortality post-STEMI and externally validate it on a large cohort.

METHODS

This was a retrospective, supervised learning, data mining study developed on the Acute Coronary Syndrome Israeli Survey (ACSIS) registry and the Myocardial Ischemia National Audit Project (MINAP) for external validation. Patients included received reperfusion therapy for STEMI between 2006 and 2016. Discrimination and calibration performances were assessed for two developed models and compared with the Global Registry of Acute Cardiac Events (GRACE) score.

RESULTS

The ACSIS cohort (2,782 included /15,212 total) and MINAP cohort (22,693 included/735,000 total) were significantly different in most variables, yet similar in 30-day mortality rate (4.3-4.4%). Random forest models were developed on the ACSIS cohort with a full model including all 32 variables and a simple model including the 10 most important ones. Features' importance was calculated using the varImp function measuring how much each feature contributes to the data's homogeneity. Applying the optimized models on the MINAP validation cohort showed high discrimination of area under the curve (AUC) = 0.804 (0.786-0.822) for the full model, and AUC = 0.787 (0.748-0.780) using the simple model, compared with the GRACE risk score discrimination of AUC = 0.764 (0.748-0.780). All models were not well calibrated for the MINAP data. Following Platt scaling on 20% of the MINAP data, the random forest models calibration improved while the GRACE calibration did not change.

CONCLUSIONS

The random forest predictive model for 30-day mortality post STEMI, developed on the ACSIS national registry, has been validated in the MINAP large external cohort and can be applied early at admission for risk stratification. The model performed better than the commonly used GRACE score. Furthermore, to the best of our knowledge, this is the first externally validated ML-based model for STEMI.

Risk Assessment Using Risk Scores in Patients with Acute Coronary Syndrome

Risk scores are widely used in patients with acute coronary syndrome (ACS) prior to treatment decision-making at different points in time. At initial hospital presentation, risk scores are used to assess the risk for developing major adverse cardiac events (MACE) and can guide clinicians in either discharging the patients at low risk or swiftly admitting and treating the patients at high risk for MACE. During hospital admission, risk assessment is performed to estimate mortality, residual ischemic and bleeding risk to guide further in-hospital management (e.g., timing of coronary angiography) and post-discharge management (e.g., duration of dual antiplatelet therapy). In the months and years following ACS, long term risk can also be assessed to evaluate current treatment strategies (e.g., intensify or reduce pharmaceutical treatment options). As multiple risk scores have been developed over the last decades, this review summarizes the most relevant risk scores used in ACS patients.

Mortality prediction algorithms for patients undergoing primary percutaneous coronary intervention

Mortality risk of ST-segment elevation myocardial infarction (STEMI) patients shows high variability. In order to assess individual risk, a number of scoring systems have been developed and validated. Yet, as treatment approaches evolve over time with improving outcomes, there is a need to build new risk prediction algorithms to maintain/increase prognostic accuracy. One of the most relevant improvements of therapy is primary percutaneous coronary intervention (PCI). We overview the characteristics and discriminative performance of the most studied and some recently constructed mortality risk models that were validated in patients with STEMI who underwent primary PCI.

ACTION (acute coronary treatment and intervention outcomes network) registry-GWTG (get with the guidelines) risk score predicts long-term mortality in acute myocardial infarction

This study aimed to test the predictive performance of the updated ACTION, GRACE, and CADILLAC risk scores (RS’s) for long-term mortality in patients with acute myocardial infarction (AMI) undergoing percutaneous coronary intervention (PCI). The study included individuals from 2 independent cohorts: derivation cohort (N = 1901) and validation cohort (N = 728). From the derivation cohort, we used Cox regression analysis to determine that the updated ACTION, GRACE, and CADILLAC RS's were associated with long-term mortality. The concordance (C) statistics of the 3 RS's were 0.682, 0.703 and 0.734, respectively. We used the validation cohort to validate the results. Moreover, the discriminatory performance of the updated ACTION RS for predicting long-term mortality in both the respective derivation and validation cohorts was similar to the discriminatory performance of the GRACE and CADILLAC RS's (ACTION vs. GRACE: z = 0.684, p = 0.494; ACTION vs. CADILLAC: z = 1.638, p = 0.101) and (ACTION vs. GRACE: z = 0.460, p = 0.646; ACTION vs. CADILLAC: z = 0.290, p = 0.772). Despite their development over a decade ago, GRACE and CADILLAC RS's maintain good performance for predicting the long-term mortality of AMI patients undergoing PCI. As a new risk model, the updated ACTION RS also predicts long-term mortality, and its discriminatory performance is similar to that of the GRACE and CADILLAC RS’s.

A novel risk model including vascular access site for predicting 30-day mortality after primary PCI: The ALPHA score

BACKGROUND

The mortality benefit of transradial primary PCI has been shown by several studies. Previous risk models have not considered access site as a candidate predictor and many of them were developed using low risk populations of randomized trials. We conducted a prospective cohort study to construct and validate an admission risk model including access site as candidate variable for predicting 30-day mortality after primary PCI.

METHODS

We analyzed data of 1255 patients using variables readily available at presentation. Predictor selection was based on backward logistic regression combined with bootstrap resampling. The model has been validated internally and temporally externally.

RESULTS

Thirty-day mortality was independently associated with older age, faster heart rate, need for life support on or prior to admission, and femoral access while it was inversely related to systolic blood pressure. ROC curve analysis revealed high discriminatory power, which was preserved in the validation set (c-statistic: 0.88 and 0.87, respectively). For the new score the acronym ALPHA (Age, Life support, Pressure, Heart rate, Access site) has been coined. Compared with previous models, our score achieved the highest c-statistic (0.87) followed by the GRACE 2.0 (0.86), APEX-AMI (0.86), and CADILLAC (0.85) models, the other scoring systems (TIMI, Zwolle, and PAMI) performed less well. The ALPHA, GRACE 2.0, APEX-AMI, and CADILLAC models predicted 30-day mortality better than the PAMI score (p=0.005, 0.004, 0.01, and 0.02, respectively).

CONCLUSIONS

Using this tool, mortality risk may be precisely assessed at admission and patients who may benefit most from transradial access may be identified.

A simple risk score in acute ST-elevation myocardial infarction: Modified ACEF(age, creatinine, and ejection fraction) score

BACKGROUND/AIM

The aim of this study was to evaluate if the modified ACEF (age, creatinine, and ejection fraction) score is a predictor of major adverse cardiac and cerebrovascular events during 1 year of follow-up in patients with ST-segment elevation myocardial infarction (STEMI) who underwent primary percutaneous coronary intervention (PCI).

MATERIALS AND METHODS

We retrospectively enrolled 1632 consecutive patients who were admitted to our emergency department diagnosed with STEMI within 12 h of chest pain and treated with primary PCI. The modified ACEF score, determined with a simplified scoring system, was calculated. The patients were grouped into tertiles according to this score (group I mACEF < 1.03, group II mACEF 1.03-1.37, group III > 1.37) . The clinical and angiographic data were compared among the tertiles.

RESULTS

In patients with the highest mACEF tertile, out-of-hospital cardiac arrest (1.3%, 1.8%, and 4.1% consecutively; P = 0.003), Killip class &ge; II (P < 0.001), and cardiogenic shock were more common and ejection fraction was lower (P < 0.001). Moreover, in the 1-year follow-up, there was a statistically significant difference between cardiac mortality, target vessel revascularization, stroke, reinfarction, and major adverse cardiac and cerebrovascular events of the groups, while the rates of stent thrombosis were similar.

CONCLUSION

The modified ACEF score is a predictor of cardiac mortality and morbidity during 1-year follow-up.

Accuracy of dedicated risk scores in patients undergoing primary percutaneous coronary intervention in daily clinical practice

BACKGROUND

Comparisons between dedicated risk scores in patients with ST-segment elevation myocardial infarction (STEMI) undergoing primary percutaneous coronary intervention (pPCI) in real-world clinical practice are scarce. The aim of this study was to assess the diagnostic performance of the Global Registry of Acute Coronary Events (GRACE), Primary Angioplasty in Myocardial Infarction (PAMI), Thrombolysis in Myocardial Infarction (TIMI), and Zwolle scores in STEMI patients undergoing pPCI in contemporary clinical practice.

METHODS

This was a prospective cohort study of consecutive patients with STEMI undergoing pPCI between December 2009 and November 2010 in a high-volume tertiary referral centre. The outcomes assessed were major cardiovascular events (MACEs) and death within 30 days. The diagnostic accuracy of the scores was assessed using receiver operating characteristic curves, and scores were compared using the DeLong method.

RESULTS

During the study period, 501 patients were included. Within 30 days, 62 patients (12.4%) presented a MACE and 39 individuals (7.8%) died. All scores were statistically associated with death and MACE within 30 days (P < 0.01). The c-statistic and 95% confidence intervals for 30-day mortality were: GRACE, 0.84 (0.78-0.90); TIMI, 0.81 (0.74-0.87); Zwolle, 0.80 (0.73-0.87); and PAMI, 0.75 (0.68-0.82) (P < 0.01). There was no statistically significant difference regarding the accuracy of the TIMI, GRACE, and Zwolle scores for 30-day mortality, but the GRACE score was superior to the PAMI score (P < 0.01).

CONCLUSIONS

The TIMI, GRACE, and Zwolle scores performed equally well as predictors of mortality in patients who underwent pPCI in current practice. These results suggest that these scores are suitable options for risk assessment in a real-world setting.

[Acute coronary syndrome in nonagenarians: clinical evolution and validation of the main risk scores]

INTRODUCTION

Several risk scores regarding the probability of death/complications in the acute setting and during the follow-up of patients admitted with acute coronary syndromes (ACS) have been published, such as the GRACE, TIMI and ZWOLLE risk score. Our objective was to assess the prognosis of nonagenarians admitted to a coronary care unit with an ACS, as well as the usefulness of each of these scores.

MATERIAL AND METHODS

A retrospective analysis was performed on nonagenarians with an ACS admitted between 2003 and 2011. Vital status was determined at 14, 30 days, and 6 months after the ACS, and later during the follow-up. The risk scores were evaluated by area under the curve ROC (AUC).

RESULTS

A total of 45 patients with an ACS, 26 (57.8%) with ST-segment elevation and 19 (42.2%) with non-ST elevation. The GRACE- AUC for in-hospital mortality was excellent, 0.91, (95% CI: 0.82-1; P<.001), and for the combined event (in-hospital mortality and re-infarction) was 0.83 (95% CI: 0.66-1.0; P<.01). However, the GRACE-AUC at 6 months for mortality was 0.34 (95% CI: 0.09-0.58; P=.45), and for the combined event it was 0.51 (95% CI: 0.26-0.77; P=.95). The TIMI-AUC and ZWOLLE-AUC did not reach statistical significance.

CONCLUSIONS

It is useful calculate the GRACE risk score in order to estimate risk and survival in the acute phase of ACS in nonagenarians. This can help appropriate in making invasive or conservative treatment decisions.

Inflammatory markers in blood and thrombus aspirated from patients with acute myocardial infarction with st-segment elevation: ARTERIA trial study design and rationale

The mechanism of coronary thrombus formation is a complex phenomenon that involves different cellular components. ARTERIA is a prospective, multicenter study that will include patients presenting with a diagnosis of ST-elevation acute coronary syndrome undergoing thrombus aspiration during an emergency primary percutaneous coronary revascularization. The purpose of the ARTERIA study is to try to clarify whether there is an association between inflammatory markers measured in blood and in intracoronary thrombi and, if any, what set of molecules provides better prognostic information in these patients. Our study will help to elucidate the complex relationship between thrombus and circulating blood.

Risk scores in acute coronary syndrome and percutaneous coronary intervention: a review

Patients with acute coronary syndrome (ACS) need to be risk stratified to deliver the most appropriate therapy. The GRACE and TIMI risk scores have penetrated contemporary guidelines with the former most commonly used in clinical practice. However, ACS prediction models need to be re-evaluated in contemporary practice with evolving diagnostic and treatment options. Moreover, the increased availability of percutaneous coronary intervention (PCI) as a treatment option for ACS combined with an expanding case mix and emphasis on quality control have triggered the creation of PCI specific prognostic models. These allow clinicians and patients to have an understanding of expected outcomes following PCI by predicting outcomes in-hospital to 5 years following intervention. The aim of this review is to evaluate the most recognized and studied ACS/PCI risk models, focusing on their strengths and limitations, and to assess the need for more robust tools to predict outcomes in a period of constantly advancing technologies and changing patient demographics.