Rationale and design of the GRACE (Global Registry of Acute Coronary Events) Project: a multinational registry of patients hospitalized with acute coronary syndromes

Development and transfer learning of self-attention model for major adverse cardiovascular events prediction across hospitals

Predicting major adverse cardiovascular events (MACE) is crucial due to its high readmission rate and severe sequelae. Current risk scoring model of MACE are based on a few features of a patient status at a single time point. We developed a self-attention-based model to predict MACE within 3 years from time series data utilizing numerous features in electronic medical records (EMRs). In addition, we demonstrated transfer learning for hospitals with insufficient data through code mapping and feature selection by the calculated importance using Xgboost. We established operational definitions and categories for diagnoses, medications, and laboratory tests to streamline scattered codes, enhancing clinical interpretability across hospitals. This resulted in reduced feature size and improved data quality for transfer learning. The pre-trained model demonstrated an increase in AUROC after transfer learning, from 0.564 to 0.821. Furthermore, to validate the effectiveness of the predicted scores, we analyzed the data using traditional survival analysis, which confirmed an elevated hazard ratio for a group with high scores.

The clinical value of serum long non-coding RNA human leukocyte antigen complex group 11/microRNA-532-3p in the diagnosis and prognosis of patients with acute myocardial infarction undergoing percutaneous coronary intervention

BACKGROUND

Acute myocardial infarction (AMI) is a cardiovascular disease with the highest morbidity and mortality rate in the world. Several studies have suggested that abnormal regulation of non-coding RNAs (ncRNAs) may play a vital role in the occurrence and progress of AMI.

OBJECTIVE

The purpose of this study was to investigate the clinical values of human leukocyte antigen complex group 11 (HCG11) or miR-532-3p in the diagnosis and prognosis of patients with AMI after percutaneous coronary intervention (PCI).

METHODS

The clinical data of 100 AMI patients who underwent PCI were analyzed retrospectively. According to whether major adverse cardiovascular events (MACE) occurred after PCI, they were divided into MACE group (n = 38) and non-MACE group (n = 62). Basic clinical data and serum HCG11 and miR-532-3p levels were analyzed. Multivariate Cox regression analysis was performed to evaluate the risk factors for MACE, and the receiver operator characteristic (ROC) curve was constructed to assess the clinical predictive value of HCG11 and miR-532-3p for MACE.

RESULTS

Compared with the control group, the serum HCG11 level and miR-532-3p in AMI patients were significantly increased or decreased, and the serum levels of HCG11 and miR-532-3p in the MACE group were significantly increased and decreased, compared with those in non-MACE group. Multivariate Cox regression showed that HCG11 and miR-532-3p were risk factors for MACE occurrence. ROC curve investigated that HCG11 combined with miR-532-3p has accurate predictive value for MACE.

CONCLUSION

This study showed that serum HCG11 and miR-532-3p have certain predictive value for MACE after PCI in patients with AMI.

Getting to the HEART of Major Adverse Cardiac Events

How to cite this article: Samavedam S. Getting to the HEART of Major Adverse Cardiac Events. Indian J Crit Care Med 2024;28(8):724-725.

HEART Score: Prospective Evaluation of Its Accuracy and Applicability

Background

The History, Electrocardiogram, Age, Risk factors, and Troponin I (HEART) score is a simple method to risk stratify patients with chest pain according to the risk for incidence of major adverse cardiac events (MACEs).

Materials and methods

A 202-patient prospective, single center study at Sri Siddhartha Medical College, Tumkur. Patients included were those who were presented to the emergency department (ED) due to non-traumatic chest pain, irrespective of age or any previous medical treatments, and were later referred to the cardiac care unit (CCU), cardiology department (CD). The end point of the study was the incidence of MACE.

Results

There was a high occurrence of endpoint-myocardial infarction (MI) as MACE among patients with a high-risk HEART score (p < 0.001). About 52 patients (81.3%) who had MI had a high-risk score and 2 patients (3.1%) who had an endpoint of MI had a low-risk score. Sensitivity of HEART score to anticipate MACE was 91%, and the specificity was 80%.

Conclusions

Our prospective study demonstrates the high sensitivity of the HEART score to effectively risk stratify patients and project the phenomenon of MACE. We support the use of the HEART score as a fast and accurate risk stratification tool in the ED.

How to cite this article

Anwar I, Sony D. HEART Score: Prospective Evaluation of Its Accuracy and Applicability. Indian J Crit Care Med 2024;28(8):748-752.

Ischaemic and haemorrhagic risk distribution in real-life patients with acute coronary syndromes

BACKGROUND

Effective treatment of non-ST-segment elevation acute coronary syndromes (NSTEACS) requires careful assessment of both ischaemic and bleeding risks. We aimed to analyse risk distribution and evaluate antiplatelet prescription behaviours in real-life settings.

METHODS

Data from 1100 NSTEACS patients in Buenos Aires, Argentina, from the Buenos Aires I Registry, with a 15-month follow-up, were analysed. In-hospital and 6-month GRACE scores, CRUSADE, and Precise DAPT scores were calculated.

RESULTS

The mean age was 65.4 ± 11.5 years with a majority being male (77.2%). In-hospital mortality was 2.7%, primarily due to cardiovascular causes (1.8%). Bleeding events occurred in 20.9% of patients, with 4.9% classified as ≥ BARC 3. Predominance of low bleeding (71.3%) and ischaemic (55.8%) risks on admission was observed. At 6 months, the low-risk Precise category (70.9%) and GRACE (44.1%) categories prevailed. Linear correlation analysis showed a moderately positive correlation (r = 0.61, p < .05) between ischaemic-haemorrhagic risks. Regarding the prescription of antiplatelet agents, in the low ischaemic-haemorrhagic risk group, there was a predominance of aspirin + clopidogrel (41.2%) over other high-potency antiplatelet regimens (aspirin + ticagrelor or prasugrel). In the low ischaemic and high haemorrhagic risk group, aspirin and clopidogrel were also predominant (58%).

CONCLUSIONS

Our analysis underscores the significant relationship between ischaemic and haemorrhagic risks during NSTEACS hospitalisation. Despite the majority of patients falling into the low-intermediate risk category, the prescription of P2Y12 inhibitors in real-life settings does not consistently align with these risks.

Lymphocyte-to-Red Blood Cell Ratio-The Guide Star of Acute Coronary Syndrome Prognosis

BACKGROUND

Beneath the surface of the acute ST-elevation myocardial infarction (STEMI) iceberg lies a hidden peril, obscured by the well-known cardiovascular risk factors that tip the iceberg. Before delving into the potential time bomb these risk factors represent, it is crucial to recognize the obscured danger lurking under the surface. What secrets does the STEMI iceberg hold? To unveil these mysteries, a closer look at the pathophysiology of STEMI is imperative. Inflammation, the catalyst of the STEMI cascade, sets off a chain reaction within the cardiovascular system. Surprisingly, the intricate interplay between red blood cells (RBC) and lymphocytes remains largely unexplored in previous research.

MATERIALS AND METHODS

The study encompassed 163 patients diagnosed with STEMI. Utilizing linear and logistic regression, the lymphocyte-to-red blood cell ratio (LRR) was scrutinized as a potential predictive biomarker.

RESULTS

There was a statistically significant correlation between LRR and the prognosis of STEMI patients. Building upon this discovery, an innovative scoring system was proposed that integrates LRR as a crucial parameter.

CONCLUSIONS

Uncovering novel predictive markers for both immediate and delayed complications in STEMI is paramount. These markers have the potential to revolutionize treatment strategies by tailoring them to individual risk profiles, ultimately enhancing patient outcomes.

Optimizing Acute Coronary Syndrome Patient Treatment: Leveraging Gated Transformer Models for Precise Risk Prediction and Management

BACKGROUND

Acute coronary syndrome (ACS) is a severe cardiovascular disease with globally rising incidence and mortality rates. Traditional risk assessment tools are widely used but are limited due to the complexity of the data.

METHODS

This study introduces a gated Transformer model utilizing machine learning to analyze electronic health records (EHRs) for an enhanced prediction of major adverse cardiovascular events (MACEs) in ACS patients. The model's efficacy was evaluated using metrics such as area under the curve (AUC), precision-recall (PR), and F1-scores. Additionally, a patient management platform was developed to facilitate personalized treatment strategies.

RESULTS

Incorporating a gating mechanism substantially improved the Transformer model's performance, especially in identifying true-positive cases. The TabTransformer+Gate model demonstrated an AUC of 0.836, a 14% increase in average precision (AP), and a 6.2% enhancement in accuracy, significantly outperforming other deep learning approaches. The patient management platform enabled healthcare professionals to effectively assess patient risks and tailor treatments, improving patient outcomes and quality of life.

CONCLUSION

The integration of a gating mechanism within the Transformer model markedly increases the accuracy of MACE risk predictions in ACS patients, optimizes personalized treatment, and presents a novel approach for advancing clinical practice and research.

Sex- and Age-Specific Differences in Risk Profiles and Early Outcomes in Adults With Acute Coronary Syndromes

BACKGROUND

Adults <55 years of age comprise a quarter of all acute coronary syndromes (ACS) hospitalisations. There is a paucity of data characterising this group, particularly sex differences. This study aimed to compare the clinical and risk profile of patients with ACS aged <55 years with older counterparts, and measure short-term outcomes by age and sex.

METHOD

The study population comprised patients with ACS enrolled in the AUS-Global Registry of Acute Coronary Events (GRACE), Cooperative National Registry of Acute Coronary Syndrome Care (CONCORDANCE) and SNAPSHOT ACS registries. We compared clinical features and combinations of major modifiable risk factors (hypertension, smoking, dyslipidaemia, and diabetes) by sex and age group (20-54, 55-74, 75-94 years). All-cause mortality and major adverse events were identified in-hospital and at 6-months.

RESULTS

There were 16,658 patients included (22.3% aged 20-54 years). Among them, 20-54 year olds had the highest proportion of ST-elevation myocardial infarction compared with sex-matched older age groups. Half of 20-54 year olds were current smokers, compared with a quarter of 55-74 year olds, and had the highest prevalence of no major modifiable risk factors (14.2% women, 12.7% men) and of single risk factors (27.6% women, 29.0% men), driven by smoking. Conversely, this age group had the highest proportion of all four modifiable risk factors (6.6% women, 4.7% men). Mortality at 6 months in 20-54 year olds was similar between men (2.3%) and women (1.7%), although lower than in older age groups.

CONCLUSIONS

Younger adults with ACS are more likely to have either no risk factor, a single risk factor, or all four modifiable risk factors, than older patients. Targeted risk factor prevention and management is warranted in this age group.

Can GRACE Risk Score Predict Mortality and the Need for Thrombolytic Treatment in Acute Pulmonary Embolism?

Acute coronary syndrome and pulmonary embolism (PE) are clinical entities sharing similar presentation and risk factors. Risk scores and indexes help to identify disease severity in both diseases. In this study, we aimed to evaluate if the Global Registry of Acute Coronary Events (GRACE) risk score could predict 30-day mortality and the need for thrombolytic treatment in patients with acute PE. Patients hospitalized with a diagnosis of PE in our tertiary center between January 2018 and May 2022 were included in this retrospective study. Pulmonary Embolism Severity Index (PESI) and GRACE risk scores on admission were calculated using clinical, electrocardiographic, and laboratory parameters for each patient. A total of 197 patients were included. The 30-day mortality rate was 28.4% whereas 32.5% of the patients required thrombolytic treatment. GRACE and PESI scores were found independent risk factors associated with 30-day mortality and the need for thrombolytic treatment. A cut-off value of 160.5 for GRACE score was associated with 88.5% sensitivity and 89.4% specificity in prediction of 30-day mortality. In contrast, GRACE score had 61.0% sensitivity and 60.0% specificity in the prediction of the need for thrombolytic treatment when the cut-off value was 147. In conclusion, GRACE risk score has an effective discriminating power in determining the early mortality of patients with acute PE. The incidence of short-term PE-related mortality was significantly increased in patients with high GRACE risk scores. Concomitant use of GRACE and PESI risk scores may aid in defining patients with high-risk PE and help predict poor prognosis with high specificity and probability.

Comparison of heart, grace and TIMI scores to predict major adverse cardiac events from chest pain in a Spanish health care region

Acute non-traumatic chest pain (ANTCP) is the second cause of consultation in the Emergency department (ED). About 70% of all Acute Myocardial Infarctions present as non persistent ST-elevation acute coronary syndrome (NSTE-ACS) in the electrocardiogram. Our aim was to compare whether the HEART risk score is more effective than the GRACE and TIMI scores for the diagnosis and prognosis of Major Adverse Cardiac Events (MACE) at six weeks in patients with ANTCP and NSTE-ACS. A prospective cohort study was conducted with patients with ANTCP that attended an ED and a Primary Care Emergency Center (PCEC) from April 2018 to December 2020. The primary outcome was MACE at six weeks. Diagnostic performance was calculated for each scale as the Area under the Receiver Operating Characteristic (ROC) curve (AUC), sensitivity (SE), specificity (SP), and predictive values (PV). Qualitative variables were compared using the Chi-square test, and continuous variables were compared using the nonparametric Kruskal-Wallis test. We adjusted a logistic regression for risk groups, age, and gender to determine the effect of the HEART, GRACE, and TIMI scores on MACE. The degree of agreement (kappa index) was calculated in the categorical classification of patients according to the three risk scales. Cox proportional hazards regressions were performed for each scale and were compared using partial likelihood ratio tests for non-nested models. From a sample of 317 patients with ANTCP, 14.82% had MACE at six weeks. The AUC was 0.743 (95% CI 0.67-0.81) for the HEART score, 0.717 (95% CI 0.64-0.79) for the TIMI score, and 0.649 (95% CI 0.561-0.738) for the GRACE score. The HEART scale identified low-risk patients with a higher SE and negative PV than the GRACE and TIMI scores. The HEART scale was better than the GRACE and TIMI scores at diagnosing and predicting MACE at six weeks in patients with ANTCP and probable NSTE-ACS. It was also a reliable tool for risk stratification in low-risk patients. Its application is feasible in EDs and PCECs, avoiding the need for complementary tests and their associated costs without compromising patient health.

Research priorities for the secondary prevention and management of acute rheumatic fever and rheumatic heart disease: a National Heart, Lung, and Blood Institute workshop report

Secondary prevention of acute rheumatic fever (ARF) and rheumatic heart disease (RHD) involves continuous antimicrobial prophylaxis among affected individuals and is recognised as a cornerstone of public health programmes that address these conditions. However, several important scientific issues around the secondary prevention paradigm remain unresolved. This report details research priorities for secondary prevention that were developed as part of a workshop convened by the US National Heart, Lung, and Blood Institute in November 2021. These span basic, translational, clinical and population science research disciplines and are built on four pillars. First, we need a better understanding of RHD epidemiology to guide programmes, policies, and clinical and public health practice. Second, we need better strategies to find and diagnose people affected by ARF and RHD. Third, we urgently need better tools to manage acute RF and slow the progression of RHD. Fourth, new and existing technologies for these conditions need to be better integrated into healthcare systems. We intend for this document to be a reference point for research organisations and research sponsors interested in contributing to the growing scientific community focused on RHD prevention and control.

Diagnostic Impact of Hs-CRP and IL-6 for Acute Coronary Syndrome in Patients Admitted to the ED with Chest Pain: Added Value to the HEART Score?

Objective

To investigate whether hs-CRP and IL-6 provide additional diagnostic value beyond that achieved by the HEART score in patients with chest pain suggestive of acute coronary syndrome (ACS) admitted to the emergency department (ED).

Methods

This was a post hoc analysis using data from the RACING-MI study. Baseline data, including hs-CRP and IL-6 levels, were analyzed using the plasma from the biobank. A total of 818 patients with chest pain suggestive of ACS were included in this analysis. Of these, 98 were diagnosed with ACS (12%). Logistic regression was used to identify the independent predictors of ACS development in patients with chest pain.

Results

hs-CRP levels >2 mg/L were observed in 50% of all ACS cases. IL-6 levels >1.3 pg/mL were observed in 71% of all ACS cases. hs-CRP had a sensitivity of 50% and specificity of 51% for the diagnosis of ACS, whereas IL-6 had a sensitivity of 71% and specificity of 29%. The diagnostic likelihood ratios for ACS was 1.0 for hs-CRP>2 mg/L and IL-6 > 1.3 pg/mL, respectively. Logistic regression analysis revealed that age, male gender, and ongoing smoking were associated with ACS in patients with acute chest pain. No association was found between IL-6 or hs-CRP level and ACS. This was observed for both IL-6 and hs-CRP, whether assessed on a continuous scale or using prespecified cut-off values.

Conclusion

Among the 818 patients admitted to the ED with chest pain suggestive of ACS, neither hs-CRP nor IL-6 provided an independent added diagnostic value. Our results suggest that inflammatory markers have limited diagnostic value in detecting patients with ACS in the ED.

Clinical Efficacy of Pre-Hospital Electrocardiogram Transmission in Patients Undergoing Primary Percutaneous Coronary Intervention for ST-Segment Elevation Myocardial Infarction

Rapid reperfusion by primary percutaneous coronary intervention (pPCI) is an established strategy for the treatment of patients with ST-segment elevation myocardial infarction (STEMI). Pre-hospital electrocardiogram (PH-ECG) transmission by the emergency medical services (EMS) facilitates timely reperfusion in these patients. However, evidence regarding the clinical benefits of PH-ECG in individual hospitals is limited.This retrospective, observational study investigated the clinical efficacy of PH-ECG in STEMI patients who underwent pPCI. Of a total of 382 consecutive STEMI patients, 237 were enrolled in the study and divided into 2 groups: a PH-ECG group (n = 77) and non-PH-ECG group (n = 160). Door-to-balloon time (D2BT) was significantly shorter in the PH-ECG group (66 [52-80] min), compared to the non-PH-ECG group (70 [57-88] minutes, P = 0.01). The 30-day all-cause mortality rate was 6% in the PH-ECG group, which was significantly lower than that in the non-PH-ECG group (16%) (P = 0.037, hazard ratio [HR]: 0.38, 95% CI: 0.15-0.98). This trend was particularly evident in severely ill patients when stratified by GRACE score.The use of PH-ECG improved the survival rate of STEMI patients undergoing pPCI due to the improved pre-arrival preparation based on the EMS information. Coordination between EMS and PCI-capable institutes is essential for the management of PH-ECG.

Social Determinants of Health and Mortality After Premature and Non-premature Acute Coronary Syndrome

Objective

To describe and compare the determinants of 1-year mortality after premature vs non-premature acute coronary syndrome (ACS).

Patients and Methods

Participants presenting with ACS were enrolled in a prospective registry of 29 hospitals in 4 countries, from January 22, 2012 to January 22, 2013, with 1-year of follow-up data. The primary outcome was all-cause 1-year mortality after premature ACS (men aged <55 years and women aged <65 years) and non-premature ACS (men aged ≥55 years and women aged ≥65 years). The associations between the baseline patient characteristics and 1-year mortality were analyzed in models adjusting for the Global Registry of Acute Coronary Events (GRACE) score and reported as adjusted odds ratio (aOR) (95% CI).

Results

Of the 3868 patients, 43.3% presented with premature ACS that was associated with lower 1-year mortality (5.7%) than those with non-premature ACS. In adjusted models, women experienced higher mortality than men after premature (aOR, 2.14 [1.37-3.41]) vs non-premature ACS (aOR, 1.28 [0.99-1.65]) (P interaction=.047). Patients lacking formal education vs any education had higher mortality after both premature (aOR, 2.92 [1.87-4.61]) and non-premature ACS (aOR, 1.78 [1.36-2.34]) (P interaction=.06). Lack of employment vs any employment was associated with approximately 3-fold higher mortality after premature and non-premature ACS (P interaction=.72). Using stepwise logistic regression to predict 1-year mortality, a model with GRACE risk score and 4 characteristics (education, employment, body mass index [kg/m2], and statin use within 24 hours after admission) had higher discrimination than the GRACE risk score alone (area under the curve, 0.800 vs 0.773; P comparison=.003).

Conclusion

In this study, women, compared with men, had higher 1-year mortality after premature ACS. The social determinants of health (no formal education or employment) were strongly associated with higher 1-year mortality after premature and non-premature ACS, improved mortality prediction, and should be routinely considered in risk assessment after ACS.

A Global Overview of Acute Coronary Syndrome Registries: A Systematic Review

The present study was conducted with the aim of identifying, and summarizing the characteristics of ACS registries at national, multinational and international levels. Literature was searched using keywords in the title and/or abstract without any time limit ending in March, 2021. After excluding duplicates, 2 reviewers independently reviewed the titles and/or abstracts and full text for inclusion. Each reviewer independently extracted the characteristics of the registries from included papers. Finally, the extracted characteristics were confirmed by a second reviewer. Out of the 1309 papers included, 71 ACS registries were identified (including 60 national and 11 multinational and international registries). Most national registries were being used in Europe. Most registries focused on measuring quality. In more than half of the registries, all types of ACS patients were enrolled. The diagnostic and drug classification systems were mentioned in eight and five registries, respectively. The design of 55 registries was hospital-based. The ability of computerized audit checks was made for 34 registries. More than half of the registries had patient consent and had a web-based design. In all the ACS registries, patient characteristics, clinical characteristics and treatment characteristics were recorded and post-discharge follow-up information was recorded in 45 registries. In the current situation and given that a limited number of countries in the world have national ACS registries, reviewing the results of this study and modeling the registries implemented in the leading countries can help countries without a registry to design it.

Role and relevance of risk stratification models in the modern-day management of non-ST elevation acute coronary syndromes

We summarise the international guidelines surrounding risk stratification as well as discuss new emerging data for future development of a new risk model in the management of patients with non-ST segment elevation acute coronary syndrome (NSTE-ACS). NSTE-ACS accounts for the bulk of acute coronary syndrome presentations in the UK, but management strategies in this group of patients have remained a subject of debate for decades. Patients with NSTE-ACS represent a heterogeneous population with a wide variation in short-term and long-term clinical outcomes, which makes a uniform, standardised treatment approach ineffective and inappropriate. Studies in the modern era have provided some guidance in treating this subset of patients: the provision of early, more potent therapies has been shown to improve outcomes in patients at a particularly elevated risk of adverse outcomes. International guidelines recommend adopting an individualised treatment approach through the use of validated risk prediction models to identify such patients at high risk of adverse outcomes. The present available evidence, however, is based on dated demographics, different diagnostic thresholds and outdated therapies. In particular, the evidence has limited applicability to female patients and older people with frailty. Moreover, the current risk models do not capture key prognostic variables, leading to an inaccurate estimation of patients' baseline risk and subsequent mistreatment. Therefore, the current risk models are no longer fit for purpose and there is a need for risk prediction scores that account for different population demographics, higher sensitivity troponin assays and contemporary treatment options.

Age-Related Mortality in STEMI Patients: Insight from One Year of HUB Centre Experience during the Pandemic

Background: Old patients have a poor prognosis when affected by ST elevation myocardial infarction (STEMI). The aim of our study was to evaluate the impact of age on acute and mid-term mortality in STEMI patients over one year in the pandemic period. Methods: we collected data on 283 STEMI patients divided into three groups according to age (not old, “Not-O”, ≤74 y/o; old, “O”, 75−84 y/o; very old, “Very-O”, ≥85 y/o). Results: the three groups did not differ in their clinical or procedural characteristics. The Very-O patients had a significantly increased incidence of in-hospital MACE (35%), mortality (30.0%), and percentage of cardiac death (25.0%). The only two independent predictors of in-hospital mortality were the ejection fraction (EF) [OR:0.902 (95% CI) 0.868−0.938; p < 0.0001] and COVID-19 infection [OR:3.177 (95% CI) 1.212−8.331; p = 0.019]. At follow-up (430 +/− days), the survival rates were decreased significatively among the age groups (Not-O 2.9% vs. O 14.8% vs. Very-O 28.6%; p < 0.0001), and the only two independent predictors of the follow-up mortality were the EF [OR:0.935 (95% CI) 0.891−0.982; p = 0.007] and age [OR:1.06 (95% CI) 1.018−1.110; p = 0.019]. Conclusions: in very old patients, all the accessory procedures that may be performed should be accurately and independently weighed up in terms of the risk−benefit balance and the real impact on the quality of life because of the poor mid-term prognosis.

Patient-oriented risk score for predicting death 1 year after myocardial infarction: the SweDen risk score

OBJECTIVES

Our aim was to derive, based on the SWEDEHEART registry, and validate, using the Western Denmark Heart registry, a patient-oriented risk score, the SweDen score, which could calculate the risk of 1-year mortality following a myocardial infarction (MI).

METHODS

The factors included in the SweDen score were age, sex, smoking, diabetes, heart failure and statin use. These were chosen a priori by the SWEDEHEART steering group based on the premise that the factors were information known by the patients themselves. The score was evaluated using various statistical methods such as time-dependent receiver operating characteristics curves of the linear predictor, area under the curve metrics, Kaplan-Meier survivor curves and the calibration slope.

RESULTS

The area under the curve values were 0.81 in the derivation data and 0.76 in the validation data. The Kaplan-Meier curves showed similar patient profiles across datasets. The calibration slope was 1.03 (95% CI 0.99 to 1.08) in the validation data using the linear predictor from the derivation data.

CONCLUSIONS

The SweDen risk score is a novel tool created for patient use. The risk score calculator will be available online and presents mortality risk on a colour scale to simplify interpretation and to avoid exact life span expectancies. It provides a validated patient-oriented risk score predicting the risk of death within 1 year after suffering an MI, which visualises the benefit of statin use and smoking cessation in a simple way.

Implementation of an All-Day Artificial Intelligence-Based Triage System to Accelerate Door-to-Balloon Times

OBJECTIVE

To implement an all-day artificial intelligence (AI)-based system to facilitate chest pain triage in the emergency department.

METHODS

The AI-based triage system encompasses an AI model combining a convolutional neural network and long short-term memory to detect ST-elevation myocardial infarction (STEMI) on electrocardiography (ECG) and a clinical risk score (ASAP) to prioritize patients for ECG examination. The AI model was developed on 2907 twelve-lead ECGs: 882 STEMI and 2025 non-STEMI ECGs.

RESULTS

Between November 1, 2019, and October 31, 2020, we enrolled 154 consecutive patients with STEMI: 68 during the AI-based triage period and 86 during the conventional triage period. The mean ± SD door-to-balloon (D2B) time was significantly shortened from 64.5±35.3 minutes to 53.2±12.7 minutes (P=.007), with 98.5% vs 87.2% (P=.009) of D2B times being less than 90 minutes in the AI group vs the conventional group. Among patients with an ASAP score of 3 or higher, the median door-to-ECG time decreased from 30 minutes (interquartile range [IQR], 7-59 minutes) to 6 minutes (IQR, 4-30 minutes) (P<.001). The overall performances of the AI model in identifying STEMI from 21,035 ECGs assessed by accuracy, precision, recall, area under the receiver operating characteristic curve, F1 score, and specificity were 0.997, 0.802, 0.977, 0.999, 0.881, and 0.998, respectively.

CONCLUSION

Implementation of an all-day AI-based triage system significantly reduced the D2B time, with a corresponding increase in the percentage of D2B times less than 90 minutes in the emergency department. This system may help minimize preventable delays in D2B times for patients with STEMI undergoing primary percutaneous coronary intervention.

Clinical Validation of the Shock Index, Modified Shock Index, Delta Shock Index, and Shock Index-C for Emergency Department ST-Segment Elevation Myocardial Infarction

Background: ST-segment elevation myocardial infarction (STEMI) is a leading cause of death worldwide. A shock index (SI), modified SI (MSI), delta-SI, and shock index-C (SIC) are known predictors of STEMI. This retrospective cohort study was designed to compare the predictive value of the SI, MSI, delta-SI, and SIC with thrombolysis in myocardial infarction (TIMI) risk scales. Method: Patients > 20 years old with STEMI who underwent percutaneous coronary intervention (PCI) were included. Receiver operating characteristic (ROC) curve analysis with the Youden index was performed to calculate the optimal cutoff values for these predictors. Results: Overall, 1552 adult STEMI cases were analyzed. The thresholds for the emergency department (ED) SI, MSI, SIC, and TIMI risk scales for in-hospital mortality were 0.75, 0.97, 21.00, and 5.5, respectively. Accordingly, ED SIC had better predictive power than the ED SI and ED MSI. The predictive power was relatively higher than TIMI risk scales, but the difference did not achieve statistical significance. After adjusting for confounding factors, the ED SI > 0.75, MSI > 0.97, SIC > 21.0, and TIMI risk scales > 5.5 were statistically and significantly associated with in-hospital mortality of STEMI. Compared with the ED SI and MSI, SIC (>21.0) had better sensitivity (67.2%, 95% CI, 58.6−75.9%), specificity (83.5%, 95% CI, 81.6−85.4%), PPV (24.8%, 95% CI, 20.2−29.6%), and NPV (96.9%, 95% CI, 96.0−97.9%) for in-hospital mortality of STEMI. Conclusions: SIC had better discrimination ability than the SI, MSI, and delta-SI. Compared with the TIMI risk scales, the ACU value of SIC was still higher. Therefore, SIC might be a convenient and rapid tool for predicting the outcome of STEMI.

Prognostic value of GRACE risk score in patients hospitalized for coronavirus disease 2019

OBJECTIVE

COVID-19 pandemic continues to threaten human health as novel mutant variants emerge and disease severity ranges from asymptomatic to fatal. Thus, studies are needed to identify the patients with ICU need as well as those who have subsequent mortality. Global Registry of Acute Coronary Events (GRACE) risk score is a validated score in acute coronary syndrome. We aimed to evaluate if GRACE score can indicate adverse outcomes and major ischemic events in hospitalized COVID-19 patients.

METHODS

All hospitalized patients due to COVID-19 at our institution between March 2020 and September 2020 were included in this retrospective study. Patients were grouped according to GRACE risk scores: low risk 0-108 points, intermediate risk 109-140 and high risk ≥141.

RESULTS

A total of 787 patients were enrolled; 434 patients formed group 1. One-hundred forty-one patients in group 2 and 212 patients formed group 3. We found that inhospital mortality, length of hospital stay, ICU and advanced ventilatory support need were associated with increasing GRACE risk score. In addition, major ischemic events were more frequently observed in higher risk groups and strong positive correlations between GRACE risk score and pro-BNP, procalcitonin and moderate positive correlation with D-dimer, CRP, NLR was found. Regression analysis showed that only GRACE risk score was an independent risk factor associated with inhospital mortality, major ischemic events, advanced ventilatory support and ICU need.

CONCLUSION

The GRACE risk score is easy to apply on hospital admission and useful for classifying those in medium-high-intensity care units and to raise the assignments of sources.

Prognostic value of myocardial salvage index assessed by cardiovascular magnetic resonance in reperfused ST-segment elevation myocardial infarction

Aims

Cardiovascular magnetic resonance (CMR) is a powerful tool to quantify the myocardial area at risk (AAR) and infarct size (IS), and evaluate the extent of myocardial salvage in acute ST-segment elevation myocardial infarction (STEMI). This study aimed to assess the prognostic value of myocardial salvage index (MSI) assessed by CMR in reperfused STEMI and investigate whether MSI could improve the predictive efficacy of the Global Registry of Acute Coronary Events (GRACE) risk score.

Methods and results:

About 104 consecutive patients who were hospitalized with first-time STEMI and received reperfusion therapy were prospectively enrolled. The primary endpoint was the incident of major adverse cardiovascular event (MACE) including all-cause mortality, non-fatal myocardial reinfarction and congestive heart failure within 36 months after the index event. Cox regression analysis was used to evaluate the prognostic association of MSI with MACE risk. About 21 (20.2%) patients developed MACE during the 3-year follow-up period, and patients with MSI &lt; median had a higher incidence of MACE than those with MSI ≥ median [16 (30.8%) vs. 5 (9.6%), P = 0.007]. After adjusting all the parameters associated with MACE in univariate Cox analysis, MSI assessed by CMR remained independently significant as a predictor of MACE in multivariate Cox analysis (hazard ratio 0.963, 95% CI: 0.943–0.983; P &lt; 0.001). Adding MSI to the GRACE risk score significantly increased the prognostic accuracy of the GRACE risk score (area under the curve: 0.833 vs. 0.773; P = 0.044), with a net reclassification improvement of 0.635 (P = 0.009) and an integrated discrimination improvement of 0.101 (P = 0.002).

Conclusion

This study confirmed that MSI assessed by CMR had a good long-term prognostic value in reperfused STEMI and improve the prognostic performance of the GRACE risk score.

The Level of HbA1c Evaluates the Extent of Coronary Atherosclerosis Lesions and the Prognosis in Diabetes with Acute Coronary Syndrome

Background

The level of HbA1c can reflect the average level of blood glucose over 3 months, which is the gold standard indicator for monitoring blood glucose. The relationship between the level of HbA1c and the extent of coronary atherosclerosis lesions or the prognosis in diabetes with acute coronary syndrome (ACS) remains poorly understood.

Aims

To explore whether the level of HbA1c can evaluate the extent of coronary atherosclerosis lesions or the prognosis in diabetes with acute coronary syndrome (ACS) using the SYNTAX score, the Global Registry of Acute Coronary Events (GRACE) score, left ventricular function (LVEF), left ventricular end-diastolic volume (LVEDV), and major adverse cardiac events (MACEs) in the hospital and 12 months after discharge.

Methods

This study was a prospective, randomized, open-label, and parallel group study. Patients with diabetes with ACS were recruited into this study indiscriminately, and all the participants were divided into two groups according to the level of HbA1c: HbA1c level ≤ 7%group and HbA1c level > 7%group. The followings were used as the evaluation indicators: SYNTAX score, GRACE score, LVEF, LVEDV, and MACEs in hospital and 12 months after discharge.

Results

A total of 233 patients with diabetes and ACS were enrolled and assigned to two groups according to their level of HbA1c: the HbA1c ≤ 7%group (n = 92) and the HbA1c > 7%group (n = 141). The results showed that the proportion of STEMI was higher in the HbA1c ≤7% group (p < 0.05), while the proportion of NSTEMI has not significantly higher in the HbA1c >7% group (p > 0.05). Regression analysis indicated that HbA1c level was significantly positively correlated with GRACE score (r = 0.156, F = 5.784, p = 0.017, n = 233) and SYNTAX score (r = 0.237, F = 13.788, p < 0.001, n = 233), and there were no statistically significant differences in LVEDV and LVEF between the two groups (p > 0.05). The total MACEs rate showed no significant difference between the two groups during hospitalization (p > 0.05) but showed significant differences at 12 months after discharge (p < 0.05).

Conclusions

This study shows that HbA1c level was positively correlated with the extent of coronary atherosclerosis lesions and the prognosis in diabetes with ACS. The higher the HbA1c level is, the more severe the coronary atherosclerotic lesion and the worse the prognosis in diabetes with ACS are.

Chest pain in the emergency department: From score to core-A prospective clinical study

High-sensitivity troponin assay brought new challenges as we detect elevated concentration in many other diseases, and it became difficult to distinguish the real cause of this elevation. In this notion, diagnosis of acute coronary syndrome (ACS) remains a challenge in emergency department (ED). We aim to examine different approaches for rule-in and rule-out of ACS using risk scores, copeptin, and coronary computed tomography angiography (CCTA). A prospective observational study was designed to evaluate chest pain patients. Consecutive adult patients admitted to the ED with a chief complaint of chest pain due to any cause were included. All patients were followed-up for 6 months after discharge for major adverse cardiovascular events and readmissions. Admission data, ED processes, and diagnoses were analyzed. One hundred forty-six patients were included, average age was 63 ± 13.4 years, and 95 (65.1%) were male. Global Registry of Acute Coronary Events (GRACE) and History, ECG, Age, Risk factors, Troponin (HEART) scores showed good prognostic abilities, but HEART combination with copeptin improves diagnoses of myocardial infarction (area under the curve [AUC] 0.764 vs AUC 0.864 P = .0008). Patients with elevated copeptin were older, had higher risk scores, and were more likely to be admitted to hospital and diagnosed with ACS in ED. For copeptin, AUC was 0.715 (95% confidence interval 0.629-0.803), and for combination with troponin, AUC of 0.770 (0.703-0.855) did not improve rule-in of myocardial infarction. High-sensitivity troponin I assay alongside prior stroke, history of carotid stenosis, dyslipidemia, use of diuretics, and electrocardiogram changes (left bundle branch block or ST depression) are good predictors of myocardial infarction (χ² = 52.29, AUC = 0.875 [0.813-0.937], P < .001). The regression analysis showed that combination of copeptin and CCTA without significant stenosis can be used for ACS rule-out (χ² = 26.36, P < .001, AUC = 0.772 [0.681-0.863], negative predictive value of 96.25%). For rule-in of ACS, practitioner should consider not only scores for risk stratification but carefully analyze medical history and nonspecific electrocardiogram changes and even with normal troponin results, we strongly suggest thorough evaluation in chest pain unit. For rule-out of ACS combination of copeptin and CCTA holds great potential.

Risk assessment in COVID-19: Prognostic importance of cardiovascular parameters

BACKGROUND

Cardiovascular risk factors and comorbidities are highly prevalent among COVID-19 patients and are associated with worse outcomes.

HYPOTHESIS

We therefore investigated if established cardiovascular risk assessment models could efficiently predict adverse outcomes in COVID-19. Furthermore, we aimed to generate novel risk scores including various cardiovascular parameters for prediction of short- and midterm outcomes in COVID-19.

METHODS

We included 441 consecutive patients diagnosed with SARS-CoV-2 infection. Patients were followed-up for 30 days after the hospital admission for all-cause mortality (ACM), venous/arterial thromboembolism, and mechanical ventilation. We further followed up the patients for post-COVID-19 syndrome for 6 months and occurrence of myocarditis, heart failure, acute coronary syndrome (ACS), and rhythm events in a 12-month follow-up. Discrimination performance of DAPT, GRACE 2.0, PARIS-CTE, PREDICT-STABLE, CHA2-DS2-VASc, HAS-BLED, PARIS-MB, PRECISE-DAPT scores for selected endpoints was evaluated by ROC-analysis.

RESULTS

Out of established risk assessment models, GRACE 2.0 score performed best in predicting combined endpoint and ACM. Risk assessment models including age, cardiovascular risk factors, echocardiographic parameters, and biomarkers, were generated and could successfully predict the combined endpoint, ACM, venous/arterial thromboembolism, need for mechanical ventilation, myocarditis, ACS, heart failure, and rhythm events. Prediction of post-COVID-19 syndrome was poor.

CONCLUSION

Risk assessment models including age, laboratory parameters, cardiovascular risk factors, and echocardiographic parameters showed good discrimination performance for adverse short- and midterm outcomes in COVID-19 and outweighed discrimination performance of established cardiovascular risk assessment models.

Use of anticoagulant drugs in patients with atrial fibrillation. Does adherence to therapy have a prognostic impact?

Anticoagulant therapy represents a pivotal element that strongly influences the thromboembolic risk of non-valvular atrial fibrillation (NVAF) subjects. The main purpose of this review was to identify issues and suggest strategies to improve the oral anticoagulants (OACs) treatment adherence, which is the most important predictor of NVAF outcome. Advantages, efficacy, and impact of these drugs on patients' prognosis were revealed in important clinical trials on large cohorts of patients and are often prescribed nowadays. A real-life data registry, the Global Anticoagulant Registry in the Field-Atrial Fibrillation (GARFIELD-AF) analyzed the profile and outcome of patients diagnosed with NVAF receiving oral antithrombotic treatment. The observations gathered in the registry were crucial for identifying relevant elements that clinicians must improve, such as adherence strategies and predisposing factors that correlated with stroke. Adherence to OACs in AF patients is essential from the viewpoint of clinical efficacy and safety. Major adverse events and negative outcome are correlated with a weak anticoagulation control caused by an ineffective treatment adherence strategy. Solving the issue of oral anticoagulation adherence is possible using new technologies, but future directions should be explored. Mobile phone applications centered on patients' needs, telemedicine programs that evaluate patients' evolution and detect adverse reactions or events, encouraging an adequate management of the event without interruption of OACs, represent perspectives with a major impact on treatment adherence.

Temporal Trends of Major Bleeding and Its Prediction by the Academic Research Consortium-High Bleeding Risk Criteria in Acute Myocardial Infarction

Limited data exist on the temporal trend of major bleeding and its prediction by the Academic Research Consortium-High Bleeding Risk (ARC-HBR) criteria in acute myocardial infarction (AMI) patients undergoing percutaneous coronary intervention (PCI). We investigated 10-year trends of major bleeding and predictive ability of the ARC-HBR criteria in AMI patients. In a multicenter registry of 10,291 AMI patients undergoing PCI between 2004 and 2014 the incidence of Bleeding Academic Research Consortium (BARC) 3 and 5 bleeding was assessed, and, outcomes in ARC-defined HBR patients with AMI were compared with those in non-HBR. The primary outcome was BARC 3 and 5 bleeding at 1 year. Secondary outcomes included all-cause mortality and composite of cardiovascular death, myocardial infarction, or ischemic stroke. The annual incidence of BARC 3 and 5 bleeding in the AMI population has increased over the years (1.8% to 5.8%; p < 0.001). At 1 year, ARC-defined HBR (n = 3371, 32.8%) had significantly higher incidence of BARC 3 and 5 bleeding (9.8% vs. 2.9%; p < 0.001), all-cause mortality (22.8% vs. 4.3%; p < 0.001) and composite of ischemic events (22.6% vs. 5.8%; p < 0.001) compared to non-HBR. During the past decade, the incidence of major bleeding in the AMI population has increased. The ARC-HBR criteria provided reliable predictions for major bleeding, mortality, and ischemic events in AMI patients.

Translational research in nephrology: prognosis

Translational research aims at reducing the gap between the results of studies focused on diagnosis, prognosis and therapy, and every day clinical practice. Prognosis is an essential component of clinical medicine. It aims at estimating the risk of adverse health outcomes in individuals, conditional to their clinical and non-clinical characteristics. There are three fundamental steps in prognostic research: development studies, in which the researcher identifies predictors, assigns the weights to each predictor, and assesses the model’s accuracy through calibration, discrimination and risk reclassification; validation studies, in which investigators test the model’s accuracy in an independent cohort of individuals; and impact studies, in which researchers evaluate whether the use of a prognostic model by clinicians improves their decision-making and patient outcome. This article aims at clarifying how to reduce the disconnection between the promises of prognostic research and the delivery of better individual health.

Additive value of bioclinical risk scores to high sensitivity troponins-only strategy in acute coronary syndrome

BACKGROUND

Discharging patients home as quickly as possible, or gaining the ability to eliminate a serious event is a goal requested by clinicians in the emergency department (ED). For this, risk scores, taking into account co-morbidities, have been established. The aim of our study consists to evaluate in patients with chest pain admitted in ED the risk stratification obtained with clinico-biological risk scores (CCS, GRACE score, TIMI score and HEART score) using Ortho hs-cTnI assay (Ortho Clinical Diagnostics, Illkirch, France) on the Vitros 3600® instrument or Roche hs-cTnT assay on the Cobas8000/e801® module (Roche diagnostics, Meylan, France), with comparison to hs-cTn-only strategy. Prognostic performances were evaluated according to AMI with or without STEMI, and deaths during hospitalization.

METHODS

Patients admitted to the ED presenting chest pain or symptoms suggesting of acute coronary syndrome (ACS) were included. Hs-cTnT was performed on a Roche hs-cTnT assay on the Cobas8000/e801® module using a fifth-generation assay and was used for the clinical diagnosis. In addition, hs-cTnI was tested using Ortho hs-cTnI assay on the Vitros 3600® analyzer. Retrospectively, we collected the variables needed for each score in clinical records. Our endpoint were occurrence of AMI in patients with chest pain after presentation to the ED and all cause death during the hospitalization.

RESULTS

We enrolled 160 patients with suspected ACS. The adjudicated diagnosis was AMI in 37 patients (with 9 STEMI and 28 NSTEMI), cardiac pathologies in 57 patients and other causes in 66 patients. The majority of patients were classified at high risk for each risk scores (from 42% to 68%) whatever the considered hs-cTn assay, except for TIMI score. Cohen's kappa agreements with GRACE, TIMI and HEART scores were excellent between Roche hs-cTnT vs Ortho hs-cTnI. The AUC of the HEART score was highest for both hs-cTn to predict AMI, NSTEMI or death, with no statistical difference according to the hs-cTn (p = NS) assay used. NRI analysis confirmed the interest of HEART score which improved individual risk prediction for AMI (or NSTEMI) and death.

CONCLUSION

In view of our results, the decision aids using only biological variables (hs-cTn-only strategy and CCS) would seem more effective for rule-out AMI whereas bioclinical risk scores could better identify patients at low and high risk for mortality. In consequence, risk scores taking in account comorbidities, appear necessary to determine the outcome and thus to adapt the therapeutic options. It is interesting to note that the HEART score could be useful for the rule out AMI but also for the risk prediction as confirmed by the NRI.

A machine learning model to predict critical care outcomes in patient with chest pain visiting the emergency department

Background

Currently, the risk stratification of critically ill patient with chest pain is a challenge. We aimed to use machine learning approach to predict the critical care outcomes in patients with chest pain, and simultaneously compare its performance with HEART, GRACE, and TIMI scores.

Methods

This was a retrospective, case-control study in patients with acute non-traumatic chest pain who presented to the emergency department (ED) between January 2017 and December 2019. The outcomes included cardiac arrest, transfer to ICU, and death during treatment in ED. In the randomly sampled training set (70%), a LASSO regression model was developed, and presented with nomogram. The performance was measured in both training set (70% participants) and testing set (30% participants), and findings were compared with the three widely used scores.

Results

We proposed a LASSO regression model incorporating mode of arrival, reperfusion therapy, Killip class, systolic BP, serum creatinine, creatine kinase-MB, and brain natriuretic peptide as independent predictors of critical care outcomes in patients with chest pain. Our model significantly outperformed the HEART, GRACE, TIMI score with AUC of 0.953 (95%CI: 0.922–0.984), 0.754 (95%CI: 0.675–0.832), 0.747 (95%CI: 0.664–0.829), 0.735 (95%CI: 0.655–0.815), respectively. Consistently, our model demonstrated better outcomes regarding the metrics of accuracy, sensitivity, specificity, positive predictive value, negative predictive value, and F1 score. Similarly, the decision curve analysis elucidated a greater net benefit of our model over the full ranges of clinical thresholds.

Conclusion

We present an accurate model for predicting the critical care outcomes in patients with chest pain, and provide substantial support to its application as a decision-making tool in ED.

Angiopoietin-2 and angiopoietin-like 4 protein provide prognostic information in patients with suspected acute coronary syndrome

BACKGROUND

Plasma levels of angiopoietin-2 (ANGPT2) and angiopoietin-like 4 protein (ANGPTL4) reflect different pathophysiological aspects of cardiovascular disease. We evaluated their association with outcome in a hospitalized Norwegian patient cohort (n = 871) with suspected acute coronary syndrome (ACS) and validated our results in a similar Argentinean cohort (n = 982).

METHODS

A cox regression model, adjusting for traditional cardiovascular risk factors, was fitted for ANGPT2 and ANGPTL4, respectively, with all-cause mortality and cardiac death within 24 months and all-cause mortality within 60 months as the dependent variables.

RESULTS

At 24 months follow-up, 138 (15.8%) of the Norwegian and 119 (12.1%) of the Argentinian cohort had died, of which 86 and 66 deaths, respectively, were classified as cardiac. At 60 months, a total of 259 (29.7%) and 173 (17.6%) patients, respectively, had died. ANGPT2 was independently associated with all-cause mortality in both cohorts at 24 months [hazard ratio (HR) 1.27 (95% confidence interval (CI), 1.08-1.50) for Norway, and HR 1.57 (95% CI, 1.27-1.95) for Argentina], with similar results at 60 months [HR 1.19 (95% CI, 1.05-1.35) (Norway), and HR 1.56 (95% CI, 1.30-1.88) (Argentina)], and was also significantly associated with cardiac death [HR 1.51 (95% CI, 1.14-2.00)], in the Argentinean population. ANGPTL4 was significantly associated with all-cause mortality in the Argentinean cohort at 24 months [HR 1.39 (95% CI, 1.15-1.68)] and at 60 months [HR 1.43 (95% CI, 1.23-1.67)], enforcing trends in the Norwegian population.

CONCLUSIONS

ANGPT2 and ANGPTL4 were significantly associated with outcome in similar ACS patient cohorts recruited on two continents.

CLINICAL TRIAL REGISTRATION

ClinicalTrials.gov Identifier: NCT00521976. ClinicalTrials.gov Identifier: NCT01377402.

Risk Prediction of Cardiovascular Events by Exploration of Molecular Data with Explainable Artificial Intelligence

Cardiovascular diseases (CVD) annually take almost 18 million lives worldwide. Most lethal events occur months or years after the initial presentation. Indeed, many patients experience repeated complications or require multiple interventions (recurrent events). Apart from affecting the individual, this leads to high medical costs for society. Personalized treatment strategies aiming at prediction and prevention of recurrent events rely on early diagnosis and precise prognosis. Complementing the traditional environmental and clinical risk factors, multi-omics data provide a holistic view of the patient and disease progression, enabling studies to probe novel angles in risk stratification. Specifically, predictive molecular markers allow insights into regulatory networks, pathways, and mechanisms underlying disease. Moreover, artificial intelligence (AI) represents a powerful, yet adaptive, framework able to recognize complex patterns in large-scale clinical and molecular data with the potential to improve risk prediction. Here, we review the most recent advances in risk prediction of recurrent cardiovascular events, and discuss the value of molecular data and biomarkers for understanding patient risk in a systems biology context. Finally, we introduce explainable AI which may improve clinical decision systems by making predictions transparent to the medical practitioner.

Application of Modern Clinical Risk Scores in the Global Assessment of Risks Related to the Diagnosis and Treatment of Acute Coronary Syndromes in Everyday Medical Practice

This article presents an overview of contemporary risk assessment systems used in patients with myocardial infarction. The full range of risk scales, both recommended by the European Society of Cardiology and others published in recent years, is presented. Scales for assessing the risk of ischemia/death as well as for assessing the risk of bleeding are presented. A separate section is devoted to systems assessing the integrated risk associated with both ischemia and bleeding. In the first part of the work, each of the risk scales is described in detail, including the clinical trials/registers on the basis of which they were created, the statistical methods used to develop them, as well as the specification of their individual parameters. The next chapter presents the practical application of a given scale in the patient risk assessment process, the timing of its application on the timeline of myocardial infarction, as well as a critical assessment of its potential advantages and limitations. The last part of the work is devoted to the presentation of potential directions for the development of risk assessment systems in the future.

Indirect comparison of TIMI, HEART and GRACE for predicting major cardiovascular events in patients admitted to the emergency department with acute chest pain: a systematic review and meta-analysis

BACKGROUND

The study aimed to compare the predictive values of the thrombolysis in myocardial infarction (TIMI); History, Electrocardiography, Age, Risk factors and Troponin (HEART) and Global Registry in Acute Coronary Events (GRACE) scoring systems for major adverse cardiovascular events (MACEs) in acute chest pain (ACP) patients admitted to the emergency department (ED).

METHODS

We systematically searched PubMed, Embase and the Cochrane Library from their inception to June 2020; we compared the following parameters: sensitivity, specificity, positive and negative likelihood ratios (PLR and NLR), diagnostic OR (DOR) and area under the receiver operating characteristic curves (AUC).

RESULTS

The pooled sensitivity and specificity for TIMI, HEART and GRACE were 0.95 and 0.36, 0.96 and 0.50, and 0.78 and 0.56, respectively. The pooled PLR and NLR for TIMI, HEART and GRACE were 1.49 and 0.13, 1.94 and 0.08, and 1.77 and 0.40, respectively. The pooled DOR for TIMI, HEART and GRACE was 9.18, 17.92 and 4.00, respectively. The AUC for TIMI, HEART and GRACE was 0.80, 0.80 and 0.70, respectively. Finally, the results of indirect comparison suggested the superiority of values of TIMI and HEART to those of GRACE for predicting MACEs, while there were no significant differences between TIMI and HEART for predicting MACEs.

CONCLUSIONS

TIMI and HEART were superior to GRACE for predicting MACE risk in ACP patients admitted to the ED.

Cardiovascular Risk Assessment in COVID-19

COVID-19 bezeichnet eine der schlimmsten Krisen unserer Generation und stellt (nicht nur) für das Gesundheitssystem eine schwer bewältigbare Herausforderung dar. Mortalität und Morbidität sind im Vergleich zu anderen saisonalen Erkrankungen wie der Influenza deutlich erhöht. COVID-19 bedroht allerdings nicht die gesamte Bevölkerung in gleichem Maße. Hochrisikopatienten sind älter und leiden an kardiovaskulären Erkrankungen wie Bluthochdruck, Diabetes mellitus oder einer koronaren Herzerkrankung. Um das Risiko für einen schweren Erkrankungsverlaufs zu quantifizieren bedarf es einer multimodalen Herangehensweise. Verschiedene Risikostratifizierungssysteme stehen zu Verfügung um ungünstige Verläufe wie Intensivbehandlung oder Gesamtmortalität vorauszusagen. Biomarker wie Troponin-I, D-Dimere und NT pro-BNP kombiniert mit echokardiographischen Parametern wie links- und rechtsventrikulärer Pumpfunktion sowie pulmonalarteriellem Druck können hilfreich sein um Hochrisikopatienten zu identifizieren, die ein intensiviertes Monitoring und eine stringentere Behandlung benötigen. Da kardiovaskuläre Risikofaktoren und Komorbiditäten von großer Bedeutung zur Abschätzung des Verlaufs einer SARS-CoV-2 Infektion sind, könnten alle hospitalisierten COVID-19 Patienten von einer routinemäßigen kardiologischen Betreuung durch ein COVID-19-Heart-Team profitieren. Ein frühzeitiges Erkennen von (kardiovaskulären) Hochrisikopatienten könnte das Management erleichtern sowie die Prognose einer schweren SARS-CoV-2 Infektion verbessern.

Geriatric Assessment and In-Hospital Economic Cost of Elderly Patients With Acute Coronary Syndromes

BACKGROUND

Elderly patients with acute coronary syndromes (ACS) are at higher risk for complications and health care resources expenditure. No previous study has assessed the specific contribution of frailty and other geriatric syndromes to the in-hospital economic cost in this setting.

METHOD

Unselected patients with ACS aged ≥75 years were prospectively included. A comprehensive geriatric assessment was performed during hospitalisation. Hospitalisation-related cost per patient was calculated with an analytical accountability method, including hospital stay-related expenditures, interventions, and consumption of devices. Expenditure was expressed in Euros (2019). The contribution of geriatric syndromes and clinical factors to the economic cost was assessed with a linear regression method.

RESULTS

A total of 194 patients (mean age 82.6 years) were included. Mean length of hospital stay was 11.3 days. The admission-related economic cost was €6,892.15 per patient. Most of this cost was attributable to hospital length of stay (77%). The performance of an invasive strategy during the admission was associated with economic cost (p=0.008). Of all the ageing-related variables, comorbidity showed the most significant association with economic cost (p=0.009). Comorbidity, disability, nutritional risk, and frailty were associated with the hospital length of stay-related component of the economic cost. The final predictive model of economic cost included age, previous heart failure, systolic blood pressure, Killip class at admission, left main disease, and Charlson index.

CONCLUSIONS

Management of ACS in elderly patients is associated with a significant economic cost, mostly due to hospital length of stay. Comorbidity mostly contributes to in-hospital resources expenditure, as well as the severity of the coronary event.

Factors associated with temporary pacing insertion in patients with inferior ST-segment elevation myocardial infarction

Background

High-degree atrioventricular block (HAVB) is a prognostic factor for survival in patients with inferior ST-segment elevation myocardial infarction (STEMI). However, there is little information about factors associated with temporary pacing (TP). The aim of this study was to find factors associated with TP in patients with inferior STEMI.

Methods

We included 232 inferior STEMI patients, and divided those into the TP group (n = 46) and the non-TP group (n = 186). Factors associated with TP were retrospectively investigated using multivariate logistic regression model.

Results

The incidence of right ventricular (RV) infarction was significantly higher in the TP group (19.6%) than in the non-TP group (7.5%) (p = 0.024), but the incidence of in-hospital death was similar between the 2 groups (4.3% vs. 4.8%, p = 1.000). Long-term major adverse cardiovascular events (MACE), which were defined as a composite of all-cause death, non-fatal myocardial infarction (MI), target vessel revascularization (TVR) and readmission for heart failure, were not different between the 2 groups (p = 0.100). In the multivariate logistic regression analysis, statin at admission [odds ratio (OR) 0.230, 95% confidence interval (CI) 0.062–0.860, p = 0.029], HAVB at admission (OR 9.950, 95% CI 4.099–24.152, p<0.001), and TIMI-thrombus grade ≥3 (OR 10.762, 95% CI 1.385–83.635, p = 0.023) were significantly associated with TP.

Conclusion

Statin at admission, HAVB at admission, and TIMI-thrombus grade ≥3 were associated with TP in patients with inferior STEMI. Although the patients with TP had the higher incidence of RV infarction, the incidence of in-hospital death and long-term MACE was not different between patients with TP and those without.

Clinical impact of estimated plasma volume status and its additive effect with the GRACE risk score on in-hospital and long-term mortality for acute myocardial infarction

BACKGROUND

Estimated plasma volume status (ePVS) is a well-validated prognostic indicator in heart failure. However, it remains unclear whether ePVS has prognostic significance in patients with acute myocardial infarction (AMI). Moreover, there is no available information on its additive effect with the Global Registry of Acute Coronary Events (GRACE) risk score in AMI patients.

METHODS

Data were obtained from the Osaka Acute Coronary Insufficiency Study (OACIS) registry database. Patients whose data were available for ePVS derived from Hakim's formula and the GRACE risk score were studied. The primary endpoints were in-hospital and 5-year mortality.

RESULTS

Of 3930 patients, 206 and 200 patients died during hospitalization and 5 years after discharge, respectively. After adjustment, ePVS remained an independent predictor of in-hospital death (OR:1.02, 95% CI: 1.00-1.04, p = 0.036), and 5-year mortality(HR:1.03, 95% CI: 1.01-1.04, p < 0.001). An additive effect of ePVS with the GRACE risk score was observed in predicting the 5-year mortality with an area under the receiver operating characteristic curve (AUC) from 0.744 to 0.763 (p = 0.026), but not in-hospital mortality (the AUC changed from 0.875 to 0.875, p = 0.529). The incremental predictive value of combining ePVS and the GRACE risk score for 5-year mortality was significantly improved, as shown by the net reclassification improvement (NRI:0.378, p < 0.001) and integrated discrimination improvement (IDI:0.014, p < 0.001).

CONCLUSIONS

In patients with AMI, ePVS independently predicted in-hospital and long-term mortality. In addition, ePVS had an additive effect with the GRACE risk score on long-term mortality. Therefore, ePVS may be useful for identifying high-risk subjects for intensive treatment.

Missed Opportunities to Initiate Oral Anticoagulant in Atrial Fibrillation: Insights from Australian Acute Coronary Syndrome Registries

BACKGROUND

Many patients with atrial fibrillation (AF) do not receive oral anticoagulant (OAC) therapy. The aims of this study were to 1) document receipt of OAC among patients with a history of AF admitted with an acute coronary syndrome (ACS); and to 2) determine whether hospital admission was associated with an improvement in prescription of OAC therapy.

METHODS

Using Australian data from the Cooperative National Registry of Acute Coronary Care, Guideline Adherence and Clinical Events (CONCORDANCE) and Global Registry of Acute Coronary Events (GRACE) registries, 1,479 patients with a history of AF presenting with an ACS were separated into two groups: aspirin monotherapy/no therapy (No OAC) or oral anticoagulant ± aspirin (OAC). Clinical characteristics and in-hospital treatments and outcomes were compared.

RESULTS

Of 1,479 patients, 532 (36%) with a history of AF presented on OAC with the remainder receiving antiplatelet (n=580 [39%]) or no antithrombotic therapy (n=367 [25%]). Treatment with OAC prior to presentation increased during the 18 years of the study (27% to 56%, p=0.0002). Ninety-five per cent (95%) of the OAC group had a CHA2DS2-VA score >1 vs 88% of the No OAC group (p<0.001). Patients receiving OAC had a lower prevalence of bleeding risk factors than no OAC patients (p<0.001). Only 39% of this cohort was discharged on an OAC, although this increased during the observational period (26-61%, p≤0.0001).

CONCLUSION

In patients presenting with an ACS with a history of AF, receipt of OAC has improved over time but remains suboptimal. There is minimal escalation in provision of OAC therapy during hospital care, indicating missed opportunities to address this evidence practice gap.

Machine learning for early prediction of in-hospital cardiac arrest in patients with acute coronary syndromes

Background

Previous studies have used machine leaning to predict clinical deterioration to improve outcome prediction. However, no study has used machine learning to predict cardiac arrest in patients with acute coronary syndrome (ACS). Algorithms are required to generate high‐performance models for predicting cardiac arrest in ACS patients with multivariate features.

Hypothesis

Machine learning algorithms will significantly improve outcome prediction of cardiac arrest in ACS patients.

Methods

This retrospective cohort study reviewed 166 ACS patients who had in‐hospital cardiac arrest. Eight machine learning algorithms were trained using multivariate clinical features obtained 24 h prior to the onset of cardiac arrest. All machine learning models were compared to each other and to existing risk prediction scores (Global Registry of Acute Coronary Events, National Early Warning Score, and Modified Early Warning Score) using the area under the receiver operating characteristic curve (AUROC).

Results

The XGBoost model provided the best performance with regard to AUC (0.958 [95%CI: 0.938–0.978]), accuracy (88.9%), sensitivity (73%), negative predictive value (89%), and F1 score (80%) compared with other machine learning models. The K‐nearest neighbor model generated the best specificity (99.3%) and positive predictive value (93.8%) metrics, but had low and unacceptable values for sensitivity and AUC. Most, but not all, machine learning models outperformed the existing risk prediction scores.

Conclusions

The XGBoost model, which was generated based on a machine learning algorithm, has high potential to be used to predict cardiac arrest in ACS patients. This proposed model significantly improves outcome prediction compared to existing risk prediction scores.

Relation of Body Mass Index to Outcomes in Acute Coronary Syndrome

We assessed the association of BMI with all-cause and cardiovascular (CV) mortality in a contemporary acute coronary syndrome cohort. Patients from the Australian Cooperative National Registry of Acute Coronary Care, Guideline Adherence and Clinical Events and Global Registry of Acute Coronary Events between 2009 and 2019, were divided into BMI subgroups (underweight: <18.5, healthy: 18.5 to 24.9, overweight: 25 to 29.9, obese: 30 to 39.9, extremely obese: >40). Logistic regression was used to determine the association between BMI group and outcomes of all cause and CV death in hospital, and at 6 months. 8,503 patients were identified, mean age 64 ± 13, 72% male. The BMI breakdown was: underweight- 95, healthy- 2,140, overweight- 3,258, obese- 2,653, extremely obese- 357. Obese patients were younger (66 ± 12 vs 67 ± 13), with more hypertension, diabetes, and dyslipidemia vs healthy (all p < 0.05). Obese had lower hospital mortality than healthy: all-cause: 1% versus 4%, aOR (95% CI): 0.49(0.27, 0.87); CV: 1% versus 3%, 0.51(0.27, 0.96). At 6-month underweight had higher mortality than healthy: all-cause: 11% versus 4%, 2.69(1.26, 5.76); CV: 7% versus 1%, 3.54(1.19, 10.54); whereas obese had lower mortality: all-cause: 1% versus 4%, 0.48(0.29, 0.77); CV: 0.4% versus 1%, 0.42(0.19, 0.93). When BMI was plotted as a continuous variable against outcome a U-shaped relationship was demonstrated, with highest event rates in the most obese (>60). In conclusion, BMI is associated with mortality following an acute coronary syndrome. Obese patients had the best outcomes, suggesting persistence of the obesity paradox. However, there was a threshold effect, and favorable outcomes did not extend to the most obese.

Prospective cohort study of elderly patients with coronary artery disease: impact of frailty on quality of life and outcome

Background

Elderly, frail patients are often excluded from clinical trials so there is lack of data regarding optimal management when they present with symptomatic coronary artery disease (CAD).

Objective

The aim of this observational study was to evaluate an unselected elderly population with CAD for the occurrence of frailty, and its association with quality of life (QoL) and clinical outcomes.

Methods

Consecutive patients aged ≥80 years presenting with CAD were prospectively assessed for frailty (Fried frailty phenotype (FFP), Edmonton frailty scale (EFS)), QoL (Short form survey (SF-12)) and comorbidity (Charlson Comorbidity Index (CCI)). Patients were re-assessed at 4 months to determine any change in frailty and QoL status as well as the clinical outcome.

Results

One hundred fifty consecutive patients with symptomatic CAD were recruited in the study. The mean age was 83.7±3.2 years, 99 (66.0%) were men. The clinical presentation was stable angina in 68 (45.3%), the remainder admitted with an acute coronary syndrome including 21 (14.0%) with ST-elevation myocardial infarction. Frailty was present in 28% and 26% by FFP and EFS, respectively, and was associated with a significantly higher CCI (7.5±2.4 in frail, 6.2±2.2 in prefrail, 5.9±1.6 in those without frailty, p=0.005). FFP was significantly related to the physical composite score for QoL, while EFS was significantly related to the mental composite score for QoL (p=0.003). Treatment was determined by the cardiologist: percutaneous coronary intervention in 51 (34%), coronary artery bypass graft surgery in 15 (10%) and medical therapy in 84 (56%). At 4 months, 14 (9.3%) had died. Frail participants had the lowest survival. Cardiovascular symptom status and the mental composite score of QoL significantly improved (52.7±11.5 at baseline vs 55.1±10.6 at follow-up, p=0.04). However, overall frailty status did not significantly change, nor the physical health composite score of QoL (37.2±11.0 at baseline vs 38.5±11.3 at follow-up, p=0.27).

Conclusions

In patients referred to hospital with CAD, frailty is associated with impaired QoL and a high coexistence of comorbidities. Following cardiac treatment, patients had improvement in cardiovascular symptoms and mental component of QoL.

Peri-Procedural Blood Pressure Changes and Their Relationship with MACE in Patients Undergoing Percutaneous Coronary Intervention: A Cross-Sectional Study

Background

Peri-procedural blood-pressure (BP) changes were investigated and correlated to Major adverse cardiovascular events (MACE) as predictor of outcome for patients undergoing percutaneous coronary intervention (PCI); whether acute coronary syndrome (Unstable angina, or MI; STEMI or NSTEMI) or scheduled for elective PCI.

Methods

Resting BP in the 204 recruited patients undergoing PCI throughout 2018 was measured thrice – in the ward before transferring to the cardiac catheterization lab (cath lab), in the cath lab, and after transfer to the recovery room. Patients were categorized based on their systolic and diastolic BP peri-procedural difference as systolic (SBP): with a large difference (>20 mmHg, n=47), with a small difference (≤20 mmHg, n=157) (shock patients excluded); diastolic (DBP): with a large difference (>10 mmHg, n=65), and with a small difference (≤10 mmHg, n=139). The primary end-points were MACE including all-cause mortality, non-fatal myocardial infarction, and stroke during the hospital stay. The Mann–Whitney U and Chi-square tests were used to analyze the data accordingly (p<0.005).

Results

Within the category of MACE, cardiac mortality was the only adverse cardiac event encountered in the study sample. Cardiac mortality was significantly higher in both the large SBP-difference group versus the other group (10.6% vs 0.6%, p=0.003) and the large DBP-difference group versus the small-difference group (7.7% vs 0.7%, p=0.013).

Conclusion

Peri-procedural systolic and diastolic BP differences, greater than 20 mmHg and 10 mmHg, respectively, correlated with MACE in all patients undergoing PCI.

Treatment effect prediction with adversarial deep learning using electronic health records

BACKGROUND

Treatment effect prediction (TEP) plays an important role in disease management by ensuring that the expected clinical outcomes are obtained after performing specialized and sophisticated treatments on patients given their personalized clinical status. In recent years, the wide adoption of electronic health records (EHRs) has provided a comprehensive data source for intelligent clinical applications including the TEP investigated in this study.

METHOD

We examined the problem of using a large volume of heterogeneous EHR data to predict treatment effects and developed an adversarial deep treatment effect prediction model to address the problem. Our model employed two auto-encoders for learning the representative and discriminative features of both patient characteristics and treatments from EHR data. The discriminative power of the learned features was further enhanced by decoding the correlational information between the patient characteristics and subsequent treatments by means of a generated adversarial learning strategy. Thereafter, a logistic regression layer was appended on the top of the resulting feature representation layer for TEP.

RESULT

The proposed model was evaluated on two real clinical datasets collected from the cardiology department of a Chinese hospital. In particular, on acute coronary syndrome (ACS) dataset, the proposed adversarial deep treatment effect prediction (ADTEP) (0.662) exhibited 1.4, 2.2, and 6.3% performance gains in terms of the area under the ROC curve (AUC) over deep treatment effect prediction (DTEP) (0.653), logistic regression (LR) (0.648), and support vector machine (SVM) (0.621), respectively. As for heart failure (HF) case study, the proposed ADTEP also outperformed all benchmarks. The experimental results demonstrated that our proposed model achieved competitive performance compared to state-of-the-art models in tackling the TEP problem.

CONCLUSION

In this work, we propose a novel model to address the TEP problem by utilizing a large volume of observational data from EHR. With adversarial learning strategy, our proposed model can further explore the correlational information between patient statuses and treatments to extract more robust and discriminative representation of patient samples from their EHR data. Such representation finally benefits the model on TEP. The experimental results of two case studies demonstrate the superiority of our proposed method compared to state-of-the-art methods.

Predicting 1-, 3- and 5-year outcomes in patients with coronary artery disease: A comparison of available risk assessment scores

BACKGROUND AND AIMS

Thromboischemic and bleeding events are rare but life-threatening complications after percutaneous coronary intervention (PCI). Various risk assessment models have been established to predict short- and long-term adverse events in patients with chronic and acute coronary syndromes (CCS, ACS). The aim of the present study was to compare available risk assessment systems based on their performance in identifying high-risk patients with symptomatic coronary artery disease (CAD).

METHODS

We enrolled 1565 consecutive patients with symptomatic CAD (n = 821 CCS, n = 744 ACS). CALIBER, DAPT, GRACE 2.0, PARIS-CTE, PARIS-MB, PRECISE-DAPT and PREDICT-STABLE scores were calculated in appropriate patient subgroups. All patients were followed-up for 1, 3 and 5 years for all-cause death (ACD), myocardial infarction (MI), ischemic stroke (IS) and bleeding. The primary combined ischemic endpoint (CE) consisted of ACD, MI and/or IS. Secondary endpoints were defined as single occurrence of either ACD, MI, IS, or bleeding.

RESULTS

GRACE 2.0 score showed good discrimination performance (AUC>0.7) for CE in a 3- and 5-year follow-up. CALIBER, GRACE 2.0 and PARIS-CTE showed best performance (AUC>0.7) in predicting ACD throughout the follow-up, whereas IS was best predicted by PARIS-CTE and CALIBER scores. None of the scores performed well (AUC>0.7) in predicting MI or bleeding.

CONCLUSIONS

In a consecutive German CAD cohort, CALIBER, GRACE 2.0 and PARIS-CTE scores performed best in predicting CE, ACD and/or IS whereas none of the selected scores could predict MI and bleeding efficiently.

Rationale and Design of the Future Optimal Research and Care Evaluation in Patients with Acute Coronary Syndrome (FORCE-ACS) Registry: Towards "Personalized Medicine" in Daily Clinical Practice

Diagnostic and treatment strategies for acute coronary syndrome have improved dramatically over the past few decades, but mortality and recurrent myocardial infarction rates remain high. An aging population with increasing co-morbidities heralds new clinical challenges. Therefore, in order to evaluate and improve current treatment strategies, detailed information on clinical presentation, treatment and follow-up in real-world patients is needed. The Future Optimal Research and Care Evaluation in patients with Acute Coronary Syndrome (FORCE-ACS) registry (ClinicalTrials.gov Identifier: NCT03823547) is a multi-center, prospective real-world registry of patients admitted with (suspected) acute coronary syndrome. Both non-interventional and interventional cardiac centers in different regions of the Netherlands are currently participating. Patients are treated according to local protocols, enabling the evaluation of different diagnostic and treatment strategies used in daily practice. Data collection is performed using electronic medical records and quality-of-life questionnaires, which are sent 1, 12, 24 and 36 months after initial admission. Major end points are all-cause mortality, myocardial infarction, stent thrombosis, stroke, revascularization and all bleeding requiring medical attention. Invasive therapy, antithrombotic therapy including patient-tailored strategies, such as the use of risk scores, pharmacogenetic guided antiplatelet therapy and patient reported outcome measures are monitored. The FORCE-ACS registry provides insight into numerous aspects of the (quality of) care for acute coronary syndrome patients.

Sex Difference in Risk Factors, GRACE Scores, and Management among Post-Acute Coronary Syndrome Patients in Sri Lanka

Objective

To assess sex-based differences in the prevalence of risk factor, their management, and differences in the prognosis among acute coronary syndrome (ACS) in Sri Lanka.

Methods

Patients diagnosed with ACS were recruited from hospitals throughout the island. The Joint European Societies guidelines were used to assess recommended targets for coronary heart disease risk factors, and the GRACE score was used to assess the post-ACS prognosis. Age-adjusted regression was performed to calculate odds ratios for men versus women in risk factor control.

Results

A total of 2116 patients, of whom 1242 (58.7%) were men, were included. Significant proportion of women were nonsmokers; OR = 0.11 (95% CI 0.09 to 0.13). The prevalence of hypertension (p < 0.001), diabetes (p < 0.001), and dyslipidemia (p=0.004) was higher in women. The LDL-C target was achieved in a significantly higher percentage of women (12.6%); OR = 0.33 (95% CI 0.10 to 1.05). When stratified by age, no significant differences were observed in achieving the risk factor targets or management strategies used except for fasting blood sugar (p < 0.05) where more men achieved control target in both age categories. Majority of the ACS patients had either high or intermediate risk for one-year mortality as per the GRACE score. In-hospital and 1-year mean mortality risk was significantly higher among men of less than 65 years of age (p < 0.05).

Conclusions

Smoking is significantly lower among Sri Lankan women diagnosed with ACS. However, hypertension, diabetes, and dyslipidemia were more prevalent among them. There was no difference in primary and secondary preventive strategies and management in both sexes but could be further improved in both groups.

GARFIELD-AF: a worldwide prospective registry of patients with atrial fibrillation at risk of stroke

The Global Anticoagulant Registry in the Field-Atrial Fibrillation (GARFIELD-AF) examined real-world practice in a total of 57,149 (5069 retrospective, 52,080 prospective) patients with newly diagnosed AF at risk of stroke/systemic embolism, enrolled at over 1000 centers in 35 countries. It aimed to capture data on AF burden, patients' clinical profile, patterns of clinical practice and antithrombotic management, focusing on stroke/systemic embolism prevention, uptake of new oral anticoagulants, impact on death and bleeding. GARFIELD-AF set new standards for quality of data collection and analysis. A total of 36 peer-reviewed articles were already published and 73 abstracts presented at international congresses, covering treatment strategies, geographical variations in baseline risk and therapies, adverse outcomes and common comorbidities such as heart failure. A risk prediction tool as well as innovative observational studies and artificial intelligence methodologies are currently being developed by GARFIELD-AF researchers. Clinical Trial Registration: NCT01090362 (ClinicalTrials.gov).