A new score for the diagnosis of acute coronary syndrome in acute chest pain with non-diagnostic ECG and normal troponin

Machine Learning for the ECG Diagnosis and Risk Stratification of Occlusion Myocardial Infarction at First Medical Contact

Patients with occlusion myocardial infarction (OMI) and no ST-elevation on presenting ECG are increasing in numbers. These patients have a poor prognosis and would benefit from immediate reperfusion therapy, but we currently have no accurate tools to identify them during initial triage. Herein, we report the first observational cohort study to develop machine learning models for the ECG diagnosis of OMI. Using 7,313 consecutive patients from multiple clinical sites, we derived and externally validated an intelligent model that outperformed practicing clinicians and other widely used commercial interpretation systems, significantly boosting both precision and sensitivity. Our derived OMI risk score provided superior rule-in and rule-out accuracy compared to routine care, and when combined with the clinical judgment of trained emergency personnel, this score helped correctly reclassify one in three patients with chest pain. ECG features driving our models were validated by clinical experts, providing plausible mechanistic links to myocardial injury.

Prehospital risk assessment in patients suspected of non-ST-segment elevation acute coronary syndrome: a systematic review and meta-analysis

OBJECTIVE

To review, inventory and compare available diagnostic tools and investigate which tool has the best performance for prehospital risk assessment in patients suspected of non-ST-segment elevation acute coronary syndrome (NSTE-ACS).

METHODS

Systematic review and meta-analysis. Medline and Embase were searched up till 1 April 2021. Prospective studies with patients, suspected of NSTE-ACS, presenting in the primary care setting or by emergency medical services (EMS) were included. The most important exclusion criteria were studies including only patients with ST-elevation myocardial infarction and studies before 1995, the pretroponin era. The primary end point was the final hospital discharge diagnosis of NSTE-ACS or major adverse cardiac events (MACE) within 6 weeks. Risk of bias was evaluated by the Quality Assessment of Diagnostic Accuracy Studies Criteria.

MAIN OUTCOME AND MEASURES

Sensitivity, specificity and likelihood ratio of findings for risk stratification in patients suspected of NSTE-ACS.

RESULTS

In total, 15 prospective studies were included; these studies reflected in total 26 083 patients. No specific variables related to symptoms, physical examination or risk factors were useful in risk stratification for NSTE-ACS diagnosis. The most useful electrocardiographic finding was ST-segment depression (LR+3.85 (95% CI 2.58 to 5.76)). Point-of-care troponin was found to be a strong predictor for NSTE-ACS in primary care (LR+14.16 (95% CI 4.28 to 46.90) and EMS setting (LR+6.16 (95% CI 5.02 to 7.57)). Combined risk scores were the best for risk assessment in an NSTE-ACS. From the combined risk scores that can be used immediately in a prehospital setting, the PreHEART score, a validated combined risk score for prehospital use, derived from the HEART score (History, ECG, Age, Risk factors, Troponin), was most useful for risk stratification in patients with NSTE-ACS (LR+8.19 (95% CI 5.47 to 12.26)) and for identifying patients without ACS (LR-0.05 (95% CI 0.02 to 0.15)).

DISCUSSION

Important study limitations were verification bias and heterogeneity between studies. In the prehospital setting, several diagnostic tools have been reported which could improve risk stratification, triage and early treatment in patients suspected for NSTE-ACS. On-site assessment of troponin and combined risk scores derived from the HEART score are strong predictors. These results support further studies to investigate the impact of these new tools on logistics and clinical outcome.

FUNDING

This study is funded by ZonMw, the Dutch Organisation for Health Research and Development.

TRIAL REGISTRATION NUMBER

This meta-analysis was published for registration in PROSPERO prior to starting (CRD York, CRD42021254122).

Novel Invasive and Noninvasive Cardiac-Specific Biomarkers in Obesity and Cardiovascular Diseases

Cardiovascular disease (CVD) is the leading cause of fatality and disability worldwide regardless of gender. Obesity has reached epidemic proportions in population across different regions. According to epidemiological studies, CVD risk markers in childhood obesity are one of the significant risk factors for adulthood CVD, but have received disproportionally little attention. This review has examined the evidence for the presence of traditional cardiac biomarkers (nonspecific; lactate dehydrogenase, alanine aminotransferase, aspartate aminotransferase, creatine kinase, myoglobulin, glycogen phosphorylase isoenzyme BB, myosin light chains, ST2, and ischemia-modified albumin) and novel emerging cardiac-specific biomarkers (cardiac troponins, natriuretic peptides, heart-type fatty acid-binding protein, and miRNAs). Besides, noninvasive anatomical and electrophysiological markers (carotid intima-media thickness, coronary artery calcification, and heart rate variability) in CVDs and obesity are also discussed. Modifiable and nonmodifiable risk factors associated with metabolic syndrome in the progression of CVD, such as obesity, diabetes, hypertension, dyslipidemia, oxidative stress, inflammation, and adipocytokines are also outlined. These underlying prognostic risk factors predict the onset of future microvascular and macrovascular complications. The understanding of invasive and noninvasive cardiac-specific biomarkers and the risk factors may yield valuable insights into the pathophysiology and prevention of CVD in a high-risk obese population at an early stage.

Highly Sensitive Detection of Minimal Cardiac Ischemia using Positron Emission Tomography Imaging of Activated Platelets

A reliable method for the diagnosis of minimal cardiac ischemia would meet a strong demand for the sensitive diagnosis of coronary artery disease in cardiac stress testing and risk stratification in patients with chest pain but unremarkable ECGs and biomarkers. We hypothesized that platelets accumulate early on in ischemic myocardium and a newly developed technology of non-invasive molecular PET imaging of activated platelets can thus detect minimal degrees of myocardial ischemia. To induce different degrees of minimal cardiac ischemia, the left anterior descending artery (LAD) was ligated for 10, 20 or 60 min. Mice were injected with a newly generated scFv_{anti-GPIIb/IIIa}-⁶⁴CuMeCOSar radiotracer, composed of a single-chain antibody that only binds to activated integrin GPIIb/IIIa (α_IIbβ_III) and thus to activated platelets, and a sarcophagine cage MeCOSar complexing the long half-life PET tracer copper-64. A single PET/CT scan was performed. Evans Blue/TTC staining to detect necrosis as well as classical serological biomarkers like Troponin I and heart-type fatty acid-binding protein (H-FABP) were negative, whereas PET imaging of activated platelets was able to detect small degrees of ischemia. Taken together, molecular PET imaging of activated platelets represents a unique and highly sensitive method to detect minimal cardiac ischemia.

A clinical score to obviate the need for cardiac stress testing in patients with acute chest pain and negative troponins

INTRODUCTION

Although cardiac stress testing may help establish the safety of early discharge in patients with suspected acute coronary syndromes and negative troponins, more cost-effective strategies are necessary. We aimed to develop a clinical prediction rule to safely obviate the need for cardiac stress testing in this setting.

METHODS

A decision rule was derived in a prospective cohort of 3001 patients with acute chest pain and negative troponins, and validated in a set of 1473 subjects. The primary end point was a composite of positive cardiac stress testing (in the absence of a subsequent negative coronary angiogram), positive coronary angiography, or any major coronary events within 3 months.

RESULTS

A score chart was built based on 7 variables: male sex (+2), age (+1 per decade from the fifth decade), diabetes mellitus (+2), hypercholesterolemia (+1), prior coronary revascularization (+2), type of chest pain (typical angina, +5; non-specific chest pain, -3), and non-diagnostic repolarization abnormalities (+2). In the validation set, the model showed good discrimination (c statistic = 0.84; 95% confidence interval, 0.82-0.87) and calibration (Hosmer-Lemeshow goodness-of-fit test, P= .34). If stress tests were avoided in patients in the validation sample with a sum score of 0 or lower, the number of referrals would be reduced by 23.4%, yielding a negative predictive value of 98.8% (95% confidence interval, 97.0%-99.7%).

CONCLUSION

This novel prediction rule based on a combination of readily available clinical characteristics may be a valuable tool to decide whether stress testing can be reliably avoided in patients with acute chest pain and negative troponins.