Diagnostic re-classification and prognostic risk stratification of patients with acute chest pain

A novel breakthrough in wrist-worn transdermal troponin-I-sensor assessment for acute myocardial infarction

Aims

Clinical differentiation of acute myocardial infarction (MI) from unstable angina and other presentations mimicking acute coronary syndromes (ACS) is critical for implementing time-sensitive interventions and optimizing outcomes. However, the diagnostic steps are dependent on blood draws and laboratory turnaround times. We tested the clinical feasibility of a wrist-worn transdermal infrared spectrophotometric sensor (transdermal-ISS) in clinical practice and assessed the performance of a machine learning algorithm for identifying elevated high-sensitivity cardiac troponin-I (hs-cTnI) levels in patients hospitalized with ACS.

Methods and results

We enrolled 238 patients hospitalized with ACS at five sites. The final diagnosis of MI (with or without ST elevation) and unstable angina was adjudicated using electrocardiography (ECG), cardiac troponin (cTn) test, echocardiography (regional wall motion abnormality), or coronary angiography. A transdermal-ISS-derived deep learning model was trained (three sites) and externally validated with hs-cTnI (one site) and echocardiography and angiography (two sites), respectively. The transdermal-ISS model predicted elevated hs-cTnI levels with areas under the receiver operator characteristics of 0.90 [95% confidence interval (CI), 0.84-0.94; sensitivity, 0.86; and specificity, 0.82] and 0.92 (95% CI, 0.80-0.98; sensitivity, 0.94; and specificity, 0.64), for internal and external validation cohorts, respectively. In addition, the model predictions were associated with regional wall motion abnormalities [odds ratio (OR), 3.37; CI, 1.02-11.15; P = 0.046] and significant coronary stenosis (OR, 4.69; CI, 1.27-17.26; P = 0.019).

Conclusion

A wrist-worn transdermal-ISS is clinically feasible for rapid, bloodless prediction of elevated hs-cTnI levels in real-world settings. It may have a role in establishing a point-of-care biomarker diagnosis of MI and impact triaging patients with suspected ACS.

Unstable Angina as a Component of Primary Composite Endpoints in Clinical Cardiovascular Trials: Pros and Cons

Background Unstable angina (UA) is a component of acute coronary syndrome that is only occasionally included in primary composite endpoints in clinical cardiovascular trials. The aim of this paper is to elucidate the potential benefits and disadvantages of including UA in such contexts. Summary UA comprises <10% of patients with acute coronary syndromes in contemporary settings. Based on the pathophysiological similarities, it is ideal as a part of a composite endpoint along with myocardial infarction (MI). By adding UA as a component of a primary composite endpoint, the number of events and feasibility of the trial should increase, thus decreasing size and costs of trials. Furthermore, UA has both economic and quality of life implications on a societal and an individual level. However, there are important challenges associated with the use of UA as an endpoint. With the introduction of high-sensitivity troponins, the number of individuals diagnosed with UA has decreased to rather low levels, with a reciprocal increase in the number of MI. In addition, UA is particularly challenging to define given the subjective assessment of the index symptoms, rendering a high risk of bias. To minimize bias, strict criteria are warranted, and events should be adjudicated by a blinded endpoint adjudication committee. Key messages UA should only be chosen as a component of a primary composite endpoint in cardiovascular trials after thoroughly evaluating the pros and cons. If it is chosen to include UA, appropriate precautions should be taken to minimize possible bias.

Elevated Lipoprotein-Associated Phospholipase A2 is Valuable in Prediction of Coronary Slow Flow in Non-ST-Segment Elevation Myocardial Infarction Patients

Background Coronary flow is a determinative factor of non-ST-segment elevation myocardial infarction (NSTEMI) patients. Lipoprotein-Associated Phospholipase A2(Lp-PLA2) as a vascular specific inflammatory cytokine might relate to coronary slow flow in these patients. Methods 105 NSTEMI patients and 83 UAP patients were enrolled. Another group division was made by Lp-PLA2 tertile data. Corrected thrombolysis in myocardial infarction (TIMI) frame count (CTFC) was adopted to represent coronary flow condition. Correlation analysis was made between CTFC and other clinical indicators. Multivariable regression analysis was used to identify the influential factors of coronary flow in NSTEMI patients. ROC curve was used to determine the diagnostic value of Lp-PLA2 with coronary slow flow (CSF). Results High sensitive C reactive protein (hsCRP, P < 0.01), Lp-PLA2(P < 0.01), N-terminal pro-brain natriuretic peptide (NT-proBNP, P < 0.05), mean platelet volume (MPV, P<0.05), CTFC(P < 0.05) was higher in NSTEMI than UAP patients. hsCRP(P < 0.01), MPV(P < 0.01), NT-proBNP(P < 0.01) CTFC(P < 0.01) was higher in high-Lp-PLA2 group. Lp-PLA2 and hsCRP (r = 0.22, P < 0.01), MPV (r = 0.21, P < 0.05), CTFC (r = 0.69, P < 0.01) had a positive correlation in NSTEMI group. Multivariable regression analysis showed that Lp-PLA2 could explain most part changes of CTFC in NSTEMI patients, CTFC = 0.55*Lp-PLA2+0.03*hsCRP+0.005*NT-proBNP+15.843. Lp-PLA2 was specific and sensitive in diagnosis of CSF in NSTEMI group, AUC = 0.851(95% confidence interval (CI): 0.771-0.924, P < 0.01), Cutoff=196.96ng/ml, sensitivity = 84%, specificity = 81%. Conclusions Lp-PLA2 is closely correlated with coronary flow in NSTEMI patients. Lp-PLA2 over 196.96ng/ml could be used to predict CSF in NSTEMI patients.