Diagnostic value of cardiac troponin I and N-terminal pro-B-Type Natriuretic Peptide in cardiac syncope

Exploring artificial intelligence methods for cardiac syncope diagnosis combined with electrocardiogram parameters and clinical characteristics

BACKGROUND

Cardiac syncope can be life-threatening, but there is no clinical tool for initial screening. The study explored and developed optimal artificial intelligence methods for automatic diagnosis of cardiac syncope based on combinations of electrocardiogram parameters and clinical characteristics.

METHODS

The patients presenting with syncope and hospitalized between June 21, 2018 and August 23, 2022 at the Second Hospital of Tianjin Medical University. The patients enrolled were divided into development cohort who were then randomly split into a training set and an internal validation set (4: 1) and temporal validation cohort. Fifteen features of syncope patients were ranked and valuable features were selected. Six supervised machine learning models were developed to explore a potential prediction model for cardiac syncope. The area under the curve (AUC) was the primary metric used to evaluate classification performance.

RESULTS

A total of 380 patients (340 in the development cohort and 40 in the temporal validation cohort) were included in the final analysis. The random forest showed the best performance using the top twelve features ranked by importance, demonstrating an AUC of 0.85 (sensitivity: 0.72, specificity: 0.85, F1 score: 0.74) in the development cohort, and an AUC of 0.75 (sensitivity: 0.70, specificity: 0.65, F1 score: 0.68) in the validation cohort. The novel approach for automatic diagnosis of cardiac syncope has been proposed as web service for further application.

CONCLUSIONS

Artificial intelligence methods may assist in syncope classification, and which have the potential to serve as a cost-effective and efficient screening tool for cardiac syncope.

Analysis of risk factors for adverse events associated with cardiogenic syncope due to coronary artery disease in the elderly

OBJECTIVE

To analyze risk factors for adverse events associated with syncope due to coronary artery disease (CAD) in the elderly.

METHODS

Two hundred eight patients with CAD who were hospitalized for cardiogenic syncope in our hospital from September 2022 to September 2023 were included in this study. Based on the follow-up results, 208 patients with cardiogenic syncope due to geriatric coronary artery disease were classified into the no-adverse group (n = 171), and the adverse group (n = 37), and the risk factors for the occurrence of adverse events in cardiogenic syncope in both groups were analyzed.

RESULTS

The age differences, history of heart failure, cardiac troponin I (hs-TnT) level, N-terminal B-type natriuretic peptide proteins (NT-proBNP) level, heart rate, left ventricular ejection fraction (LVEF), and QTC abnormality between the two groups were statistically significant (P < 0.05). The COX multifactorial regression analysis revealed that hs-TnT, NT-proBNP, QTC abnormality prolongation and LVEF were all identified as risk factors for poor prognosis in elderly CAD patients (P < 0.05). proBNP, abnormal prolongation of QTC, and LVEF were identified as risk factors for cardiogenic syncope in elderly CAD patients, leading to a poor prognosis (P < 0.05). ROC curve analysis demonstrated that combining hs-TnT, NT-proBNP, QTC, and LVEF tests resulted in higher diagnostic accuracy than a single test alone, significantly improving the diagnostic accuracy (P < 0.05).

CONCLUSION

High hs-TnT and NT-proBNP levels, abnormally prolonged QTC, and LVEF > 50% are risk factors for cardiogenic syncope leading to adverse events in elderly CAD patients. The clinical Trial Number of this study is CLTR202356423, and it was registered in 2023.

Visual and quantitative lateral flow immunoassay based on Au@PS SERS tags for multiplex cardiac biomarkers

Rapid and sensitive detection of multiple biomarkers by lateral flow immunoassay (LFIA) remains challenging for signal amplification for commonly used nanotags. Herein, we report a novel LFIA strip for visual and highly sensitive analysis of two cardiac biomarkers based on functionalized gold nanoparticles @ polystyrene microsphere (Au@PS）microcavity as surface-enhanced Raman scattering (SERS) tags. Antibody-modified Au@PS was designed as a SERS label. The evanescent waves propagating along the surface of the PS microcavity and the localized surface plasmons of the gold nanoparticles were coupled to enhance the light-matter interaction synergistically for Raman signal enhancement. In this strategy, the proposed Au@PS SERS tags-based LFIA was carried out to quantify the content of the heart failure and infarct biomarkers synchronously within 15 min and get the limits of detection of 1 pg/mL and 10 pg/mL for cardiac troponin I (cTnI) and N-terminal natriuretic peptide precursor (NT-proBNP), respectively. The results demonstrated 10-20 folds more sensitivity than that of the standard colloidal gold strip and fluorescent strip for the same biomarkers. This novel quantitative LFIA shows promise as a high-sensitive and visual sensing method for relevant clinical and forensic analysis.

Diagnostic accuracy of high sensitivity troponin and association of electrocardiogram findings for mortality in syncope patients: A retrospective cohort study

High-sensitivity cardiac troponin-T (hs-cTnT) and electrocardiogram (ECG) are commonly ordered in daily practice in emergency medicine but their value on long term mortality in syncope patients is unclear. Our aim is to determine the diagnostic accuracy of hs-cTnT and association of ECG findings for 1-year mortality in patients presenting with syncope. In this retrospective cohort study, we included patients presenting with syncope to the emergency department (ED) between May 2020 and May 2021. Patient demographics, vital parameters on admission, ECG findings, hs-cTnT level at admission and 1-year mortality status were recorded. The study included 417 patients (62.4% women) with a mean age of 41.51 (standard deviation [SD] 17.1), 21 of whom were deceased within 1 year after syncope attack (5%). Patients with an abnormal QTc, T-Axis or frontal QRS-T angle had significantly higher 1-year mortality (OR: 9.26, 95% CI: 1.64-52.31; OR: 5.82, 95% CI: 1.69-20.1; 4.94, 95% CI: 1.45-16.84, respectively). The hs-cTnT level was 21.92 pg/mL (95% CI: 3.35-40.51 pg/mL) higher in the mortality group (P = .023). An abnormal QTc, T-Axis and frontal QRS-T angle are associated with a higher 1-year mortality rate and hs-cTnT has good diagnostic accuracy in detecting 1-year mortality for patients presenting with syncope.

Syncope Prediction Scores in the Emergency Department

Syncope is a common clinical presentation defined as a transient loss of consciousness (TLOC) due to cerebral hypoperfusion, characterized by a rapid onset, short duration, and spontaneous complete recovery. Different clinical decision rules (CDRs) and risk stratification scores have been developed to predict short- and long-term risks for adverse outcomes after syncope. The central theme of these prediction systems is consistent with the ESC syncope guidelines. Initial assessment according to the ESC guideline is essential until an optimal and well-validated risk score is available. The focus should be accurate risk stratification to allow prevention of adverse outcomes and optimize the use of limited healthcare resources. In this review article, we summarize and critically appraise the evidence regarding the CDRs for patients presenting with syncope.