The contribution of intermittent handheld electrocardiogram and continuous electrocardiogram monitoring with an implantable loop recorder to detect incident and recurrent atrial fibrillation during 1 year after coronary artery bypass graft surgery: A prospective cohort study

Atrial fibrillation incidence after coronary artery bypass graft surgery and percutaneous coronary intervention: the prospective AFAF cohort study

Objectives. Atrial fibrillation is a common arrhythmia in patients with ischemic heart disease. This study aimed to determine the cumulative incidence of new-onset atrial fibrillation after percutaneous coronary intervention or coronary artery bypass grafting surgery during 30 days of follow-up. Design. This was a prospective multi-center cohort study on atrial fibrillation incidence following percutaneous coronary intervention or coronary artery bypass grafting for stable angina or non-ST-elevation acute coronary syndrome. Heart rhythm was monitored for 30 days postoperatively by in-hospital telemetry and handheld thumb ECG recordings after discharge were performed. The primary endpoint was the cumulative incidence of atrial fibrillation 30 days after the index procedure. Results. In-hospital atrial fibrillation occurred in 60/123 (49%) coronary artery bypass graft and 0/123 percutaneous coronary intervention patients (p < .001). The cumulative incidence of atrial fibrillation after 30 days was 56% (69/123) of patients undergoing coronary artery bypass grafting and 2% (3/123) of patients undergoing percutaneous coronary intervention (p < .001). CABG was a strong predictor for atrial fibrillation compared to PCI (OR 80.2, 95% CI 18.1-354.9, p < .001). Thromboembolic stroke occurred in-hospital in one coronary artery bypass graft patient unrelated to atrial fibrillation, and at 30 days in two additional patients, one in each group. There was no mortality. Conclusion. New-onset atrial fibrillation during 30 days of follow-up was rare after percutaneous coronary intervention but common after coronary artery bypass grafting. A prolonged uninterrupted heart rhythm monitoring strategy identified additional patients in both groups with new-onset atrial fibrillation after discharge.

Recurrence of new-onset post-operative AF after cardiac surgery: detected by implantable loop recorders: A systematic review and Meta-analysis

BACKGROUND

Atrial fibrillation (AF) is one of the most common complications after cardiac surgery. New-onset post-operative AF may signal an elevated risk of AF and associated outcomes in long-term follow-up. We aimed to estimate the rate of AF recurrence as detected by an implantable loop recorder (ILR) in patients experiencing post-operative AF within 30 days after cardiac surgery.

METHODS

We searched MEDLINE, Embase and Cochrane CENTRAL to April 2023 for studies of adults who did not have known AF, experienced new-onset AF within 30 days of cardiac surgery and received an ILR. We pooled individual participant data on timing of AF recurrence using a random-effects model with a frailty model applied to a Cox proportional hazard analysis.

RESULTS

From 8671 citations, 8 single-centre prospective cohort studies met eligibility criteria. Data were available from 185 participants in 7 studies, with a median follow-up of 1.7 (IQR: 1.3-2.8) years. All included studies were at a low risk of bias. Pooled AF recurrence rates following 30 post-operative days were 17.8% (95% CI 11.9%-23.2%) at 3 months, 24.4% (17.7%-30.6%) at 6 months, 30.1% (22.8%-36.7%) at 12 months and 35.3% (27.6%-42.2%) at 18 months.

CONCLUSIONS

In patients who experience new-onset post-operative AF after cardiac surgery, AF recurrence lasting at least 30 s occurs in approximately 1 in 3 in the first year after surgery. The optimal frequency and modality to use for monitoring for AF recurrence in this population remain uncertain.

Recurrence of Atrial Fibrillation in Patients With New-Onset Postoperative Atrial Fibrillation After Coronary Artery Bypass Grafting

Importance

New-onset postoperative atrial fibrillation (POAF) occurs in approximately 30% of patients undergoing coronary artery bypass grafting (CABG). It is unknown whether early recurrence is associated with worse outcomes.

Objective

To test the hypothesis that early AF recurrence in patients with POAF after CABG is associated with worse outcomes.

Design, Setting, and Participants

This Swedish nationwide cohort study used prospectively collected data from the SWEDEHEART (Swedish Web System for Enhancement and Development of Evidence-Based Care in Heart Disease Evaluated According to Recommended Therapies) registry and 3 other mandatory national registries. The study included patients who underwent isolated first-time CABG between January 1, 2007, and December 31, 2020, and developed POAF. Data analysis was performed between March 6 and September 16, 2023.

Exposure

Early AF recurrence defined as an episode of AF leading to hospital care within 3 months after discharge.

Main Outcomes and Measures

The primary outcome was all-cause mortality. Secondary outcomes included ischemic stroke, any thromboembolism, heart failure hospitalization, and major bleeding within 2 years after discharge. The groups were compared with multivariable Cox regression models, with early AF recurrence as a time-dependent covariate. The hypothesis tested was formulated after data collection.

Results

Of the 35 329 patients identified, 10 609 (30.0%) developed POAF after CABG and were included in this study. Their median age was 71 (IQR, 66-76) years. The median follow-up was 7.1 (IQR, 2.9-9.0) years, and most patients (81.6%) were men. Early AF recurrence occurred in 6.7% of patients. Event rates (95% CIs) per 100 patient-years with vs without early AF recurrence were 2.21 (1.49-3.24) vs 2.03 (1.83-2.25) for all-cause mortality, 3.94 (2.92-5.28) vs 2.79 (2.56-3.05) for heart failure hospitalization, and 3.97 (2.95-5.30) vs 2.74 (2.51-2.99) for major bleeding. No association between early AF recurrence and all-cause mortality was observed (adjusted hazard ratio [AHR], 1.17 [95% CI, 0.80-1.74]; P = .41). In exploratory analyses, there was an association with heart failure hospitalization (AHR, 1.80 [95% CI, 1.32-2.45]; P = .001) and major bleeding (AHR, 1.92 [1.42-2.61]; P < .001).

Conclusions and Relevance

In this cohort study of early AF recurrence after POAF in patients who underwent CABG, no association was found between early AF recurrence and all-cause mortality. Exploratory analyses showed associations between AF recurrence and heart failure hospitalization, oral anticoagulation, and major bleeding.

A Deep Learning Approach for Atrial Fibrillation Classification Using Multi-Feature Time Series Data from ECG and PPG

Atrial fibrillation is a prevalent cardiac arrhythmia that poses significant health risks to patients. The use of non-invasive methods for AF detection, such as Electrocardiogram and Photoplethysmogram, has gained attention due to their accessibility and ease of use. However, there are challenges associated with ECG-based AF detection, and the significance of PPG signals in this context has been increasingly recognized. The limitations of ECG and the untapped potential of PPG are taken into account as this work attempts to classify AF and non-AF using PPG time series data and deep learning. In this work, we emploted a hybrid deep neural network comprising of 1D CNN and BiLSTM for the task of AF classification. We addressed the under-researched area of applying deep learning methods to transmissive PPG signals by proposing a novel approach. Our approach involved integrating ECG and PPG signals as multi-featured time series data and training deep learning models for AF classification. Our hybrid 1D CNN and BiLSTM model achieved an accuracy of 95% on test data in identifying atrial fibrillation, showcasing its strong performance and reliable predictive capabilities. Furthermore, we evaluated the performance of our model using additional metrics. The precision of our classification model was measured at 0.88, indicating its ability to accurately identify true positive cases of AF. The recall, or sensitivity, was measured at 0.85, illustrating the model's capacity to detect a high proportion of actual AF cases. Additionally, the F1 score, which combines both precision and recall, was calculated at 0.84, highlighting the overall effectiveness of our model in classifying AF and non-AF cases.

Post-operative atrial fibrillation after cardiac surgery: Challenges throughout the patient journey

Atrial fibrillation (AF) is the most common complication of cardiac surgery, occurring in up to half of patients. Post-operative AF (POAF) refers to new-onset AF in a patient without a history of AF that occurs within the first 4 weeks after cardiac surgery. POAF is associated with short-term mortality and morbidity, but its long-term significance is unclear. This article reviews existing evidence and research challenges for the management of POAF in patients who have had cardiac surgery. Specific challenges are discussed in four phases of care. Pre-operatively, clinicians need to be able to identify high-risk patients, and initiate prophylaxis to prevent POAF. In hospital, when POAF is detected, clinicians need to manage symptoms, stabilize hemodynamics and prevent increases in length of stay. In the month after discharge, the focus is on minimizing symptoms and preventing readmission. Some patients require short term oral anticoagulation for stroke prevention. Over the long term (2-3  months after surgery and beyond), clinicians need to identify which patients with POAF have paroxysmal or persistent AF and can benefit from evidence-based therapies for AF, including long-term oral anticoagulation.

Evidence-Based Analysis of the Emergency Temporary Cardiac Pacing (Electrical Stimulation from Metal Wire Electrode)

The patient's Cr (creatinine), BUN (blood urea nitrogen), HBG (hemoglobin), VT (ventricular tachycardia), pacing frequency, puncture point, emergency to permanent pacing time, pacing current (mA), pacing threshold current (mA), and admission diagnosis data were collected. The data were subjected to frequency statistics, curve regression analysis, PLS regression analysis, adjustment analysis, chi-square test, ridge regression analysis, discriminant analysis, negative binomial regression analysis, Poisson regression analysis, and stepwise regression analysis. Some findings include the following: (1) Cr has a significant positive effect on HBG, and BUN has a significant negative effect on HBG. (2) VT has a negative correlation with age and a positive correlation with CK-MB and CK (creatinine kinase). (3) Myocarditis has a negative correlation with age and a significant positive correlation with CTnI (cardiac troponin I). (4) AST (aspartate transaminase) and ALT (alanine aminotransferase) have a significant positive impact on DDI (D-dimer), while CTnI has a significant negative impact on DDI. MYO (myoglobin) has no impact relationship to DDI. (5) ALT has a significant positive relationship with APTT (partial thromboplastin time). (6) Alb (albumin) and TBIL (total bilirubin) have a significant positive effect on PLT (platelet) count, while pro-BNP (B-type natriuretic peptide) and MYO have a significant negative effect on PLT. (7) CK has a significant positive effect on INR (international normalized ratio). (8) The relationship between sinus node dysfunction and VT significantly affect the pacing frequency (beats/minute). For third-degree atrioventricular block, different samples of sinus node dysfunction showed significant differences. (9) There is a significant positive correlation between pacing current (mA) and pacing threshold current (mA). (10) There was a significant positive correlation between perceived voltage (mV) and the time from emergency to permanent pacing. Admission diagnosis has a significant positive impact on the time from emergency to permanent pacing. The change (increase) in time from emergency to permanent pacing was 1.137-fold when an additional condition was diagnosed on admission.