Heart Rhythm O2最新文献

The introduction of pulsed field ablation (PFA) in electrophysiology marks a significant advancement, promising efficacy comparable to thermal ablation methods while potentially providing safety advantages. Despite a generally favorable safety profile in human trials and postmarket registries, cautious evaluation of PFA's safety is essential. This review provides a comprehensive overview of key safety considerations as we discuss a myriad of considerations ranging from thermal effects, gaseous microbubble formation, muscle contractions, and proarrhythmia to procedural techniques. We explore specific safety concerns with phrenic nerve injury, cerebral lesions, coronary artery spasm, hemolysis and pulmonary bleeding. Vigilance in safety monitoring, coupled with advancements in procedural techniques and understanding of PFA's unique effects, is crucial for optimizing the safe and effective use of PFA.

Background

Studies have shown that the risk of new-onset heart failure (HF) is higher postimplantation for patients receiving right ventricular pacing.

Objective

This study aimed to investigate incidence, risk factors, and implications for long-term prognosis of new-onset HF in patients after pacemaker implantation.

Methods

Patients without pre-existing HF who received a pacemaker in Sweden during the period of 2005 to 2020 were identified via the nationwide Pacemaker Registry. Data were crossmatched with the population registry and national disease registries. The primary outcome was new-onset HF within 5 years, and a risk score for this was developed and validated.

Results

In all, 65,579 patients met the inclusion criteria (10,351 single-chamber ventricular and 55,228 dual-chamber pacemakers). A total of 13,792 (21.0%) patients were diagnosed with HF within 5 years postimplantation. Of these, 6244 (45.3%) were hospitalized for HF. Patients with new-onset HF were more likely to die within 5 years (41.2% vs 19.7%, P < .0001). Risk factors for new-onset HF included increasing age, male sex, hypertension, diabetes, atrial fibrillation, chronic lung and kidney disease, ischemic heart disease, and atrioventricular block. In a combined score using these variables, patients in the highest risk-score quartile had a hazard ratio of 5.36 (95% CI 4.91–5.86, P < .001) and an absolute risk of 32% for developing HF.

Conclusion

Pacemaker therapy is associated with >20% risk of new-onset HF within 5 years, and we identified 9 risk factors associated with the diagnosis of new-onset HF. The proposed score based on these variables can be used to identify patients at high risk for new-onset HF.

Background

Artificial intelligence–machine learning (AI-ML) has demonstrated the ability to extract clinically useful information from electrocardiograms (ECGs) not available using traditional interpretation methods. There exists an extensive body of AI-ML research in fields outside of cardiology including several open-source AI-ML architectures that can be translated to new problems in an “off-the-shelf” manner.

Objective

We sought to address the limited investigation of which if any of these off-the-shelf architectures could be useful in ECG analysis as well as how and when these AI-ML approaches fail.

Methods

We applied 6 off-the-shelf AI-ML architectures to detect low left ventricular ejection fraction (LVEF) in a cohort of ECGs from 24,868 patients. We assessed LVEF classification and explored patient characteristics associated with inaccurate (false positive or false negative) LVEF prediction.

Results

We found that all of these network architectures produced LVEF detection area under the receiver-operating characteristic curve values above 0.9 (averaged over 5 instances per network), with the ResNet 18 network performing the highest (average area under the receiver-operating characteristic curve of 0.917). We also observed that some patient-specific characteristics such as race, sex, and presence of several comorbidities were associated with lower LVEF prediction performance.

Conclusions

This demonstrates the ability of off-the-shelf AI-ML architectures to detect clinically useful information from ECGs with performance matching contemporary custom-build AI-ML architectures. We also highlighted the presence of possible biases in these AI-ML approaches in the context of patient characteristics. These findings should be considered in the pursuit of efficient and equitable deployment of AI-ML technologies moving forward.

Background

A high annual failure rate of the Linox family defibrillator lead was reported in various small single-center studies. No independent multicenter long-term performance information exists for this lead.

Objective

Our aim was to assess the longevity of the Linox family leads and to evaluate clinical variables and adverse events associated with failure.

Methods

This 4-center study included adults >18 years of age who received Linox family leads for the prevention of sudden cardiac death. From November 2006 to November 2016, a total of 3993 high-voltage leads of the Linox family were implanted and followed up on.

Results

The absolute failure rate was 10.6% (dwell time to lead failure of 6.3 ± 3.4 years). Multivariate analysis confirmed younger age (for every 5 years younger than 65 years) (hazard ratio 1.09, 95% confidence interval 1.05–1.14, P < .001) and subclavian access (hazard ratio 1.46, 95% confidence interval 1.18–1.81, P < .001) as independent risk factors for lead failure. Patients frequently presented themselves with inappropriate shocks (20% in patients with lead failure) due to detection of nonphysiologic high-rate signals/noise.

Conclusion

This is the largest physician-driven multicenter study on the very long-term performance of Linox family leads. Our data report a remarkably high failure rate of these leads. Our findings have significant implications for the management of patients. Monitoring by remote care should be available for all active Linox family leads.

In patients with a mechanical tricuspid prosthetic valve, the transvenous position of a ventricular lead through the coronary sinus (CS) is a good alternative option to right ventricular or epicardial lead implantation. In cardiac resynchronization therapy, pacing the left ventricular lateral wall was considered the best site for the CS lead. However, for patients without a left bundle branch block, the best position of CS leads remains controversial. Here, we present a case of placing CS lead in the anterior interventricular vein. Measurements at implantation and 2 years’ follow-up reported low pacing thresholds with good sensing thresholds. The electrocardiograph showed narrow QRS complexes (120 ms) and follow-up echocardiography at 2 years presented left ventricular ejection fraction 58.9%.

Background

Transthyretin cardiac amyloidosis (ATTR-CA) is associated with an increased incidence of arrhythmias. We hypothesized that 2-week noninvasive ambulatory cardiac rhythm monitoring of patients with ATTR-CA would detect high rates of atrial fibrillation/atrial flutter (AF/AFL) and nonsustained ventricular tachycardia (NSVT).

Objective

The study sought to characterize arrhythmia in patients with ATTR-CA on 2-week, noninvasive cardiac rhythm monitors.

Methods

A total of 38 patients with ATTR-CA who underwent 2-week remote external patch monitoring were included in this single-center retrospective study. An age-matched control group included 38 patients who underwent the same cardiac rhythm monitoring as part of neurological workup.

Results

Of the ATTR-CA cohort, 26.3% had AF/AFL and 81.6% had NSVT. ATTR-CA was associated with higher rates of AF/AFL and NSVT compared with the control group. At a median follow-up of 45 weeks, there was no association between the presence of AF/AFL or NSVT on remote monitor in the ATTR-CA group and a composite of adverse clinical outcome.

Conclusion

ATTR-CA was associated with an elevated rate of AF/AFL and an even higher rate of NSVT on noninvasive ambulatory monitors. While evidence regarding the management of arrhythmias, particularly NSVT/ventricular tachycardia, in ATTR-CA remains limited, 2-week noninvasive cardiac monitoring can be considered to aid in risk stratification for both atrial and ventricular arrhythmias.

Background

Atrial fibrillation (AF) and heart failure (HF) are cardiac disorders that often coexist.

Objective

This study aimed to investigate how time to ablation could influence the outcomes of AF patients with pre-existing HF.

Methods

Using the 2013 to 2022 Optum Clinformatics database, AF patients with pre-existing HF were classified into 2 groups: early ablation (ablation within 6 months of AF diagnosis) and late ablation (ablation in the 6- to 24-month period after AF diagnosis). Outcomes including AF-related hospitalization, electrical cardioversion, repeat ablation, antiarrhythmic drug (AAD) use, and AF recurrence (a composite outcome of the aforementioned events) were assessed in the postblanking 24-month period. Inverse probability of treatment weighted Poisson regression estimated risk ratio (RR) and 95% confidence interval (CI) for each outcome.

Results

Overall, 601 patients were identified (early ablation: 347; late ablation: 254). In 24 months, the weighted data suggested that patients in the early ablation cohort had significantly lower rate of composite outcome (49.32% vs 61.39%, P = .01), repeat ablation (8.56% vs 17.35%, P < .01), and AAD use (35.95% vs 47.92%, P = .01). Early ablation was associated with a 20%, 51%, and 25% lower risk of composite outcome (RR 0.80, 95% CI 0.69–0.94), repeat ablation (RR 0.49, 95% CI 0.31–0.79), and AAD use (RR 0.75, 95% CI 0.61–0.92), respectively. No significant difference in AF-related hospitalization and electrical cardioversion were observed.

Conclusion

AF patients with pre-existing HF undergoing ablation within 6 months of AF diagnosis have a lower risk of AF recurrence than those undergoing late ablation, which was evidenced by a lower rate of repeat ablation and AAD use.