Paroxysmal atrial fibrillation as a predictor of pacemaker implantation in patients with unexplained syncope

Usefulness of last generation insertable cardiac monitors in the diagnosis of unexplained syncope

AIMS

Guidelines recommend insertable cardiac monitor (ICM) in the early phases of the evaluation of unexplained syncope (US) syncope, when an arrhythmic etiology is suspected. We examined the diagnostic yield of the last generation ICM (LG-ICM) to establish the causes of US, by assessing in the clinical practice the incidence of: relevant arrhythmia diagnosis, syncope recurrences and CM-guided cardiac electronic device (CIED) implantation. We investigated also baseline patient characteristics associated to an increased risk of relevant arrhythmias and of syncope recurrence.

METHODS

Data prospectively collected from consecutive patients receiving LG-ICM for investigation of US or presyncope in our institution between November 2020 and January 2023 were analyzed.

RESULTS

A total of 109 patients (mean age 64.4 ± 16.1 years, 40.4% women) with US or pre-syncope episodes underwent implantation of the LG-ICM. During a mean follow-up of 11.7 ± 8.1 months, LG-ICM diagnostic yield was 42%. In particular, LG-ICM detected cardiac arrhythmias in 29 (27%) patients (in 6 out of them during a syncope recurrence) and to exclude the arrhythmic origin of the syncope in additional 19 (17%) patients. LG-ICM guided the implantation of a CIED in 16 (15%) US patients, due to the diagnosis of asystole or severe bradycardia. Age ≥ 65 years (p = 0.012) and atrial arrhythmia history (p = 0.004) are significant independent predictors of arrhythmic diagnoses performed by LG-ICM, while CAD is predictor of syncope recurrence (bordering on statistical significance, p = 0.056).

CONCLUSIONS

The diagnostic yield of LG-ICM in US syncope is comparable to those of ILR and previous generation ICM. The advantages of LG-ICM should be sought in lower hospital workload necessary to manage ICM data. Age ≥ 65 years and atrial arrhythmia history are independent predictors of significant ICM-detected arrhythmias.

Predictors of pacemaker requirement in patients receiving implantable loop recorders for unexplained syncope: A systematic review and meta-analysis

BACKGROUND

Implantable loop recorders (ILRs) are increasingly used to evaluate patients with unexplained syncope. Identification of all predictors of bradycardic syncope and consequent permanent pacemaker (PPM) insertion is of substantial clinical interest as patients in the highest risk category may benefit from upfront pacemaker insertion.

OBJECTIVE

We performed a systematic review and meta-analysis to identify risk predictors for PPM insertion in ILR recipients with unexplained syncope.

METHODS

An electronic database search (MEDLINE, Embase, Scopus, Cochrane) was performed in June 2023. Studies evaluating ILR recipients with unexplained syncope and recording risk factors for eventual PPM insertion were included. A random effects model was used to calculate the pooled odds ratio (OR) for clinical and electrocardiographic characteristics with respect to future PPM requirement.

RESULTS

Eight studies evaluating 1007 ILR recipients were included; 268 patients (26.6%) underwent PPM insertion during study follow-up. PPM recipients were older (mean age, 70.2 ± 15.4 years vs 61.6 ± 19.7 years; P < .001). PR prolongation on baseline electrocardiography was a significant predictor of PPM requirement (pooled OR, 2.91; 95% confidence interval, 1.63-5.20). The presence of distal conduction system disease, encompassing any bundle branch or fascicular block, yielded a pooled OR of 2.88 for PPM insertion (95% confidence interval, 1.53-5.41). Injurious syncope and lack of syncopal prodrome were not significant predictors of PPM insertion. Sinus node dysfunction accounted for 62% of PPM insertions, whereas atrioventricular block accounted for 26%.

CONCLUSION

Approximately one-quarter of ILR recipients for unexplained syncope require eventual PPM insertion. Advancing age, PR prolongation, and distal conduction disease are the strongest predictors for PPM requirement.

Artificial Intelligence-Enabled Electrocardiography Predicts Future Pacemaker Implantation and Adverse Cardiovascular Events

Medical advances prolonging life have led to more permanent pacemaker implants. When pacemaker implantation (PMI) is commonly caused by sick sinus syndrome or conduction disorders, predicting PMI is challenging, as patients often experience related symptoms. This study was designed to create a deep learning model (DLM) for predicting future PMI from ECG data and assess its ability to predict future cardiovascular events. In this study, a DLM was trained on a dataset of 158,471 ECGs from 42,903 academic medical center patients, with additional validation involving 25,640 medical center patients and 26,538 community hospital patients. Primary analysis focused on predicting PMI within 90 days, while all-cause mortality, cardiovascular disease (CVD) mortality, and the development of various cardiovascular conditions were addressed with secondary analysis. The study's raw ECG DLM achieved area under the curve (AUC) values of 0.870, 0.878, and 0.883 for PMI prediction within 30, 60, and 90 days, respectively, along with sensitivities exceeding 82.0% and specificities over 81.9% in the internal validation. Significant ECG features included the PR interval, corrected QT interval, heart rate, QRS duration, P-wave axis, T-wave axis, and QRS complex axis. The AI-predicted PMI group had higher risks of PMI after 90 days (hazard ratio [HR]: 7.49, 95% CI: 5.40-10.39), all-cause mortality (HR: 1.91, 95% CI: 1.74-2.10), CVD mortality (HR: 3.53, 95% CI: 2.73-4.57), and new-onset adverse cardiovascular events. External validation confirmed the model's accuracy. Through ECG analyses, our AI DLM can alert clinicians and patients to the possibility of future PMI and related mortality and cardiovascular risks, aiding in timely patient intervention.

Incidental and anticipated arrhythmic diagnoses in patients with an implantable cardiac monitor

AIMS

In this study, we investigated a cohort of unselected patients with various indications for an implantable cardiac monitor (ICM). Our main objectives were to determine the incidence of arrhythmic diagnoses, both anticipated and incidental in relation to the ICM indication, and to assess their clinical relevance.

METHODS

We examined remote monitoring transmissions from patients with an ICM at four Italian sites to identify occurrences of cardiac arrhythmias. Concurrently, we collected data on medical actions taken in response to arrhythmic findings.

RESULTS

The study included 119 patients, with a median follow-up period of 371 days. ICM indications were syncope/presyncope (46.2%), atrial fibrillation management (31.1%), and cryptogenic stroke (22.7%). In the atrial fibrillation management group, atrial fibrillation was the most common finding, with an incidence of 36% [95% confidence interval (CI) 22-55%] at 18 months. Rates of atrial fibrillation were not significantly different between patients with cryptogenic stroke and syncope/presyncope [17% (95% CI 7-40%) vs. 8% (95% CI 3-19%), P  = 0.229].For patients with cryptogenic stroke, the incidence of asystole and bradyarrhythmias at 18 months was 23% (95% CI 11-45%) and 42% (95% CI 24-65%), respectively, similar to estimates obtained for patients implanted for syncope/presyncope ( P  = 0.277 vs. P  = 0.836).Overall, 30 patients (25.2%) required medical intervention following ICM-detected arrhythmias, predominantly involving atrial fibrillation ablation (10.9%) and medication therapy changes (10.1%).

CONCLUSION

In a real-life population with heterogeneous insertion indications, approximately 25% of patients received ICM-guided medical interventions within a short timeframe, including treatments for incidental findings. Common incidental arrhythmic diagnoses were bradyarrhythmias in patients with cryptogenic stroke and atrial fibrillation in patients with unexplained syncope.

Predictors of pacemaker requirement in patients with implantable loop recorder and unexplained syncope: A systematic review and meta-analysis

Identifying the underlying cause of unexplained syncope is crucial for appropriate management of recurrent syncopal episodes. Implantable loop recorders (ILRs) have emerged as valuable diagnostic tools for monitoring patients with unexplained syncope. However, the predictors of pacemaker requirement in patients with ILR and unexplained syncope remain unclear. In this study, we shed light on these prognostic factors. PubMed/MEDLINE, EMBASE, Web of Science, and Cochrane CENTRAL were systematically searched until May 04, 2023. Studies that evaluated the predictors of pacemaker requirement in patients with implantable loop recorder and unexplained syncope were included. The "Quality In Prognosis Studies" appraisal tool was used for quality assessment. The pooled odds ratio (OR) with 95% confidence intervals (CIs) was calculated. The publication bias was evaluated using Egger's and Begg's tests. Ten studies (n = 4200) were included. Right bundle branch block (OR: 3.264; 95% CI: 1.907-5.588, p < .0001) and bifascicular block (OR: 2.969; 95% CI: 1.859-4.742, p < .0001) were the strongest predictors for pacemaker implantation. Pacemaker requirement was more than two times in patients with atrial fibrillation, sinus bradycardia and first degree AV block. Valvular heart disease, diabetes mellitus, and hypertension were also significantly more in patients with pacemaker implantation. Age (standardized mean difference [SMD]: 0.560; 95% CI: 0.410/0.710, p < .0001) and PR interval (SMD: 0.351; 95% CI: 0.150/0.553, p = .001) were significantly higher in patients with pacemaker requirement. Heart conduction disorders, atrial arrhythmias and underlying medical conditions are main predictors of pacemaker device implantation following loop recorder installation in unexplained syncopal patients.

Clinical Predictors of Pacing Device Implantation in Implantable Cardiac Monitor Recipients for Unexplained Syncope

Background

Implantable cardiac monitors (ICMs) help investigate the cause of unexplained syncope, but the probability and predictors of needing a pacing device thereafter remain unclear.

Methods

We retrospectively analyzed the data of patients who received ICM insertion for unexplained syncope with suspected arrhythmic etiology. The data were obtained from a nationwide database obtained between April 1, 2012 and March 31, 2020. Multivariable mixed-effects survival analysis was performed to identify predictors of pacing device implantation (PDI), and a risk score model was developed accordingly.

Results

In total, 2905 patients (age: 72 years [range: 60-78]) implanted with ICMs to investigate the cause of syncope were analyzed. During the median follow-up period of 128 days (range: 68-209) days, 473 patients (16%) underwent PDI. Older age, history of atrial fibrillation, bundle branch block (BBB), and diabetes were independent predictors of PDI in multivariable analysis. A risk score model was developed with scores ranging from 0 to 32 points. When patients with the lowest quartile score (0-13 points) were used as a reference, those with higher quartiles had a higher risk of PDI (second quartile: 14-15 points, hazard ratio [HR]: 3.86, 95% confidence interval [CI]: 2.62-5.68; third quartile: 16-18 points, HR: 4.67, 95% CI: 3.14-6.94; fourth quartile: 19-32 points, HR: 6.59, 95% CI: 4.47-9.71).

Conclusions

The 4 identified predictors are easily assessed during the initial evaluation of patients with syncope. They may help identify patients with a higher risk of requiring permanent PDI.