Catheter ablation of typical atrial flutter improves cardiac chamber size and function.

INTRODUCTION: Cavo-tricuspid isthmus (CTI) dependent atrial flutter (AFL) is one of the most common atrial arrhythmias involving the right atrium (RA) for which radiofrequency catheter ablation has been widely used as a therapy of choice. However, there is limited data on the effect of this intervention on cardiac size and function. METHODS: A retrospective study was conducted on 468 patients who underwent ablation for CTI dependent typical AFL at a single institution between 2010 and 2019. After excluding patients with congenital or rheumatic heart disease, heart transplant recipients, or those without baseline echocardiogram, a total of 130 patients were included in the analysis. Echocardiographic data were analyzed at baseline before ablation, and at early follow-up within 1-year postablation. Follow-up echocardiographic data was available for 55 patients. RESULTS: Of the 55 patients with CTI-AFL, the mean age was 64.2 ± 14.8 years old with 14.5% (n = 8) female. The average left ventricular ejection fraction (LVEF) significantly improved on follow-up echo (40.2 ± 16.9 to 50.4 ± 14.9%, p < .0001), of which 50% of patients had an improvement in LVEF of at least 10%. There was a significant reduction in left atrial volume index (82.74 ± 28.5 to 72.96 ± 28 mL/m2 , p = .008) and RA volume index (70.62 ± 25.6 to 64.15 ± 31 mL/m2 , p = .046), and a significant improvement in left atrial reservoir strain (13.04 ± 6.8 to 19.10 ± 7.7, p < .0001). CONCLUSIONS: Patients who underwent CTI dependent AFL ablation showed an improvement in cardiac size and function at follow-up evaluation. While long-term results are still unknown, these findings indicate that restoration of sinus rhythm in patients with typical AFL is associated with improvement in atrial size and left ventricular function.

Automated prediction of isthmus areas in scar-related atrial tachycardias using artificial intelligence.

INTRODUCTION: Ablation of scar-related reentrant atrial tachycardia (SRRAT) involves identification and ablation of a critical isthmus. A graph convolutional network (GCN) is a machine learning structure that is well-suited to analyze the irregularly-structured data obtained in mapping procedures and may be used to identify potential isthmuses. METHODS: Electroanatomic maps from 29 SRRATs were collected, and custom electrogram features assessing key tissue and wavefront properties were calculated for each point. Isthmuses were labeled off-line. Training data was used to determine the optimal GCN parameters and train the final model. Putative isthmus points were predicted in the training and test populations and grouped into proposed isthmus areas based on density and distance thresholds. The primary outcome was the distance between the centroids of the true and closest proposed isthmus areas. RESULTS: A total of 193 821 points were collected. Thirty isthmuses were detected in 29 tachycardias among 25 patients (median age 65.0, 5 women). The median (IQR) distance between true and the closest proposed isthmus area centroids was 8.2 (3.5, 14.4) mm in the training and 7.3 (2.8, 16.1) mm in the test group. The mean overlap in areas, measured by the Dice coefficient, was 11.5 ± 3.2% in the training group and 13.9 ± 4.6% in the test group. CONCLUSION: A GCN can be trained to identify isthmus areas in SRRATs and may help identify critical ablation targets.

Practical Considerations for the Application of Nonlinear Indices Characterizing the Atrial Substrate in Atrial Fibrillation.

Atrial fibrillation (AF) is the most common cardiac arrhythmia, and in response to increasing clinical demand, a variety of signals and indices have been utilized for its analysis, which include complex fractionated atrial electrograms (CFAEs). New methodologies have been developed to characterize the atrial substrate, along with straightforward classification models to discriminate between paroxysmal and persistent AF (ParAF vs. PerAF). Yet, most previous works have missed the mark for the assessment of CFAE signal quality, as well as for studying their stability over time and between different recording locations. As a consequence, an atrial substrate assessment may be unreliable or inaccurate. The objectives of this work are, on the one hand, to make use of a reduced set of nonlinear indices that have been applied to CFAEs recorded from ParAF and PerAF patients to assess intra-recording and intra-patient stability and, on the other hand, to generate a simple classification model to discriminate between them. The dominant frequency (DF), AF cycle length, sample entropy (SE), and determinism (DET) of the Recurrence Quantification Analysis are the analyzed indices, along with the coefficient of variation (CV) which is utilized to indicate the corresponding alterations. The analysis of the intra-recording stability revealed that discarding noisy or artifacted CFAE segments provoked a significant variation in the CV(%) in any segment length for the DET and SE, with deeper decreases for longer segments. The intra-patient stability provided large variations in the CV(%) for the DET and even larger for the SE at any segment length. To discern ParAF versus PerAF, correlation matrix filters and Random Forests were employed, respectively, to remove redundant information and to rank the variables by relevance, while coarse tree models were built, optimally combining high-ranked indices, and tested with leave-one-out cross-validation. The best classification performance combined the SE and DF, with an accuracy (Acc) of 88.3%, to discriminate ParAF versus PerAF, while the highest single Acc was provided by the DET, reaching 82.2%. This work has demonstrated that due to the high variability of CFAEs data averaging from one recording place or among different recording places, as is traditionally made, it may lead to an unfair oversimplification of the CFAE-based atrial substrate characterization. Furthermore, a careful selection of reduced sets of features input to simple classification models is helpful to accurately discern the CFAEs of ParAF versus PerAF.

Advanced heart failure patients supported with ambulatory inotropic therapy: What defines success of therapy?

OBJECTIVE: The objective of this study was to describe the profiles and outcomes of a cohort of advanced heart failure patients on ambulatory inotropic therapy (AIT). BACKGROUND: With the growing burden of patients with end-stage heart failure, AIT is an increasingly common short or long-term option, for use as bridge to heart transplant (BTT), bridge to ventricular assist device (BTVAD), bridge to decision regarding advanced therapies (BTD) or as palliative care. AIT may be preferred by some patients and physicians to facilitate hospital discharge. However, counseling patients on risks and benefits is critically important in the modern era of defibrillators, durable mechanical support and palliative care. METHODS: We retrospectively studied a cohort of 241 patients on AIT. End points included transplant, VAD implantation, weaning of inotropes, or death. The primary outcomes were survival on AIT and ability to reach intended goal if planned as BTT or BTVAD. We also evaluated recurrent heart failure hospitalizations, incidence of ventricular arrhythmias (VT/VF) and indwelling line infections. Unintended consequences of AIT, such reaching unintended end point (e.g. VAD implantation in BTT patient) or worse than expected outcome after LVAD or HT, were recorded. RESULTS: Mean age of the cohort was 60.7 ± 13.2 years, 71% male, with Class III-IV heart failure (56% non-ischemic). Average ejection fraction was 19.4 ± 10.2%, pre-AIT cardiac index was 1.5 ± 0.4 L/min/m2 and 24% had prior ventricular arrhythmias. Overall on-AIT 1-year survival was 83%. Hospitalizations occurred in 51.9% (125) of patients a total of 174 times for worsening heart failure, line complication or ventricular arrhythmia. In the BTT cohort, only 42% were transplanted by the end of follow-up, with a 14.8% risk of death or delisting for clinical deterioration. For the patients who were transplanted, 1-year post HT survival was 96.7%. In the BTVAD cohort, 1-year survival after LVAD was 90%, but with 61.7% of patients undergoing LVAD as INTERMACS 1-2. In the palliative care cohort, only 24.5% of patients had a formal palliative care consult prior to AIT. CONCLUSIONS: AIT is a strategy to discharge advanced heart failure patients from the hospital. It may be useful as bridge to transplant or ventricular assist device, but may be limited by complications such as hospitalizations, infections, and ventricular arrhythmias. Of particular note, it appears more challenging to bridge to transplant on AIT in the new allocation system. It is important to clarify the goals of AIT therapy upfront and continue to counsel patients on risks and benefits of the therapy itself and potential unintended consequences. Formalized, multi-disciplinary care planning is essential to clearly define individualized patient, as well as programmatic goals of AIT.

Electrocardiographic recognition of benign and malignant right ventricular arrhythmias.

Ventricular arrhythmias (VAs) can originate from different anatomical locations of the right ventricle. Ventricular arrhythmias originating from right ventricle have unique electrocardiographic (ECG) characteristics that can be utilized to localize the origin of the arrhythmia. This is crucial in pre-procedural planning particularly for ablation treatments. Moreover, non-ischaemic structural heart diseases, such as infiltrative and congenital heart diseases, are associated with the VAs that exhibit particular ECG findings. This article comprehensively reviews discriminatory ECG characteristics of VAs in the right ventricle with and without structural right ventricular diseases.

Performance of electrophysiology procedures at an academic medical center amidst the 2020 coronavirus (COVID-19) pandemic.

A global coronavirus (COVID-19) pandemic occurred at the start of 2020 and is already responsible for more than 74 000 deaths worldwide, just over 100 years after the influenza pandemic of 1918. At the center of the crisis is the highly infectious and deadly SARS-CoV-2, which has altered everything from individual daily lives to the global economy and our collective consciousness. Aside from the pulmonary manifestations of disease, there are likely to be several electrophysiologic (EP) sequelae of COVID-19 infection and its treatment, due to consequences of myocarditis and the use of QT-prolonging drugs. Most crucially, the surge in COVID-19 positive patients that have already overwhelmed the New York City hospital system requires conservation of hospital resources including personal protective equipment (PPE), reassignment of personnel, and reorganization of institutions, including the EP laboratory. In this proposal, we detail the specific protocol changes that our EP department has adopted during the COVID-19 pandemic, including performance of only urgent/emergent procedures, after hours/7-day per week laboratory operation, single attending-only cases to preserve PPE, appropriate use of PPE, telemedicine and video chat follow-up appointments, and daily conferences to collectively manage the clinical and ethical dilemmas to come. We discuss also discuss how we perform EP procedures on presumed COVID positive and COVID tested positive patients to highlight issues that others in the EP community may soon face in their own institution as the virus continues to spread nationally and internationally.

Clinical and cardiac characteristics of COVID-19 mortalities in a diverse New York City Cohort.

INTRODUCTION: Electrocardiographic characteristics in COVID-19-related mortality have not yet been reported, particularly in racial/ethnic minorities. METHODS AND RESULTS: We reviewed demographics, laboratory and cardiac tests, medications, and cardiac rhythm proximate to death or initiation of comfort care for patients hospitalized with a positive SARS-CoV-2 reverse-transcriptase polymerase chain reaction in three New York City hospitals between March 1 and April 3, 2020 who died. We described clinical characteristics and compared factors contributing toward arrhythmic versus nonarrhythmic death. Of 1258 patients screened, 133 died and were enrolled. Of these, 55.6% (74/133) were male, 69.9% (93/133) were racial/ethnic minorities, and 88.0% (117/133) had cardiovascular disease. The last cardiac rhythm recorded was VT or fibrillation in 5.3% (7/133), pulseless electrical activity in 7.5% (10/133), unspecified bradycardia in 0.8% (1/133), and asystole in 26.3% (35/133). Most 74.4% (99/133) died receiving comfort measures only. The most common abnormalities on admission electrocardiogram included abnormal QRS axis (25.8%), atrial fibrillation/flutter (14.3%), atrial ectopy (12.0%), and right bundle branch block (11.9%). During hospitalization, an additional 17.6% developed atrial ectopy, 14.7% ventricular ectopy, 10.1% atrial fibrillation/flutter, and 7.8% a right ventricular abnormality. Arrhythmic death was confirmed or suspected in 8.3% (11/133) associated with age, coronary artery disease, asthma, vasopressor use, longer admission corrected QT interval, and left bundle branch block (LBBB). CONCLUSIONS: Conduction, rhythm, and electrocardiographic abnormalities were common during COVID-19-related hospitalization. Arrhythmic death was associated with age, coronary artery disease, asthma, longer admission corrected QT interval, LBBB, ventricular ectopy, and usage of vasopressors. Most died receiving comfort measures.

Mobile Electrocardiogram Monitoring and Health-Related Quality of Life in Patients With Atrial Fibrillation: Findings From the iPhone Helping Evaluate Atrial Fibrillation Rhythm Through Technology (iHEART) Study.

BACKGROUND: Atrial fibrillation (AF) is associated with high recurrence rates and poor health-related quality of life (HRQOL) but few effective interventions to improve HRQOL exist. OBJECTIVE: The aim of this study was to examine the impact of the "iPhone Helping Evaluate Atrial Fibrillation Rhythm through Technology" (iHEART) intervention on HRQOL in patients with AF. METHODS: We randomized English- and Spanish-speaking adult patients with AF to receive either the iHEART intervention or usual care for 6 months. The iHEART intervention used smartphone-based electrocardiogram monitoring and motivational text messages. Three instruments were used to measure HRQOL: the Atrial Fibrillation Effect on Quality of Life (AFEQT), the 36-item Short-Form Health survey, and the EuroQol-5D. We used linear mixed models to compare the effect of the iHEART intervention on HRQOL, quality-adjusted life-years, and AF symptom severity. RESULTS: A total of 238 participants were randomized to the iHEART intervention (n = 115) or usual care (n = 123). Of the participants, 77% were men and 76% were white. More than half (55%) had an AF recurrence. Both arms had improved scores from baseline to follow-up for AFEQT and AF symptom severity scores. The global AFEQT score improved 18.5 and 11.2 points in the intervention and control arms, respectively (P < .05). There were no statistically significant differences in HRQOL, quality-adjusted life-years, or AF symptom severity between groups. CONCLUSIONS: We found clinically meaningful improvements in AF-specific HRQOL and AF symptom severity for both groups. Additional research with longer follow-up should examine the influence of smartphone-based interventions for AF management on HRQOL and address the unique needs of patients diagnosed with different subtypes of AF.

Cardiac electrophysiology consultative experience at the epicenter of the COVID-19 pandemic in the United States.

BACKGROUND: The COVID-19 pandemic has greatly altered the practice of cardiac electrophysiology around the world for the foreseeable future. Professional organizations have provided guidance for practitioners, but real-world examples of the consults and responsibilities cardiac electrophysiologists face during a surge of COVID-19 patients is lacking. METHODS: In this observational case series we report on 29 consecutive inpatient electrophysiology consultations at a major academic medical center in New York City, the epicenter of the pandemic in the United States, during a 2 week period from March 30-April 12, 2020, when 80% of hospital beds were occupied by COVID-19 patients, and the New York City metropolitan area accounted for 10% of COVID-19 cases worldwide. RESULTS: Reasons for consultation included: Atrial tachyarrhythmia (31%), cardiac implantable electronic device management (28%), bradycardia (14%), QTc prolongation (10%), ventricular arrhythmia (7%), post-transcatheter aortic valve replacement conduction abnormality (3.5%), ventricular pre-excitation (3.5%), and paroxysmal supraventricular tachycardia (3.5%). Twenty-four patients (86%) were positive for COVID-19 by nasopharyngeal swab. All elective procedures were canceled, and only one urgent device implantation was performed. Thirteen patients (45%) required in-person evaluation and the remainder were managed remotely. CONCLUSION: Our experience shows that the application of a massive alteration in workflow and personnel forced by the pandemic allowed our team to efficiently address the intersection of COVID-19 with a range of electrophysiology issues. This experience will prove useful as guidance for emerging hot spots or areas affected by future waves of the pandemic.

Recurrent atrial fibrillation/flutter detection after ablation or cardioversion using the AliveCor KardiaMobile device: iHEART results.

OBJECTIVE: This study evaluated the impact of daily ECG (electrocardiogram) self-recordings on time to documented recurrent atrial fibrillation (AF) or atrial flutter (AFL) and time to treatment of recurrent arrhythmia in patients undergoing catheter radiofrequency ablation (RFA) or direct current cardioversion (DCCV) for AF/AFL. BACKGROUND: AF recurrence rates after RFA and DCCV are 20% to 45% and 60% to 80%, respectively. Randomized trials comparing mobile ECG devices to standard of care have not been performed in an AF/AFL population after treatment. METHODS: Of 262 patients consented, 238 were randomized to either standard of care (123) or to receive the iHEART intervention (115). Patients in the intervention group were provided with and trained to use an AliveCor KardiaMobile ECG monitor, and were instructed to take and transmit daily ECG recordings. Data were collected from transmitted ECG recordings and patients' electronic health records. RESULTS: In a multivariate Cox model, the likelihood of recurrence detection was greater in the intervention group (hazard ratio = 1.56, 95% confidence interval [CI]: 1.06-2.30, P = .024). Hazard ratios did not differ significantly for RFA and DCCV procedures. Recurrence during the first month after ablation strongly predicted later recurrence (hazard ratio = 4.53, 95% CI: 2.05-10.00, P = .0006). Time from detection to treatment was shorter for the control group (hazard ratio = 0.33, 95% CI: 0.57-2.92, P < .0001). CONCLUSIONS: The use of mobile ECG self-recording devices allows for earlier detection of AF/AFL recurrence and may empower patients to engage in shared health decision-making.

Leadless pacemaker implantation: A feasible and reasonable option in transcatheter heart valve replacement patients.

BACKGROUND: Leadless pacemakers (LPMs) have been shown to have lower postoperative complications than traditional permanent pacemakers but there have been no studies on the outcomes of LPMs in patients with transcatheter heart valve replacements (THVRs). This study determined outcomes of LPMs compared to transvenous single-chamber pacemakers (SCPs) post-THVR. METHODS: This is a retrospective single-center study including 10 patients who received LPMs post-THVR between February 2017 and August 2018 and a comparison group of 23 patients who received SCP post-THVR between July 2008 and August 2018. LPM or SCP was implanted at the discretion of electrophysiologists for atrial fibrillation with slow ventricular response or sinus node dysfunction with need for single-chamber pacing only. RESULTS: LPMs were associated with decreased tricuspid regurgitation (P = 0.04) and decreased blood loss during implantation (7.5 ± 2.5 cc for LPMs vs 16.8 ± 3.2 cc for SCPs, P = 0.03). Five LPM patients had devices positioned in the right ventricular septum as seen on transthoracic echocardiogram. Frequency of ventricular pacing was similar between LPM and SCP groups. In the LPM group, one case was complicated by a pseudoaneurysm and one death was due to noncardiac causes. There was one pneumothorax and one pocket infection in the SCP group. CONCLUSIONS: In this small retrospective study, LPMs were feasible post-THVR and found to perform as well as SCPs, had less intraprocedural blood loss, and were associated with less tricuspid regurgitation. Further, larger studies are required to follow longer-term outcomes and complications.

Imaging the Propagation of the Electromechanical Wave in Heart Failure Patients with Cardiac Resynchronization Therapy.

BACKGROUND: Current electrocardiographic and echocardiographic measurements in heart failure (HF) do not take into account the complex interplay between electrical activation and local wall motion. The utilization of novel technologies to better characterize cardiac electromechanical behavior may lead to improved response rates with cardiac resynchronization therapy (CRT). Electromechanical wave imaging (EWI) is a noninvasive ultrasound-based technique that uses the transient deformations of the myocardium to track the intrinsic EW that precedes myocardial contraction. In this paper, we investigate the performance and reproducibility of EWI in the assessment of HF patients and CRT. METHODS: EWI acquisitions were obtained in five healthy controls and 16 HF patients with and without CRT pacing. Responders (n = 8) and nonresponders (n = 8) to CRT were identified retrospectively on the basis of left ventricular (LV) reverse remodeling. Electromechanical activation maps were obtained in all patients and used to compute a quantitative parameter describing the mean LV lateral wall activation time (LWAT). RESULTS: Mean LWAT was increased by 52.1 ms in HF patients in native rhythm compared to controls (P < 0.01). For all HF patients, CRT pacing initiated a different electromechanical activation sequence. Responders exhibited a 56.4-ms ± 28.9-ms reduction in LWAT with CRT pacing (P < 0.01), while nonresponders showed no significant change. CONCLUSION: In this initial feasibility study, EWI was capable of characterizing local cardiac electromechanical behavior as it pertains to HF and CRT response. Activation sequences obtained with EWI allow for quantification of LV lateral wall electromechanical activation, thus providing a novel method for CRT assessment.

A single-center randomized, controlled trial investigating the efficacy of a mHealth ECG technology intervention to improve the detection of atrial fibrillation: the iHEART study protocol.

BACKGROUND: Atrial fibrillation is a major public health problem and is the most common cardiac arrhythmia, affecting an estimated 2.7 million Americans. The true prevalence of atrial fibrillation is likely underestimated because episodes are often sporadic; therefore, it is challenging to detect and record an occurrence in a "real world" setting. To date, mobile health tools that promote earlier detection and treatment of atrial fibrillation and improvement in self-management behaviors and knowledge have not been evaluated. This study will be the first to address the epidemic problem of atrial fibrillation with a novel approach utilizing advancements in mobile health electrocardiogram technology to empower patients to actively engage in their healthcare and to evaluate impact on quality of life and quality-adjusted life years. Furthermore, sending a daily electrocardiogram transmission, coupled with receiving educational and motivational text messages aimed at promoting self-management and a healthy lifestyle may improve the management of chronic cardiovascular conditions (e.g., hypertension, diabetes, heart failure, etc.). Therefore, we are currently conducting a randomized controlled trial to assess the efficacy of a mobile health intervention, iPhone® Helping Evaluate Atrial fibrillation Rhythm through Technology (iHEART) versus usual cardiac care. METHODS: The iHEART study is a single center, prospective, randomized controlled trial. A total of 300 participants with a recent history of atrial fibrillation will be enrolled. Participants will be randomized 1:1 to receive the iHEART intervention, receiving an iPhone® equipped with an AliveCor® Mobile ECG and accompanying Kardia application and behavioral altering motivational text messages or usual cardiac care for 6 months. DISCUSSION: This will be the first study to investigate the utility of a mobile health intervention in a "real world" setting. We will evaluate the ability of the iHEART intervention to improve the detection and treatment of recurrent atrial fibrillation and assess the intervention's impact on improving clinical outcomes, quality of life, quality-adjusted life-years and disease-specific knowledge. TRIAL REGISTRATION: NCT02731326 ; Verified April 2016.

Atrial Tachycardias After Atrial Fibrillation Ablation Manifest Different Waveform Characteristics: Implications for Characterizing Tachycardias.

INTRODUCTION: Atrial fibrillation (AF) ablation patients often manifest atrial tachycardias (AT) with atypical ECG morphologies that preclude accurate localization and mechanism. Diagnostic maneuvers used to define ATs during electrophysiology studies can be limited by tachycardia termination or transformation. Additional methods of characterizing post-AF ablation ATs are required. METHODS AND RESULTS: We evaluated the utility of noninvasive ECG signal analytics in postablation AF patients for the following features: (1) Localization of ATs (i.e., right vs. left atrium), and (2) Identification of common left AT mechanisms (i.e., focal vs. macroreentrant). Atrial waveforms from the surface ECG were used to analyze (1) spectral organization, including dominant amplitude (DA) and mean spectral profile (MP), and (2) temporospatial variability, using temporospatial correlation coefficients. We studied 94 ATs in 71 patients who had undergone prior pulmonary vein isolation for AF and returned for a second ablation: (1) right atrial cavotricuspid-isthmus dependent (CTI) ATs (n = 21); (2) left atrial macroreentrant ATs (n = 41) and focal ATs (n = 32). Right CTI ATs manifested higher DAs and lower MPs than left ATs, indicative of greater stability and less complexity in the frequency spectrum. Left macroreentrant ATs possessed higher temporospatial organization than left focal ATs. CONCLUSIONS: Noninvasively recorded atrial waveform signal analyses show that right ATs possess more stable activation properties than left ATs, and left macroreentrant ATs manifest higher temporospatial organization than left focal ATs. Further prospective analyses evaluating the role these novel ECG-derived tools can play to help localize and identify mechanisms of common ATs in AF ablation patients are warranted.

Temporal stability in the spectral representation of complex fractionated atrial electrograms.

BACKGROUND: Although local electrograms during atrial fibrillation (AF) are often spectrally analyzed over 8-second (8s) intervals, changes may be common over intervals as short as 2s. We sought to determine whether averaged 2s measurements of electrogram spectral parameters were similar to 8s measurements, and whether the 2s intervals could provide an estimate of the temporal stability of the signal frequency content in paroxysmal versus persistent AF. METHODS: Complex fractionated atrial electrograms (CFAEs) were acquired outside the pulmonary vein ostia and from free wall sites in nine paroxysmal and 10 longstanding persistent AF patients. Using a 2s sliding calculation window, a frequency spectrum was computed every 100 ms over an interval of 8.4 seconds (82 spectra in total). The dominant frequency (DF), the dominant amplitude (DA), and the mean spectral profile (MP) were measured. The 2s measurements were compared to single 8.4-second interval measurements. Coefficients of variation (COV) were computed from the 82 spectra for each CFAE recording to determine temporal variability of parameters. RESULTS: Over the sliding 2s computation intervals, as for fixed 8.4-second computation intervals, mean DA and DF were significantly higher in longstanding persistent AF while MP was significantly higher in paroxysmal AF (P ≤ 0.001). The COV was significantly higher for the DF parameter in paroxysmal AF (P < 0.001) and significantly higher for the MP parameter in persistent AF (P < 0.02). CONCLUSIONS: For both paroxysmal and persistent AF data, the 2s sliding window averages provide similar results to single 8.4-second intervals, and information regarding temporal stability was additionally obtained in the process.

Ventricular cycle length characteristics estimative of prolonged RR interval during atrial fibrillation.

BACKGROUND: When atrial fibrillation (AF) is incessant, imaging during a prolonged ventricular RR interval may improve image quality. It was hypothesized that long RR intervals could be predicted from preceding RR values. METHODS: From the PhysioNet database, electrocardiogram RR intervals were obtained from 74 persistent AF patients. An RR interval lengthened by at least 250 ms beyond the immediately preceding RR interval (termed T0 and T1, respectively) was considered prolonged. A two-parameter scatterplot was used to predict the occurrence of a prolonged interval T0. The scatterplot parameters were: (1) RR variability (RRv) estimated as the average second derivative from 10 previous pairs of RR differences, T13-T2, and (2) Tm-T1, the difference between Tm, the mean from T13 to T2, and T1. For each patient, scatterplots were constructed using preliminary data from the first hour. The ranges of parameters 1 and 2 were adjusted to maximize the proportion of prolonged RR intervals within range. These constraints were used for prediction of prolonged RR in test data collected during the second hour. RESULTS: The mean prolonged event was 1.0 seconds in duration. Actual prolonged events were identified with a mean positive predictive value (PPV) of 80% in the test set. PPV was >80% in 36 of 74 patients. An average of 10.8 prolonged RR intervals per 60 minutes was correctly identified. CONCLUSIONS: A method was developed to predict prolonged RR intervals using two parameters and prior statistical sampling for each patient. This or similar methodology may help improve cardiac imaging in many longstanding persistent AF patients.

Software algorithm and hardware design for real-time implementation of new spectral estimator.

BACKGROUND: Real-time spectral analyzers can be difficult to implement for PC computer-based systems because of the potential for high computational cost, and algorithm complexity. In this work a new spectral estimator (NSE) is developed for real-time analysis, and compared with the discrete Fourier transform (DFT). METHOD: Clinical data in the form of 216 fractionated atrial electrogram sequences were used as inputs. The sample rate for acquisition was 977 Hz, or approximately 1 millisecond between digital samples. Real-time NSE power spectra were generated for 16,384 consecutive data points. The same data sequences were used for spectral calculation using a radix-2 implementation of the DFT. The NSE algorithm was also developed for implementation as a real-time spectral analyzer electronic circuit board. RESULTS: The average interval for a single real-time spectral calculation in software was 3.29 µs for NSE versus 504.5 µs for DFT. Thus for real-time spectral analysis, the NSE algorithm is approximately 150× faster than the DFT. Over a 1 millisecond sampling period, the NSE algorithm had the capability to spectrally analyze a maximum of 303 data channels, while the DFT algorithm could only analyze a single channel. Moreover, for the 8 second sequences, the NSE spectral resolution in the 3-12 Hz range was 0.037 Hz while the DFT spectral resolution was only 0.122 Hz. The NSE was also found to be implementable as a standalone spectral analyzer board using approximately 26 integrated circuits at a cost of approximately $500. The software files used for analysis are included as a supplement, please see the Additional files 1 and 2. CONCLUSIONS: The NSE real-time algorithm has low computational cost and complexity, and is implementable in both software and hardware for 1 millisecond updates of multichannel spectra. The algorithm may be helpful to guide radiofrequency catheter ablation in real time.

Esophageal injury, perforation, and fistula formation following atrial fibrillation ablation.

BACKGROUND: Esophageal perforation and fistula formation are rare but serious complications following atrial fibrillation ablation. In this review article, we outline the incidence, pathophysiology, predictors, and preventative strategies of this dreaded complication. METHODS: We conducted an electronic search in 10 databases/electronic search engines to access relevant publications. All articles reporting complications following atrial fibrillation ablation, including esophageal injury and fistula formation, were included for systematic review. RESULTS: A total of 130 manuscripts were identified for the final review process. The overall incidence of esophageal injury following atrial fibrillation ablation was significantly higher with thermal ablation modalities (radiofrequency 5-40%, cryoballoon 3-25%, high-intensity focused ultrasound < 10%) as opposed to non-thermal ablation modalities (no cases reported to date). The incidence of esophageal perforation and fistula formation with the use of thermal ablation modalities is estimated to occur in less than 0.25% of all atrial fibrillation ablation procedures. The use of luminal esophageal temperature monitoring probe and mechanical esophageal deviation showed protective effect toward reducing the incidence of this complication. The prognosis is very poor for patients who develop atrioesophageal fistula, and the condition is rapidly fatal without surgical intervention. CONCLUSIONS: Esophageal perforation and fistula formation following atrial fibrillation ablation are rare complications with poor prognosis. Various strategies have been proposed to protect the esophagus and reduce the incidence of this fearful complication. Pulsed field ablation is a promising new ablation technology that may be the future answer toward reducing the incidence of esophageal complications.

Wavefront curvature analysis derived from preprocedural imaging can identify the critical isthmus in patients with postinfarcted ventricular tachycardia.

BACKGROUND: Where activation wavefront curvature is convexly shaped, functional conduction block can occur. OBJECTIVE: The purpose of this study was to determine whether left ventricular (LV) wall thickness determined from contrast-enhanced computed tomography (CT) is useful in localizing such areas in clinical postinfarction reentrant ventricular tachycardia (VT). METHODS: We evaluated data from 6 patients who underwent catheter ablation for postinfarction VT. CT imaging with inHEART processing was conducted 1-3 days before electrophysiological (EP) study to determine LV wall thickness (T). Activation wavefront curvature was approximated as ΔT/T, where ΔT represents wall thickness change. During EP study, bipolar LV VT electrograms were acquired using a high-density mapping catheter, and activation times were determined. Maps of T, ΔT/T, and VT activation were subsequently compared using statistical analyses. RESULTS: Two of 6 cases exhibited dual circuit morphologies, resulting in a total of 8 VT morphologies analyzed. The LV wall near the VT isthmus location tended to be thin, on the order of a few hundred micrometers. Regions of largest ΔT/T partially coincided with the lateral isthmus boundaries where electrical conduction block occurred during VT. ΔT/T at the boundaries, measured from imaging, was significantly larger compared to values at the isthmus midline and to the global LV mean value (P <.001). CONCLUSION: Wavefront curvature measured by ΔT/T and caused by source-sink mismatch is dependent on ventricular wall thickness. Areas of high wavefront curvature partly coincide with and may be helpful in locating the VT isthmus in infarct border zones using preprocedural imaging analysis.

Predictors of Transthoracic Impedance in Patients Who Underwent Elective Electrical Cardioversion.

Successful synchronized direct current cardioversion (DCCV) requires adequate current delivery to the heart. However, adequate current for successful DCCV has not yet been established. Transmyocardial current depends on 2 factors: input energy and transthoracic impedance (TTI). Although factors affecting TTI have been studied in animal models, factors affecting TTI in humans have not been well established. Herein, we explored the potential factors that affect TTI in humans. A retrospective review of patients who underwent DCCV at a large quaternary medical center between October 2019 and August 2021 was conducted. Pertinent clinical information, including demographics, echocardiography findings, laboratory findings, and body characteristics, was collected. Cardioversion details, including joules delivered and TTI, were recorded by the defibrillator for each patient's first shock. Predictors of thoracic impedance were assessed using regression analysis. A total of 220 patients (29% women) were included in the analysis; 143 of the patients (65%) underwent DCCV for atrial fibrillation and 77 (35%) underwent DCCV for atrial flutter. The mean impedance in our population was 73 ± 18 Ω. In a regression model with high impedance defined as the upper quartile of our cohort, body mass index (BMI), female sex, obstructive sleep apnea, and chronic kidney disease (all p values <0.05) were significantly associated with high impedance. According to a receiver operating characteristic analysis, BMI has a high predictive value for high impedance, with an area under the curve of 0.76. In conclusion, our study reveals that elevated BMI, female sex, sleep apnea, and chronic kidney disease were predictors of higher TTI. These factors may help determine the appropriate initial shock energy in patients who underwent DCCV for atrial fibrillation and flutter.