40 results found
Ali N, Arnold AD, Miyazawa AA, et al., 2023, Septal scar as a barrier to left bundle branch area pacing., Pacing Clin Electrophysiol, Vol: 46, Pages: 1077-1084
BACKGROUND: The use of left bundle branch area pacing (LBBAP) for bradycardia pacing and cardiac resynchronization is increasing, but implants are not always successful. We prospectively studied consecutive patients to determine whether septal scar contributes to implant failure. METHODS: Patients scheduled for bradycardia pacing or cardiac resynchronization therapy were prospectively enrolled. Recruited patients underwent preprocedural scar assessment by cardiac MRI with late gadolinium enhancement imaging. LBBAP was attempted using a lumenless lead (Medtronic 3830) via a transeptal approach. RESULTS: Thirty-five patients were recruited: 29 male, mean age 68 years, 10 ischemic, and 16 non-ischemic cardiomyopathy. Pacing indication was bradycardia in 26% and cardiac resynchronization in 74%. The lead was successfully deployed to the left ventricular septum in 30/35 (86%) and unsuccessful in the remaining 5/35 (14%). Septal late gadolinium enhancement was significantly less extensive in patients where left septal lead deployment was successful, compared those where it was unsuccessful (median 8%, IQR 2%-18% vs. median 54%, IQR 53%-57%, p < .001). CONCLUSIONS: The presence of septal scar appears to make it more challenging to deploy a lead to the left ventricular septum via the transeptal route. Additional implant tools or alternative approaches may be required in patients with extensive septal scar.
Sau A, 2023, Artificial intelligence-enabled electrocardiogram to distinguish atrioventricular re-entrant tachycardia from atrioventricular nodal re-entrant tachycardia, Cardiovascular Digital Health Journal, Vol: 4, Pages: 60-67, ISSN: 2666-6936
BackgroundAccurately determining arrhythmia mechanism from a 12-lead electrocardiogram (ECG) of supraventricular tachycardia can be challenging. We hypothesized a convolutional neural network (CNN) can be trained to classify atrioventricular re-entrant tachycardia (AVRT) vs atrioventricular nodal re-entrant tachycardia (AVNRT) from the 12-lead ECG, when using findings from the invasive electrophysiology (EP) study as the gold standard.MethodsWe trained a CNN on data from 124 patients undergoing EP studies with a final diagnosis of AVRT or AVNRT. A total of 4962 5-second 12-lead ECG segments were used for training. Each case was labeled AVRT or AVNRT based on the findings of the EP study. The model performance was evaluated against a hold-out test set of 31 patients and compared to an existing manual algorithm.ResultsThe model had an accuracy of 77.4% in distinguishing between AVRT and AVNRT. The area under the receiver operating characteristic curve was 0.80. In comparison, the existing manual algorithm achieved an accuracy of 67.7% on the same test set. Saliency mapping demonstrated the network used the expected sections of the ECGs for diagnoses; these were the QRS complexes that may contain retrograde P waves.ConclusionWe describe the first neural network trained to differentiate AVRT from AVNRT. Accurate diagnosis of arrhythmia mechanism from a 12-lead ECG could aid preprocedural counseling, consent, and procedure planning. The current accuracy from our neural network is modest but may be improved with a larger training dataset.
Keene D, Anselme F, Burri H, et al., 2023, Conduction system pacing, a European survey: insights from clinical practice, EUROPACE, ISSN: 1099-5129
Coyle C, Koutsoftidis S, Kim M-Y, et al., 2023, Feasibility of mapping and ablating ectopy-triggering ganglionated plexus reproducibly in persistent atrial fibrillation, Journal of Interventional Cardiac Electrophysiology: an international journal of arrhythmias and pacing, ISSN: 1383-875X
BackgroundAblation of autonomic ectopy-triggering ganglionated plexuses (ET-GP) has been used to treat paroxysmal atrial fibrillation (AF). It is not known if ET-GP localisation is reproducible between different stimulators or whether ET-GP can be mapped and ablated in persistent AF. We tested the reproducibility of the left atrial ET-GP location using different high-frequency high-output stimulators in AF. In addition, we tested the feasibility of identifying ET-GP locations in persistent atrial fibrillation.MethodsNine patients undergoing clinically-indicated paroxysmal AF ablation received pacing-synchronised high-frequency stimulation (HFS), delivered in SR during the left atrial refractory period, to compare ET-GP localisation between a custom-built current-controlled stimulator (Tau20) and a voltage-controlled stimulator (Grass S88, SIU5). Two patients with persistent AF underwent cardioversion, left atrial ET-GP mapping with the Tau20 and ablation (Precision™, Tacticath™ [n = 1] or Carto™, SmartTouch™ [n = 1]). Pulmonary vein isolation (PVI) was not performed. Efficacy of ablation at ET-GP sites alone without PVI was assessed at 1 year.ResultsThe mean output to identify ET-GP was 34 mA (n = 5). Reproducibility of response to synchronised HFS was 100% (Tau20 vs Grass S88; [n = 16] [kappa = 1, SE = 0.00, 95% CI 1 to 1)][Tau20 v Tau20; [n = 13] [kappa = 1, SE = 0, 95% CI 1 to 1]). Two patients with persistent AF had 10 and 7 ET-GP sites identified requiring 6 and 3 min of radiofrequency ablation respectively to abolish ET-GP response. Both patients were free from AF for > 365 days without anti-arrhythmics.ConclusionsET-GP sites are identified at the same location by different stimulators. ET-GP ablation alone was able to prevent AF recurrence in persistent AF, and further studies would be warranted
Ali N, Arnold AD, Miyazawa AA, et al., 2023, Comparison of methods for delivering cardiac resynchronization therapy: an acute electrical and haemodynamic within-patient comparison of left bundle branch area, His bundle, and biventricular pacing, EP Europace, Vol: 25, Pages: 1060-1067, ISSN: 1099-5129
AimsLeft bundle branch area pacing (LBBAP) is a promising method for delivering cardiac resynchronization therapy (CRT), but its relative physiological effectiveness compared with His bundle pacing (HBP) is unknown. We conducted a within-patient comparison of HBP, LBBAP, and biventricular pacing (BVP).Methods and resultsPatients referred for CRT were recruited. We assessed electrical response using non-invasive mapping, and acute haemodynamic response using a high-precision haemodynamic protocol. Nineteen patients were recruited: 14 male, mean LVEF of 30%. Twelve had time for BVP measurements. All three modalities reduced total ventricular activation time (TVAT), (ΔTVATHBP -43 ± 14 ms and ΔTVATLBBAP −35 ± 20 ms vs. ΔTVATBVP −19 ± 30 ms, P = 0.03 and P = 0.1, respectively). HBP produced a significantly greater reduction in TVAT compared with LBBAP in all 19 patients (−46 ± 15 ms, −36 ± 17 ms, P = 0.03). His bundle pacing and LBBAP reduced left ventricular activation time (LVAT) more than BVP (ΔLVATHBP −43 ± 16 ms, P < 0.01 vs. BVP, ΔLVATLBBAP −45 ± 17 ms, P < 0.01 vs. BVP, ΔLVATBVP −13 ± 36 ms), with no difference between HBP and LBBAP (P = 0.65). Acute systolic blood pressure was increased by all three modalities. In the 12 with BVP, greater improvement was seen with HBP and LBBAP (6.4 ± 3.8 mmHg BVP, 8.1 ± 3.8 mmHg HBP, P = 0.02 vs. BVP and 8.4 ± 8.2 mmHg for LBBAP, P = 0.3 vs. BVP), with no difference between HBP and LBBAP (P = 0.8).ConclusionHBP delivered better ventricular resynchronization than LBBAP because right ventricular activation was slower during LBBAP. But LBBAP was not inferior to HBP with respect to LV electrical resynchronization and acute haemodynamic response.
Whinnett ZI, Shun-Shin MJ, Tanner M, et al., 2023, Effects of haemodynamically atrio-ventricular optimized His bundle pacing on heart failure symptoms and exercise capacity: the His Optimized Pacing Evaluated for Heart Failure (HOPE-HF) randomized, double-blind, cross-over trial, EUROPEAN JOURNAL OF HEART FAILURE, Vol: 25, Pages: 274-283, ISSN: 1388-9842
Pharithi RB, Ayeni M, Makharia M, et al., 2023, Optimizing conduction system pacing lead placement utilizing the image overlay technique, PACE - Pacing and Clinical Electrophysiology, ISSN: 0147-8389
The His-bundle has several locations from which conduction system pacing can be achieved. Some locations offer better sensing, thresholds and paced QRS durations. Existing techniques to aid repositioning of an already deployed, but sub-optimally placed lead, include either simple memory of the initial lead position combined with its observation on an x-ray review screen or utilizing an additional vascular access and pacing lead with the first lead serving as a real-time marker (Two-lead technique). We describe a novel, readily available, cost-efficient, imaging-based approach to assist in the re-positioning of a pacing lead for His-bundle pacing (the Image Overlay Technique).
Arnold AD, Shun-Shin MJ, Ali N, et al., 2023, Contributions of Atrioventricular Delay Shortening and Ventricular Resynchronization to Hemodynamic Benefits of Biventricular Pacing., JACC Clin Electrophysiol, Vol: 9, Pages: 117-119
Kaza N, Htun V, Miyazawa A, et al., 2022, Upgrading right ventricular pacemakers to biventricular pacing or conduction system pacing: a systematic review and meta-analysis, EUROPACE, ISSN: 1099-5129
Simader FA, Howard JP, Ahmad Y, et al., 2022, Catheter ablation improves cardiovascular outcomes in patients with atrial fibrillation and heart failure: a meta-analysis of randomized controlled trials, EUROPACE, ISSN: 1099-5129
Sau A, Ibrahim S, Ahmed A, et al., 2022, Artificial intelligence-enabled electrocardiogram to distinguish cavotricuspid isthmus dependence from other atrial tachycardia mechanisms, European Heart Journal – Digital Health, Vol: 3, Pages: 405-414, ISSN: 2634-3916
Aims:Accurately determining atrial arrhythmia mechanisms from a 12-lead electrocardiogram (ECG) can be challenging. Given the high success rate of cavotricuspid isthmus (CTI) ablation, identification of CTI-dependent typical atrial flutter (AFL) is important for treatment decisions and procedure planning. We sought to train a convolutional neural network (CNN) to classify CTI-dependent AFL vs. non-CTI dependent atrial tachycardia (AT), using data from the invasive electrophysiology (EP) study as the gold standard.Methods and results:We trained a CNN on data from 231 patients undergoing EP studies for atrial tachyarrhythmia. A total of 13 500 five-second 12-lead ECG segments were used for training. Each case was labelled CTI-dependent AFL or non-CTI-dependent AT based on the findings of the EP study. The model performance was evaluated against a test set of 57 patients. A survey of electrophysiologists in Europe was undertaken on the same 57 ECGs. The model had an accuracy of 86% (95% CI 0.77–0.95) compared to median expert electrophysiologist accuracy of 79% (range 70–84%). In the two thirds of test set cases (38/57) where both the model and electrophysiologist consensus were in agreement, the prediction accuracy was 100%. Saliency mapping demonstrated atrial activation was the most important segment of the ECG for determining model output.Conclusion:We describe the first CNN trained to differentiate CTI-dependent AFL from other AT using the ECG. Our model matched and complemented expert electrophysiologist performance. Automated artificial intelligence-enhanced ECG analysis could help guide treatment decisions and plan ablation procedures for patients with organized atrial arrhythmias.
Kaza N, Keene D, Whinnett ZI, 2022, Generating Evidence to Support the Physiologic Promise of Conduction System Pacing: Status and Update on Conduction System Pacing Trials., Card Electrophysiol Clin, Vol: 14, Pages: 345-355
Conduction system pacing avoids the potential deleterious effects of right ventricular pacing in patients with bradycardia and provides an alternative approach to cardiac resynchronization therapy. We focus on the available observational and randomized evidence and review studies supporting the safety, feasibility, and physiologic promise of conduction system approaches. We evaluate the randomized data generated from the available clinical trials of conduction system pacing, which have led to the recent inclusion of CSP in international guidelines. The scope for future randomized trials will building on the physiologic promise of conduction system approaches and offering information on clinical end points is explored.
Keene D, Miyazawa AA, Johal M, et al., 2022, Optimizing atrio-ventricular delay in pacemakers using potentially implantable physiological biomarkers, Pacing and Clinical Electrophysiology, Vol: 45, Pages: 461-470, ISSN: 0147-8389
BackgroundHemodynamically optimal atrioventricular (AV) delay can be derived by echocardiography or beat-by-beat blood pressure (BP) measurements, but analysis is labor intensive. Laser Doppler perfusion monitoring measures blood flow and can be incorporated into future implantable cardiac devices.We assess whether laser Doppler can be used instead of BP to optimize AV delay.MethodsFifty eight patients underwent 94 AV delay optimizations with biventricular or His-bundle pacing using laser Doppler and simultaneous noninvasive beat-by-beat BP. Optimal AV delay was defined using a curve of hemodynamic response to switching from AAI (reference state) to DDD (test state) at several AV delays (40–320 ms), with automatic quality control checking precision of the optimum.Five subsequent patients underwent an extended protocol to test the impact of greater numbers of alternations on optimization quality.Results55/94 optimizations passed quality control resulting in an optimal AV delay on laser Doppler similar to that derived by BP (median absolute deviation 12 ms).An extended protocol with increasing number of replicates consistently improved quality and reduced disagreement between laser Doppler and BP optima. With only five replicates, no optimization passed quality control, and the median absolute deviation would be 29 ms. These improved progressively until at 50 replicates, all optimizations passed quality control and the median absolute deviation was only 13 ms.ConclusionsLaser Doppler perfusion produces hemodynamic optima equivalent to BP. Quality control can be automatic. Adding more replicates, consistently improves quality. Future implantable devices could use such methods to dynamically and reliably optimize AV delays.
Ahmad Y, Kane C, Arnold AD, et al., 2022, Randomized blinded placebo-controlled trials of renal sympathetic denervation for hypertension: a meta-analysis, Cardiovascular Revascularization Medicine, Vol: 34, Pages: 112-118, ISSN: 1553-8389
BackgroundThe efficacy of renal denervation has been controversial, but the procedure has now undergone several placebo-controlled trials. New placebo-controlled trial data has recently emerged, with longer follow-up of one trial and the full report of another trial (which constitutes 27% of the total placebo-controlled trial data). We therefore sought to evaluate the effect of renal denervation on ambulatory and office blood pressures in patients with hypertension.MethodsWe systematically identified all blinded placebo-controlled randomized trials of catheter-based renal denervation for hypertension. The primary efficacy outcome was ambulatory systolic blood pressure change relative to placebo. A random-effects meta-analysis was performed.Results6 studies randomizing 1232 patients were eligible. 713 patients were randomized to renal denervation and 519 to placebo. Renal denervation significantly reduced ambulatory systolic blood pressure (−3.52 mmHg; 95% CI −4.94 to −2.09; p < 0.0001), ambulatory diastolic blood pressure (−1.93 mmHg; 95% CI −3.04 to −0.83, p = 0.0006), office systolic blood pressure size (−5.10 mmHg; 95% CI −7.31 to −2.90, p < 0.0001) and office diastolic pressure (effect size −3.11 mmHg; 95% CI −4.43 to −1.78, p < 0.0001). Adverse events were rare and not more common with denervation.ConclusionsThe totality of blinded, randomized placebo-controlled data shows that renal denervation is safe and provides genuine reduction in blood pressure for at least 6 months post-procedure. If this effect continues in the long term, renal denervation might provide a life-long 10% relative risk reduction in major adverse cardiac events and 7.5% relative risk reduction in all-cause mortality.
Bachtiger P, Petri CF, Scott FE, et al., 2022, Point-of-care screening for heart failure with reduced ejection fraction using artificial intelligence during ECG-enabled stethoscope examination in London, UK: a prospective, observational, multicentre study, The Lancet Digital Health, Vol: 4, ISSN: 2589-7500
BACKGROUND: Most patients who have heart failure with a reduced ejection fraction, when left ventricular ejection fraction (LVEF) is 40% or lower, are diagnosed in hospital. This is despite previous presentations to primary care with symptoms. We aimed to test an artificial intelligence (AI) algorithm applied to a single-lead ECG, recorded during ECG-enabled stethoscope examination, to validate a potential point-of-care screening tool for LVEF of 40% or lower. METHODS: We conducted an observational, prospective, multicentre study of a convolutional neural network (known as AI-ECG) that was previously validated for the detection of reduced LVEF using 12-lead ECG as input. We used AI-ECG retrained to interpret single-lead ECG input alone. Patients (aged ≥18 years) attending for transthoracic echocardiogram in London (UK) were recruited. All participants had 15 s of supine, single-lead ECG recorded at the four standard anatomical positions for cardiac auscultation, plus one handheld position, using an ECG-enabled stethoscope. Transthoracic echocardiogram-derived percentage LVEF was used as ground truth. The primary outcome was performance of AI-ECG at classifying reduced LVEF (LVEF ≤40%), measured using metrics including the area under the receiver operating characteristic curve (AUROC), sensitivity, and specificity, with two-sided 95% CIs. The primary outcome was reported for each position individually and with an optimal combination of AI-ECG outputs (interval range 0-1) from two positions using a rule-based approach and several classification models. This study is registered with ClinicalTrials.gov, NCT04601415. FINDINGS: Between Feb 6 and May 27, 2021, we recruited 1050 patients (mean age 62 years [SD 17·4], 535 [51%] male, 432 [41%] non-White). 945 (90%) had an ejection fraction of at least 40%, and 105 (10%) had an ejection fraction of 40% or lower. Across all positions, ECGs were most frequently of adequate quality for AI-ECG interpretation at the p
Keene D, Whinnett Z, 2021, Advances in cardiac resynchronisation therapy: review of indications and delivery options, HEART, Vol: 108, Pages: 889-897, ISSN: 1355-6037
Arnold AD, Shun-Shin MJ, Ali N, et al., 2021, Left ventricular activation time and pattern are preserved with both selective and non-selective his bundle pacing, Heart Rhythm O2, Vol: 2, Pages: 439-445, ISSN: 2666-5018
BackgroundHis bundle pacing (HBP) can be achieved in two ways: selective HBP (S-HBP), where the His bundle is captured alone, and non-selective HBP (NS-HBP), where local myocardium is also captured resulting a pre-excited ECG appearance.ObjectiveWe assessed the impact of this ventricular pre-excitation on left and right ventricular dys-synchrony.MethodsWe recruited patients who displayed both S-HBP and NS-HBP. We performed non-invasive epicardial electrical mapping for left and right ventricular activation time (LVAT and RVAT) and pattern.Results20 patients were recruited. In the primary analysis, the mean within-patient change in LVAT from S-HBP to NS-HBP was -5.5ms (95% confidence interval: -0.6 to -10.4, non-inferiority p<0.0001). NS-HBP did not prolong RVAT (4.3ms, -4.0 to 12.8, p=0.296) but did prolong QRS duration (QRSd, 22.1ms, 11.8 to 32.4, p = 0.0003). In patients with narrow intrinsic QRS (n=6), NS-HBP preserved LVAT (-2.9ms, -9.7 to 4.0, p=0.331) but prolonged QRS duration (31.4ms, 22.0 to 40.7, p=0.0003) and mean RVAT (16.8ms, -5.3 to 38.9, p=0.108) compared to S-HBP. Activation pattern of the left ventricular surface was unchanged between S-HBP and NS-HBP but NS-HBP produced early basal right ventricular activation that was not seen in S-HBP.ConclusionCompared to S-HBP, local myocardial capture during NS-HBP produces pre-excitation of the basal right ventricle resulting in QRS duration prolongation. However, NS-HBP preserves the left ventricular activation time and pattern of S-HBP. Left ventricular dys-synchrony is not an important factor when choosing between S-HBP and NS-HBP in most patients.
Arnold AD, Shun-Shin MJ, Keene D, et al., 2021, Electrocardiographic predictors of successful resynchronization of left bundle branch block by his bundle pacing, Journal of Cardiovascular Electrophysiology, Vol: 32, Pages: 428-438, ISSN: 1045-3873
BackgroundHis bundle pacing (HBP) is an alternative to biventricular pacing (BVP) for delivering cardiac resynchronization therapy (CRT) in patients with heart failure and left bundle branch block (LBBB). It is not known whether ventricular activation times and patterns achieved by HBP are equivalent to intact conduction systems and not all patients with LBBB are resynchronized by HBP.ObjectiveTo compare activation times and patterns of His-CRT with BVP-CRT, LBBB and intact conduction systems.MethodsIn patients with LBBB, noninvasive epicardial mapping (ECG imaging) was performed during BVP and temporary HBP. Intrinsic activation was mapped in all subjects. Left ventricular activation times (LVAT) were measured and epicardial propagation mapping (EPM) was performed, to visualize epicardial wavefronts. Normal activation pattern and a normal LVAT range were determined from normal subjects.ResultsForty-five patients were included, 24 with LBBB and LV impairment, and 21 with normal 12-lead ECG and LV function. In 87.5% of patients with LBBB, His-CRT successfully shortened LVAT by ≥10 ms. In 33.3%, His-CRT resulted in complete ventricular resynchronization, with activation times and patterns indistinguishable from normal subjects. EPM identified propagation discontinuity artifacts in 83% of patients with LBBB. This was the best predictor of whether successful resynchronization was achieved by HBP (logarithmic odds ratio, 2.19; 95% confidence interval, 0.07–4.31; p = .04).ConclusionNoninvasive electrocardiographic mapping appears to identify patients whose LBBB can be resynchronized by HBP. In contrast to BVP, His-CRT may deliver the maximum potential ventricular resynchronization, returning activation times, and patterns to those seen in normal hearts.
Keene D, Shun-Shin MJ, Arnold AD, et al., 2020, Within-patient comparison of His-bundle pacing, right ventricular pacing, and right ventricular pacing avoidance algorithms in patients with PR prolongation: Acute hemodynamic study, Journal of Cardiovascular Electrophysiology, Vol: 31, Pages: 2964-2974, ISSN: 1045-3873
AimsA prolonged PR interval may adversely affect ventricular filling and, therefore, cardiac function. AV delay can be corrected using right ventricular pacing (RVP), but this induces ventricular dyssynchrony, itself harmful. Therefore, in intermittent heart block, pacing avoidance algorithms are often implemented. We tested His‐bundle pacing (HBP) as an alternative.MethodsOutpatients with a long PR interval (>200 ms) and intermittent need for ventricular pacing were recruited. We measured within‐patient differences in high‐precision hemodynamics between AV‐optimized RVP and HBP, as well as a pacing avoidance algorithm (Managed Ventricular Pacing [MVP]).ResultsWe recruited 18 patients. Mean left ventricular ejection fraction was 44.3 ± 9%. Mean intrinsic PR interval was 266 ± 42 ms and QRS duration was 123 ± 29 ms. RVP lengthened QRS duration (+54 ms, 95% CI 42–67 ms, p < .0001) while HBP delivered a shorter QRS duration than RVP (−56 ms, 95% CI −67 to −46 ms, p < .0001). HBP did not increase QRS duration (−2 ms, 95% CI −8 to 13 ms, p = .6). HBP improved acute systolic blood pressure by mean of 5.0 mmHg (95% CI 2.8–7.1 mmHg, p < .0001) compared to RVP and by 3.5 mmHg (95% CI 1.9–5.0 mmHg, p = .0002) compared to the pacing avoidance algorithm. There was no significant difference in hemodynamics between RVP and ventricular pacing avoidance (p = .055).ConclusionsHBP provides better acute cardiac function than pacing avoidance algorithms and RVP, in patients with prolonged PR intervals. HBP allows normalization of prolonged AV delays (unlike pacing avoidance) and does not cause ventricular dyssynchrony (unlike RVP). Clinical trials may be justified to assess whether these acute
Arnold AD, Howard JP, Gopi AA, et al., 2020, Discriminating electrocardiographic responses to His-bundle pacing using machine learning., Cardiovascular Digital Health Journal, Vol: 1, Pages: 11-20
Background: His-bundle pacing (HBP) has emerged as an alternative to conventional ventricular pacing because of its ability to deliver physiological ventricular activation. Pacing at the His bundle produces different electrocardiographic (ECG) responses: selective His-bundle pacing (S-HBP), non-selective His bundle pacing (NS-HBP), and myocardium-only capture (MOC). These 3 capture types must be distinguished from each other, which can be challenging and time-consuming even for experts. Objective: The purpose of this study was to use artificial intelligence (AI) in the form of supervised machine learning using a convolutional neural network (CNN) to automate HBP ECG interpretation. Methods: We identified patients who had undergone HBP and extracted raw 12-lead ECG data during S-HBP, NS-HBP, and MOC. A CNN was trained, using 3-fold cross-validation, on 75% of the segmented QRS complexes labeled with their capture type. The remaining 25% was kept aside as a testing dataset. Results: The CNN was trained with 1297 QRS complexes from 59 patients. Cohen kappa for the neural network's performance on the 17-patient testing set was 0.59 (95% confidence interval 0.30 to 0.88; P <.0001), with an overall accuracy of 75%. The CNN's accuracy in the 17-patient testing set was 67% for S-HBP, 71% for NS-HBP, and 84% for MOC. Conclusion: We demonstrated proof of concept that a neural network can be trained to automate discrimination between HBP ECG responses. When a larger dataset is trained to higher accuracy, automated AI ECG analysis could facilitate HBP implantation and follow-up and prevent complications resulting from incorrect HBP ECG analysis.
Bohm M, Kario K, Kandzari DE, et al., 2020, Efficacy of catheter-based renal denervation in the absence of antihypertensive medications (SPYRAL HTN-OFF MED Pivotal): a multicentre, randomised, sham-controlled trial, LANCET, Vol: 395, Pages: 1444-1451, ISSN: 0140-6736
Pucci N, Kwan CH, Yates DC, et al., 2020, Effect of fields generated through wireless power transfer on implantable biomedical devices, 2019 IEEE PELS Workshop on Emerging Technologies: Wireless Power Transfer (WoW), Publisher: IEEE, Pages: 1-5
This paper assesses the safety of pacemakers when exposed to the electromagnetic (EM) field generated by high frequency inductive power transfer (HF-IPT) systems. It includes both simulation and experimental results, showing temperature variations to ensure conformity with the EN standards, changes in detected lead impedance and determining whether EM field strength can affect the operating mode of the device. This is the first time the interaction between 6.78MHz, 100W HF-IPT systems and pacemaker devices was tested up to distances of 5 cm to 10 cm, Temporary decrease of detected lead's impedance and interruption of communications are the most relevant effects recorded through in-vitro tests. No permanent alteration of the device's operation was recorded, indicating good early stage evidence of safety for pacemaker users in proximity of this new emerging technology.
Keene D, Sohaib SMA, Wong T, 2020, Cardiac Pacing in Adults, Cardiac Surgery: A Complete Guide, Pages: 81-92, ISBN: 9783030241735
The heart is served by intrinsic, efficient and coordinated electrical activation provided by its specialised conduction system. The conduction system can be damaged, requiring the provision of pacing to maintain an adequate cardiac output. Causes of cardiac conduction disease are most commonly idiopathic or degenerative relating to calcium deposition. Pacing is not uncommonly indicated after cardiac surgery, particularly following procedures on the aortic valve especially in the presence of underlying conduction disease. The disturbance and damage caused to the conduction system may be short lived and resolve whilst back-up pacing support is provided by a temporary pacing system or more permanent damage may result requiring a permanent pacing solution. Managing a temporary pacing system and determining if and when to convert to a permanent pacing approach can at times be difficult. This chapter provides an overview of standard indications for pacemakers and implantable defibrillators as well as clarifies basic principles of pacing including commonly used terms such as threshold and sensitivity. It explores new developments in the sphere of cardiac pacing such as pacemakers in an MRI field as well as emerging technologies namely leadless and His bundle pacing. It includes a practical section on troubleshooting of temporary epicardial systems and provides insight into cases where cardiac surgeons may be called upon to assist cardiology colleagues, namely, surgical lead implantation or lead extraction.
Arnold A, Howard J, Chiew K, et al., 2019, Right ventricular pacing for hypertrophic obstructive cardiomyopathy: meta-analysis and meta-regression of clinical trials, European Heart Journal - Quality of Care and Clinical Outcomes, Vol: 5, Pages: 321-333, ISSN: 2058-5225
AimsRight ventricular pacing for left ventricular outflow tract gradient reduction in hypertrophic obstructive cardiomyopathy remains controversial. We undertook a meta-analysis for echocardiographic and functional outcomes.Methods and resultsThirty-four studies comprising 1135 patients met eligibility criteria. In the four blinded randomized controlled trials (RCTs), pacing reduced gradient by 35% [95% confidence interval (CI) 23.2–46.9, P < 0.0001], but there was only a trend towards improved New York Heart Association (NYHA) class [odds ratio (OR) 1.82, CI 0.96–3.44; P = 0.066]. The unblinded observational studies reported a 54.3% (CI 44.1–64.6, P < 0.0001) reduction in gradient, which was a 18.6% greater reduction than the RCTs (P = 0.0351 for difference between study designs). Observational studies reported an effect on unblinded NYHA class at an OR of 8.39 (CI 4.39–16.04, P < 0.0001), 450% larger than the OR in RCTs (P = 0.0042 for difference between study designs). Across all studies, the gradient progressively decreased at longer follow durations, by 5.2% per month (CI 2.5–7.9, P = 0.0001).ConclusionRight ventricular pacing reduces gradient in blinded RCTs. There is a non-significant trend to reduction in NYHA class. The bias in assessment of NYHA class in observational studies appears to be more than twice as large as any genuine treatment effect.
Keene D, Arnold A, Jastrzębski M, et al., 2019, His bundle pacing, learning curve, procedure characteristics, safety, and feasibility: Insights from a large international observational study, Journal of Cardiovascular Electrophysiology, Vol: 30, Pages: 1984-1993, ISSN: 1045-3873
BackgroundHis‐bundle pacing (HBP) provides physiological ventricular activation. Observational studies have demonstrated the techniques feasibility however, data has come from a limited number of centres.ObjectivesWe set out to explore contemporary global practise in HBP focusing on learning curve, procedural characteristics and outcomes.MethodsThis is a retrospective, multi‐centre observational study of patients undergoing attempted HBP at seven centres. Pacing indication, fluoroscopy time, HBP thresholds and lead re‐intervention and deactivation rates were recorded. Where centres had systematically recorded implant success rates from the outset, these were collated.Results529 patients underwent attempted HBP during the study period (2014‐19) with mean follow‐up of 217±303 days. Most implants were for bradycardia indications.In the three centres with systematic collation of all attempts, overall implant success rate was 81% which improved to 87% after completion of 40 cases.All seven centres reported data on successful implants. Mean fluoroscopy time was 11.7±12.0 minutes, His‐bundle capture threshold at implant was 1.4±0.9V at 0.8±0.3 ms and was 1.3±1.2V at 0.9±0.2ms at last device check.HBP lead re‐intervention or deactivation (for lead displacement or rise in threshold) occurred in 7.5% of successful implants.There was evidence of a learning curve: fluoroscopy time and HBP capture threshold reduced with greater experience, plateauing after ~30‐50 cases.ConclusionWe found that it is feasible to establish a successful HBP program, using the currently available implantation tools. For physicians who are experienced at pacemaker implantation the steepest part of the learning curve appears to be over the first 30‐50 cases.
ShunShin MJ, Miyazawa AA, Keene D, et al., 2019, How to deliver personalized Cardiac Resynchronization Therapy through the precise measurement of the acute hemodynamic response: insights from the iSpot trial, Journal of Cardiovascular Electrophysiology, Vol: 30, Pages: 1610-1619, ISSN: 1045-3873
IntroductionNew pacing technologies offer greater choice of left ventricular pacing sites and greater personalization of cardiac resynchronization therapy (CRT). The effects on cardiac function of novel pacing configurations are often compared using multi‐beat averages of acute hemodynamic measurements. In this analysis of the iSpot trial we explore whether this is sufficient.MethodsThe iSpot trial was an international, prospective, acute hemodynamic trial that assessed seven CRT configurations: Standard CRT, Multispot (posterolateral vein), and Multivein (anterior and posterior vein) pacing. Invasive and non‐invasive blood pressure, and LV dP/dtmax were recorded. Eight beats were recorded before and after an alternation from AAI to the tested pacing configuration and vice‐versa. Eight alternations were performed for each configuration at each of the 5 AV delays.Results25 patients underwent the full protocol of 8 alternations. Only 4 (16%) patients had a statistically significant >3mmHg improvement over conventional CRT configuration (posterolateral vein, distal electrode). However, if only one alternation was analyzed (standard multi‐beat averaging protocol), 15 (60%) patients falsely appeared to have a superior non‐conventional configuration. Responses to pacing were significantly correlated between the different hemodynamic measures: invasive SBP versus non‐invasive SBP r=0.82 (p<0.001); invasive SBP versus LV dP/dt r=0.57, r2=0.32 (p<0.001).ConclusionsCurrent standard multi‐beat acquisition protocols are unfortunately unable to prevent false impressions of optimality arising in individual patients. Personalization processes need to include distinct repeated transitions to the tested pacing configuration in addition to averaging multiple beats. The need is not only during research stages, but also during clinical implementation.
Keene D, Shun-Shin M, Arnold A, et al., 2019, Quantification of Electromechanical Coupling to Prevent Inappropriate Implantable Cardioverter-Defibrillator Shocks, JACC: Clinical Electrophysiology, Vol: 5, Pages: 705-715, ISSN: 2405-500X
Objective To test specialised processing of laser Doppler signals for discriminating ventricular fibrillation(VF) from common causes of inappropriate therapies.BackgroundInappropriate ICD therapies remain a clinically important problem associated with morbidity and mortality.Tissue perfusion biomarkers, to assist automated diagnosis of VF, suffer the vulnerability of sometimes mistaking artefact and random noise for perfusion, which could lead to shocks being inappropriately withheld. MethodsWe developed a novel processing algorithm that combines electrogram data and laser Doppler perfusion monitoring, as a method for assessing circulatory status. We recruited 50 patients undergoing VF induction during ICD implantation. We recorded non-invasive laser Doppler and continuous electrograms, during both sinus-rhythm and VF. For each patient we simulated two additional scenarios that may lead to inappropriate shocks: ventricular-lead fracture and T-wave oversensing. We analysed the laser Doppler using three methods for reducing noise: (i)Running Mean, (ii)Oscillatory Height, (iii)a novel quantification of Electro-Mechanical coupling which gates laser Doppler against electrograms. We additionally tested the algorithm during exercise induced sinus tachycardia.ResultsOnly the Electro-mechanical coupling algorithm found a clear perfusion cut-off between sinus rhythm and VF (sensitivity and specificity 100%). Sensitivity and specificity remained 100% during simulated lead fracture and electrogram oversensing. (AUC: Running Mean 0.91, Oscillatory Height 0.86, Electro-Mechanical Coupling 1.00). Sinus tachycardia did not cause false positives.ConclusionsQuantifying the coupling between electrical and perfusion signals increases reliability of discrimination between VF and artefacts that ICDs may interpret as VF. Incorporating such methods into future ICDs may safely permit reductions of inappropriate shocks.
Howard J, Fisher L, Shun-Shin M, et al., 2019, Cardiac rhythm device identification using neural networks, JACC: Clinical Electrophysiology, Vol: 5, Pages: 576-586, ISSN: 2405-5018
BackgroundMedical staff often need to determine the model of a pacemaker or defibrillator (cardiac rhythm devices) quickly and accurately. Current approaches involve comparing a device’s X-ray appearance with a manual flow chart. We aimed to see whether a neural network could be trained to perform this task more accurately.Methods and ResultsWe extracted X-ray images of 1676 devices, comprising 45 models from 5 manufacturers. We developed a convolutional neural network to classify the images, using a training set of 1451 images. The testing set was a further 225 images, consisting of 5 examples of each model. We compared the network’s ability to identify the manufacturer of a device with those of cardiologists using a published flow-chart.The neural network was 99.6% (95% CI 97.5 to 100) accurate in identifying the manufacturer of a device from an X-ray, and 96.4% (95% CI 93.1 to 98.5) accurate in identifying the model group. Amongst 5 cardiologists using the flow-chart, median manufacturer accuracy was 72.0% (range 62.2% to 88.9%), and model group identification was not possible. The network was significantly superior to all of the cardiologists in identifying the manufacturer (p < 0.0001 against the median human; p < 0.0001 against the best human).ConclusionsA neural network can accurately identify the manufacturer and even model group of a cardiac rhythm device from an X-ray, and exceeds human performance. This system may speed up the diagnosis and treatment of patients with cardiac rhythm devices and it is publicly accessible online.
Lewis AJM, Foley P, Whinnett Z, et al., 2019, His bundle pacing: a new strategy for physiological ventricular activation, Journal of the American Heart Association : Cardiovascular and Cerebrovascular Disease, Vol: 8, Pages: e010972-e010972, ISSN: 2047-9980
The specialized fibers of the His‐Purkinje system are essential for the maintenance of the coordinated, synchronous ventricular contraction via endocardial to epicardial and apical to basal electrical activation. The right ventricle has been the most commonly used site to deliver artificial pacemaker stimuli since the 1950s, although pacing from both right ventricular (RV) apical and septal positions causes ventricular dyssynchrony, which is in turn associated with deleterious consequences including impaired myocardial perfusion,1 mitral and tricuspid regurgitation,2 an increased risk of atrial fibrillation, and systolic contractile dysfunction.3 As a result, the risk of hospitalization for heart failure was strikingly increased in patients receiving a higher proportion of ventricular pacing in the DAVID (Dual Chamber and VVI Implantable Defibrillator) trial 4, 5 and MOST (Mode Selection Trial)6 alongside an increased risk of ventricular tachycardia/fibrillation.7 Current guidelines8 and pacemaker algorithms9 therefore promote the minimization of right ventricular pacing wherever possible; however, excessive restriction of RV pacing with, for example, long atrioventricular delays impairs atrioventricular synchrony, increasing the risk of atrioventricular block at higher atrial rates and predisposing to mitral regurgitation. Furthermore, current strategies for the reduction of RV pacing have not improved clinical outcomes.10
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