Primary cilia suppress the fibrotic activity of atrial fibroblasts from patients with atrial fibrillation in vitro.

Atrial fibrosis serves as an arrhythmogenic substrate in atrial fibrillation (AF) and contributes to AF persistence. Treating atrial fibrosis is challenging because atrial fibroblast activity is multifactorial. We hypothesized that the primary cilium regulates the profibrotic response of AF atrial fibroblasts, and explored therapeutic potentials of targeting primary cilia to treat fibrosis in AF. We included 25 patients without AF (non-AF) and 26 persistent AF patients (AF). Immunohistochemistry using a subset of the patients (non-AF: n = 10, AF: n = 10) showed less ciliated fibroblasts in AF versus non-AF. Acetylated α-tubulin protein levels were decreased in AF, while the gene expressions of AURKA and NEDD9 were highly increased in AF patients' left atrium. Loss of primary cilia in human atrial fibroblasts through IFT88 knockdown enhanced expression of ECM genes, including FN1 and COL1A1. Remarkably, restoration or elongation of primary cilia by an AURKA selective inhibitor or lithium chloride, respectively, prevented the increased expression of ECM genes induced by different profibrotic cytokines in atrial fibroblasts of AF patients. Our data reveal a novel mechanism underlying fibrotic substrate formation via primary cilia loss in AF atrial fibroblasts and suggest a therapeutic potential for abrogating atrial fibrosis by restoring primary cilia.

Left atrial strain and recurrence of atrial fibrillation after thoracoscopic surgical ablation: a subanalysis of the AFACT study.

To assess transthoracic echocardiographic (TTE) left atrial (LA) strain parameters and their association with atrial fibrillation (AF) recurrence after thoracoscopic surgical ablation (SA) in patients in sinus rhythm (SR) or in AF at baseline. Patients participating in the Atrial Fibrillation Ablation and Autonomic Modulation via Thoracoscopic Surgery trial were included. All patients underwent thoracoscopic pulmonary vein isolation with LA appendage exclusion and were randomized to ganglion plexus (GP) or no GP ablation. In TTEs performed before surgery, LA strain and mechanical dispersion (MD) of the LA reservoir and conduit phase in all patients, and of the contraction phase in patients in SR were obtained. Recurrence of AF was defined as any documented atrial tachyarrhythmia lasting > 30 s during one year of follow-up. Two hundred and four patients (58.6 ± 7.8 years, 73% male, 57% persistent AF) were included. At baseline TTE 121 (59%) were in SR and 83 (41%) had AF. Patients with AF recurrence had lower LA strain of the reservoir phase (13.0% vs. 16.6%; p = < 0.001) and a less decrease in strain of the conduit phase (-9.0% vs. -11.8%; p = 0.006), regardless of rhythm. MD of the conduit phase was larger in patients with AF recurrence (79.4 vs. 43.5 ms; p = 0.012). Multivariate cox regression analysis demonstrated solely an association between LA strain of the reservoir phase and AF recurrence in patients in SR (HR 0.95, p = 0.046) or with AF (HR 0.90, p = 0.038). A reduction in LA strain of the reservoir phase prior to SA predicts recurrence of AF in both patients with SR or AF. Left atrial strain assessment may therefore add to a better patient selection for SA.

Prediction of Atrial Fibrillation Recurrence after Thoracoscopic Surgical Ablation Using Machine Learning Techniques.

Thoracoscopic surgical ablation (SA) for atrial fibrillation (AF) has shown to be an effective treatment to restore sinus rhythm in patients with advanced AF. Identifying patients who will not benefit from this procedure would be valuable to improve personalized AF therapy. Machine learning (ML) techniques may assist in the improvement of clinical prediction models for patient selection. The aim of this study is to investigate how available baseline characteristics predict AF recurrence after SA using ML techniques. One-hundred-sixty clinical baseline variables were collected from 446 AF patients undergoing SA in our tertiary referral center. Multiple ML models were trained on five outcome measurements, including either all or a number of key variables selected by using the least absolute shrinkage and selection operator (LASSO). There was no difference in model performance between different ML techniques or outcome measurements. Variable selection significantly improved model performance (AUC: 0.73, 95% CI: 0.68-0.77). Subgroup analysis showed a higher model performance in younger patients (<55 years, AUC: 0.82 vs. >55 years, AUC 0.66). Recurrences of AF after SA can be predicted best when using a selection of baseline characteristics, particularly in young patients.

Extracellular matrix remodeling precedes atrial fibrillation: Results of the PREDICT-AF trial.

BACKGROUND: To which extent atrial remodeling occurs before atrial fibrillation (AF) is unknown. OBJECTIVE: The PREventive left atrial appenDage resection for the predICtion of fuTure Atrial Fibrillation (PREDICT-AF) study investigated such subclinical remodeling, which may be used for risk stratification and AF prevention. METHODS: Patients (N = 150) without a history of AF with a CHA2DS2-VASc score of ≥2 at an increased risk of developing AF were included. The left atrial appendage was excised and blood samples were collected during elective cardiothoracic surgery for biomarker discovery. Participants were followed for 2 years with Holter monitoring to determine any atrial tachyarrhythmia after a 50-day blanking period. RESULTS: Eighteen patients (12%) developed incident AF, which was associated with increased tissue gene expression of collagen I (COL1A1), collagen III (COL3A1), and collagen VIII (COL8A2), tenascin-C (TNC), thrombospondin-2 (THBS2), and biglycan (BGN). Furthermore, the fibroblast activating endothelin-1 (EDN1) and sodium voltage-gated channel ß subunit 2 (SCN2B) were associated with incident AF whereas the Kir2.1 channel (KCNJ2) tended to downregulate. The plasma levels of COL8A2 and TNC correlated with tissue expression and predicted incident AF. A gene panel including tissue KCNJ2, COL1A1, COL8A2, and EDN1 outperformed clinical prediction models in discriminating incident AF. CONCLUSION: The PREDICT-AF study demonstrates that atrial remodeling occurs long before incident AF and implies future potential for early patient identification and therapies to prevent AF (ClinicalTrials.gov identifier NCT03130985).

Neutrophil degranulation interconnects over-represented biological processes in atrial fibrillation.

Despite our expanding knowledge about the mechanism underlying atrial fibrillation (AF), the interplay between the biological events underlying AF remains incompletely understood. This study aimed to identify the functionally enriched gene-sets in AF and capture their interconnection via pivotal factors, that may drive or be driven by AF. Global abundance of the proteins in the left atrium of AF patients compared to control patients (n = 3/group), and the functionally enriched biological processes in AF were determined by mass-spectrometry and gene set enrichment analysis, respectively. The data were validated in an independent cohort (n = 19-20/group). In AF, the gene-sets of innate immune system, metabolic process, cellular component disassembly and ion homeostasis were up-regulated, while the gene-set of ciliogenesis was down-regulated. The innate immune system was over-represented by neutrophil degranulation, the components of which were extensively shared by other gene-sets altered in AF. In the independent cohort, an activated form of neutrophils was more present in the left atrium of AF patients with the increased gene expression of neutrophil granules. MYH10, required for ciliogenesis, was decreased in the atrial fibroblasts of AF patients. We report the increased neutrophil degranulation appears to play a pivotal role, and affects multiple biological processes altered in AF.

Computer versus cardiologist: Is a machine learning algorithm able to outperform an expert in diagnosing a phospholamban p.Arg14del mutation on the electrocardiogram?

BACKGROUND: Phospholamban (PLN) p.Arg14del mutation carriers are known to develop dilated and/or arrhythmogenic cardiomyopathy, and typical electrocardiographic (ECG) features have been identified for diagnosis. Machine learning is a powerful tool used in ECG analysis and has shown to outperform cardiologists. OBJECTIVES: We aimed to develop machine learning and deep learning models to diagnose PLN p.Arg14del cardiomyopathy using ECGs and evaluate their accuracy compared to an expert cardiologist. METHODS: We included 155 adult PLN mutation carriers and 155 age- and sex-matched control subjects. Twenty-one PLN mutation carriers (13.4%) were classified as symptomatic (symptoms of heart failure or malignant ventricular arrhythmias). The data set was split into training and testing sets using 4-fold cross-validation. Multiple models were developed to discriminate between PLN mutation carriers and control subjects. For comparison, expert cardiologists classified the same data set. The best performing models were validated using an external PLN p.Arg14del mutation carrier data set from Murcia, Spain (n = 50). We applied occlusion maps to visualize the most contributing ECG regions. RESULTS: In terms of specificity, expert cardiologists (0.99) outperformed all models (range 0.53-0.81). In terms of accuracy and sensitivity, experts (0.28 and 0.64) were outperformed by all models (sensitivity range 0.65-0.81). T-wave morphology was most important for classification of PLN p.Arg14del carriers. External validation showed comparable results, with the best model outperforming experts. CONCLUSION: This study shows that machine learning can outperform experienced cardiologists in the diagnosis of PLN p.Arg14del cardiomyopathy and suggests that the shape of the T wave is of added importance to this diagnosis.

Complications related to elective generator replacement of the subcutaneous implantable defibrillator.

AIMS: To guarantee uninterrupted function of the subcutaneous implantable cardioverter-defibrillator (S-ICD), the pulse generator needs to be surgically replaced before the battery is depleted. The risks related to this replacement substantially impact long-term outcome for S-ICD recipients, as the majority will undergo one or several of these procedures in their lifetime. We aim to describe the procedural characteristics of the replacement procedure and to provide an insight in the complications associated with these replacements. METHODS AND RESULTS: In this retrospective analysis, data from replacement procedures and follow-up visits were collected from all patients who underwent elective S-ICD generator replacement in our tertiary centre from June 2014 until November 2019. Original device position was assessed using the PRAETORIAN score. Complications were defined as those requiring surgical intervention, systemic antibiotic treatment, or device extraction. Seventy-two patients were included, with a median follow-up of 1.9 years (IQR 0.6-3.3 years) after replacement. Battery depletion occurred after 5.9 ± 0.7 years. The pulse generator was repositioned in patients with a PRAETORIAN score ≥90 to minimize the defibrillation threshold. Although there was an increase in impedance compared to the implant procedure, first shock conversion rate during defibrillation testing was 91.4% with a success rate of 100% after multiple attempts. Two patients developed a complication after, respectively, 9 and 21 months, resulting in a complication rate of 1.4% per year. CONCLUSION: With a median follow-up of 1.9 years, this study shows a low complication rate after S-ICD replacement, with a first shock conversion rate of 91.4%.

Real-world performance of the atrial fibrillation monitor in patients with a subcutaneous ICD.

INTRODUCTION: The third-generation subcutaneous implantable cardioverter-defibrillator (S-ICD) (EMBLEM™ A219, Boston Scientific) contains a new diagnostic tool to detect atrial fibrillation (AF) in S-ICD patients, without the use of an intracardiac lead. This is the first study to evaluate the performance of the S-ICD AF monitor (AFM). METHODS: The AFM algorithm analyzes a subcutaneous signal for the presence of AF, similar to the signals collected by implantable and wearable diagnostic devices. The AFM algorithm combines heart rate (HR) scatter analysis with an HR histogram. The algorithm was tested against publicly available electrocardiogram databases (simulated performance). Real-world performance of the algorithm was evaluated by using the S-ICD LATITUDE remote monitoring (RM) database. RESULTS: The simulated performance of the AFM algorithm resulted in a sensitivity of 95.0%, specificity of 100.0%, and positive predictive value (PPV) of 100.0%. To evaluate the real-world performance of the AFM, 7744 S-ICD devices were followed for up to 30 months by RM, whereof 99.5% had the AFM enabled. A total of 387 AF episodes were randomly chosen for adjudication, resulting in a PPV of 67.7%. The main cause of misclassification was atrial and ventricular ectopy. CONCLUSION: The AFM exhibited a very high sensitivity and specificity in a simulated setting, designed to maximize PPV in order to minimize the clinical burden of reviewing falsely detected AF events. The real-world performance of the AFM, enabled in 99.5% of S-ICD patients, is a PPV of 67.7%.

Long-term follow-up of the two-incision implantation technique for the subcutaneous implantable cardioverter-defibrillator.

INTRODUCTION: The two-incision implantation technique of the subcutaneous implantable cardioverter-defibrillator (S-ICD) was introduced as an alternative to the standard three-incision approach by omitting the superior parasternal incision. Thereby, complications may be prevented. Short-term follow-up demonstrated the safety and efficacy of the two-incision technique. However, long-term results are lacking. METHODS: This retrospective study included patients implanted between February 2009 and June 2020. Patients were divided into a group of patients who were implanted with the standard three-incision technique and a group who were implanted with the two-incision technique. Outcomes were defibrillation impedance and efficacy and complications requiring intervention. RESULTS: A total of 268 patients were included (age 42.4 ± 16.6 years, 35.4% female, BMI 25.1 ± 4.5 kg/m2 ). Thirty-one patients underwent S-ICD implantation with the three-incision technique and 237 patients with the two-incision technique. First shock efficacy during defibrillation testing was 93% in the three-incision group versus 94% in the two-incision group (P = .69), and shock impedance was 85 versus 68 ohms (P = .04). First shock success was 75% versus 76% for spontaneous episodes (P = 1.00). Complication-free survival at 5-year follow-up in the three-incision group was estimated at 0.96 (95% CI 0.90-1.00) versus 0.98 (95% CI 0.96-1.00) in the two-incision group (P = .20) and for inappropriate shocks at 5-year 0.77 (95% CI 0.63-0.94) versus 0.83 (95% CI 0.77-0.89, P = .30), respectively. CONCLUSION: Five-year follow-up in this S-ICD cohort showed similar complication rates and effectiveness of two-incision technique compared to the three-incision technique. This technique offers physicians a less invasive and more simplified implantation procedure for the S-ICD, with a better cosmetic result.

Improving the care for female subcutaneous ICD patients: A qualitative study of gender-specific issues.

BACKGROUND: The subcutaneous implantable cardioverter-defibrillator (S-ICD) consists of a large generator and is implanted near the left breast. This might lead to discomfort and problems with self-perception and sexuality, especially in the female population. We aimed to assess the issues that female S-ICD patients experience and to provide practical guidance for cardiologists and implanters on minimizing these issues. METHODS: For this retrospective single-center study, we conducted semi-structured interviews with four female S-ICD patients and processed their experiences into a questionnaire. This consisted of three open questions and 17 statements that participants could answer through a five-point Likert scale. The questionnaire was subsequently sent to all female adult patients who received an S-ICD between February 2009 and November 2018 in our tertiary centre in Amsterdam, the Netherlands. RESULTS: The response rate of the questionnaire was 73%, with 52 female respondents (mean age 47.4 ± 12.5 years, mean time since implant 4.6 ± 3.1 years). Postoperative pain exceeded the expectation of 54% of the respondents. Furthermore, 14 out of 49 respondents (29%) expressed an unpleasant feeling during intimate contact with their sexual partner since the implant. Many women (44%) reported daily discomfort caused by their bra and preferred a more cranial and posterior position of the S-ICD generator. Finally, a smaller design of the generator is desired by a great majority (63%) of female S-ICD patients CONCLUSION: Female S-ICD patients experience a variety of issues with a substantial impact on their daily life. Most issues that we identified would benefit from adequate counseling and implanter awareness.

A morphology based deep learning model for atrial fibrillation detection using single cycle electrocardiographic samples.

BACKGROUND: Deep learning (DL) has shown promising results in improving atrial fibrillation (AF) detection algorithms. However, these models are often criticized because of their "black box" nature. AIM: To develop a morphology based DL model to discriminate AF from sinus rhythm (SR), and to visualize which parts of the ECG are used by the model to derive to the right classification. METHODS: We pre-processed raw data of 1469 ECGs in AF or SR, of patients with a history AF. Input data was generated by normalizing all single cycles (SC) of one ECG lead to SC-ECG samples by 1) centralizing the R wave or 2) scaling from R-to- R wave. Different DL models were trained by splitting the data in a training, validation and test set. By using a DL based heat mapping technique we visualized those areas of the ECG used by the classifier to come to the correct classification. RESULTS: The DL model with the best performance was a feedforward neural network trained by SC-ECG samples on a R-to-R wave basis of lead II, resulting in an accuracy of 0.96 and F1-score of 0.94. The onset of the QRS complex proved to be the most relevant area for the model to discriminate AF from SR. CONCLUSION: The morphology based DL model developed in this study was able to discriminate AF from SR with a very high accuracy. DL model visualization may help clinicians gain insights into which (unrecognized) ECG features are most sensitive to discriminate AF from SR.

Minimal defibrillation thresholds and the correlation with implant position in subcutaneous implantable-defibrillator patients.

BACKGROUND: Since the introduction of the subcutaneous implantable-defibrillator (S-ICD) knowledge of factors elevating the defibrillation threshold (DFT), have increased. Optimal device positioning most likely results in a decrease in DFT. The PRAETORIAN score is a tool to systematically evaluate S-ICD implant position and predict conversion success by estimating the DFT on a chest X-ray. The objective of this study is to determine DFT in de novo S-ICD patients. METHODS: De novo S-ICD patients were enrolled with DFT testing using a single 30 J shock or a prespecified step-down protocol. Chest X-rays were obtained and implant position was evaluated using the PRAETORIAN score. RESULTS: Fifteen patients, age 47 (±18) years and body mass index (BMI) 25(±3) kg/m2 , underwent conversion testing with a single 30 J shock. Fourteen patients (93%) converted successfully. Implant position was optimal in all patients, PRAETORIAN score of 30 (100%). Twelve patients were available for analysis in the step-down DFT cohort, age 46 years (±15), left ventricular ejection fraction 50% (±15%) and a median BMI of 25.7 kg/m2 (range 23.8-29.1 kg/m2 ). No complications occurred during DFT testing. Mean DFT was 29 J (±12 J). Time to shock was 11 seconds (±2 seconds) for a 20 J shock compared with 17 seconds in case of a 70 J shock output. Nearly all patients were implanted with optimal device positioning with the lowest possible PRAETORIAN score of 30 (92%). CONCLUSION: DFT in S-ICD patients with optimal device positioning is lower than previously reported. Conversion testing using a low shock output reduced time to therapy by 6 seconds on average.

Rationale and design of the PRAETORIAN-DFT trial: A prospective randomized CompArative trial of SubcutanEous ImplanTable CardiOverter-DefibrillatoR ImplANtation with and without DeFibrillation testing.

In transvenous implantable cardioverter-defibrillator (TV-ICD) implants, routine defibrillation testing (DFT) does not improve shock efficacy or reduce arrhythmic death but patients are exposed to the risk of complications related to DFT. The conversion rate of DFT in subcutaneous ICD (S-ICD) is high and first shock efficacy is similar to TV-ICD efficacy rates. STUDY DESIGN: The PRAETORIAN-DFT trial is an investigator-initiated, randomized, controlled, multicenter, prospective two-arm trial designed to demonstrate non-inferiority of omitting DFT in patients undergoing S-ICD implantation in which the S-ICD system components are optimally positioned. Positioning of the S-ICD will be assessed with the PRAETORIAN score. The PRAETORIAN score is developed to systematically evaluate implant position of the S-ICD system components which determine the defibrillation threshold on post-operative chest X-ray. A total of 965 patients, scheduled to undergo a de novo S-ICD implantation without contra-indications for either DFT strategy, will be randomized to either standard of care S-ICD implantation with DFT, or S-ICD implantation without DFT but with evaluation of the implant position using the PRAETORIAN score. The study is powered to claim non-inferiority of S-ICD implantation without DFT in de novo S-ICD patients in respect to the primary endpoint of first shock efficacy in spontaneous arrhythmia episodes. Patients with a high PRAETORIAN score (≥90) in the interventional arm of this study will undergo DFT according to the same DFT protocol as in the control arm. CONCLUSION: The PRAETORIAN-DFT trial is a randomized trial that aims to gain scientific evidence to safely omit a routine DFT after S-ICD implantation in patients with correct device positioning.

A novel tool to evaluate the implant position and predict defibrillation success of the subcutaneous implantable cardioverter-defibrillator: The PRAETORIAN score.

BACKGROUND: Suboptimal positioning of the subcutaneous implantable cardioverter-defibrillator (S-ICD) increases the defibrillation threshold and risk of conversion failure. OBJECTIVE: Our objective is to develop a tool to evaluate the implant position and predict defibrillation success of the S-ICD: the PRAETORIAN score. METHODS: The PRAETORIAN score is based on clinical and computer modeling knowledge of determinants affecting the defibrillation threshold: subcoil fat, subgenerator fat, and anterior positioning of the S-ICD generator. The score evaluates these determinants on the postoperative anterior-posterior and lateral chest radiographs and has 3 categories: 30-<90 points representing a low risk, 90-<150 points representing an intermediate risk, and ≥150 points representing a high risk of conversion failure. The score was developed using 2 separate S-ICD data sets for derivation and validation. The performance metrics are the positive and negative predictive values. RESULTS: The development data set consisted of 181 patients with S-ICD, and the validation cohort consisted of 321 patients from the S-ICD Investigational Device Exemption trial. The distribution of scores was 93%-98% low risk (<90 points), 2%-5% intermediate risk (90-<150 points), and 1% high risk (≥150 points). The positive predictive value for an intermediate or high PRAETORIAN score for a failed conversion test was 51%, while a low PRAETORIAN score predicted a successful conversion in 99.8% of patients. CONCLUSION: The PRAETORIAN score allows the identification of patients with high defibrillation thresholds by using the routine chest radiograph and provides feedback to implanters on S-ICD positioning. The PRAETORIAN-DFT trial will prospectively validate the score by randomizing to standard conversion testing vs using the score without conversion testing.