Paediatric/young versus adult patients with long QT syndrome

Introduction Long QT syndrome (LQTS) is a less prevalent cardiac ion channelopathy than Brugada syndrome in Asia. The present study compared the outcomes between paediatric/young and adult LQTS patients. Methods This was a population-based retrospective cohort study of consecutive patients diagnosed with LQTS attending public hospitals in Hong Kong. The primary outcome was spontaneous ventricular tachycardia/ventricular fibrillation (VT/VF). Results A total of 142 LQTS (mean onset age=27±23 years old) were included. Arrhythmias other than VT/VF (HR 4.67, 95% CI (1.53 to 14.3), p=0.007), initial VT/VF (HR=3.25 (95% CI 1.29 to 8.16), p=0.012) and Schwartz score (HR=1.90 (95% CI 1.11 to 3.26), p=0.020) were predictive of the primary outcome for the overall cohort, while arrhythmias other than VT/VF (HR=5.41 (95% CI 1.36 to 21.4), p=0.016) and Schwartz score (HR=4.67 (95% CI 1.48 to 14.7), p=0.009) were predictive for the adult subgroup (>25 years old; n=58). A random survival forest model identified initial VT/VF, Schwartz score, initial QTc interval, family history of LQTS, initially asymptomatic and arrhythmias other than VT/VF as the most important variables for risk prediction. Conclusion Clinical and ECG presentation varies between the paediatric/young and adult LQTS population. Machine learning models achieved more accurate VT/VF prediction

Ventricular tachyarrhythmia risk in paediatric/young vs. adult Brugada syndrome patients: a territory-wide study

Introduction: Brugada syndrome (BrS) is a cardiac ion channelopathy with a higher prevalence in Asia compared to the Western populations. The present study compared the differences in clinical and electrocardiographic (ECG) presentation between paediatric/young (≤25 years old) and adult (>25 years) BrS patients. Method: This was a territory-wide retrospective cohort study of consecutive BrS patients presenting to public hospitals in Hong Kong. The primary outcome was spontaneous ventricular tachycardia/ventricular fibrillation (VT/VF). Results: The cohort consists of 550 consecutive patients (median age of initial presentation = 51 ± 23 years; female = 7.3%; follow-up period = 83 ± 80 months), divided into adult (n = 505, mean age of initial presentation = 52 ± 19 years; female = 6.7%; mean follow-up period = 83 ± 80 months) and paediatric/young subgroups (n = 45, mean age of initial presentation = 21 ± 5 years, female = 13.3%, mean follow-up period = 73 ± 83 months). The mean annual VT/VF incidence rate were 17 and 25 cases per 1,000 patient-year, respectively. Multivariate analysis showed that initial presentation of type 1 pattern (HR = 1.80, 95% CI = [1.02, 3.15], p = 0.041), initial asymptomatic presentation (HR = 0.26, 95% CI = [0.07, 0.94], p = 0.040) and increased P-wave axis (HR = 0.98, 95% CI = [0.96, 1.00], p = 0.036) were significant predictors of VT/VF for the adult subgroup. Only initial presentation of VT/VF was predictive (HR = 29.30, 95% CI = [1.75, 492.00], p = 0.019) in the paediatric/young subgroup. Conclusion: Clinical and ECG presentation of BrS vary between the paediatric/young and adult population in BrS. Risk stratification and management strategies for younger patients should take into consideration and adopt an individualised approach

Attendance-related healthcare resource utilisation and costs in patients with Brugada Syndrome in Hong Kong: A retrospective cohort study.

Understanding healthcare resource utilisation and its associated costs are important for identifying areas of improvement regarding resource allocations. However, there is limited research exploring this issue in the setting of Brugada syndrome (BrS). This was a retrospective territory-wide study of BrS patients from Hong Kong. Healthcare resource utilisation for accident and emergency (A&E), inpatient and specialist outpatient attendances were analysed over a 19-year period, with their associated costs presented in US dollars. A total of 507 BrS patients with a mean presentation age of 49.9 ± 16.3 years old were included. Of these, 384 patients displayed spontaneous type 1 electrocardiographic (ECG) Brugada pattern and 77 patients had presented with ventricular tachycardia/ventricular fibrillation (VT/VF). At the individual patient level, the median annualised costs were 110 (52-224) at the (A&E) setting, 6812 (1982-32414) at the inpatient setting and $557 (326-1001) for specialist outpatient attendances. Patients with initial VT/VF presentation had overall greater costs in inpatient ($20161 [9147-189215] vs. $5290 [1613-24937],p<0.0001) and specialist outpatient setting ($776 [438-1076] vs. $542 [293-972],p=0.015) compared to those who did not present VT. In addition, patients without Type 1 ECG pattern had greater median costs in the specialist outpatient setting ($7036 [3136-14378] vs. $4895 [2409-10554],p=0.019). There is a greater healthcare demand in the inpatient and specialist outpatient settings for BrS patients. The most expensive attendance type was inpatient setting stay at$6812 per year. The total median annualised cost of BrS patients without VT/VF presentation was 78% lower compared to patients with VT/VF presentation. [Abstract copyright: Copyright © 2022 The Authors. Published by Elsevier Inc. All rights reserved.

Comparing the performance of published risk scores in Brugada syndrome: a multi-center cohort study.

The management of Brugada Syndrome (BrS) patients at intermediate risk of arrhythmic events remains controversial. The present study evaluated the predictive performance of different risk scores in an Asian BrS population and its intermediate risk subgroup. This retrospective cohort study included consecutive patients diagnosed with BrS from January 1 , 1997 to June 20 , 2020 from Hong Kong. The primary outcome is sustained ventricular tachyarrhythmias. Two novel risk risk scores and seven machine learning-based models (random survival forest, Ada boost classifier, Gaussian naïve Bayes, light gradient boosting machine, random forest classifier, gradient boosting classifier and decision tree classifier) were developed. The area under the receiver operator characteristic (ROC) curve (AUC) [95% confidence intervals] was compared between the different models. This study included 548 consecutive BrS patients (7% female, age at diagnosis: 50±16 years, follow-up: 84±55 months). For the whole cohort, the score developed by Sieira et al. showed the best performance (AUC: 0.806 [0.747-0.865]). A novel risk score was developed using the Sieira score and additional variables significant on univariable Cox regression (AUC: 0.855 [0.808-0.901]). A simpler score based on non-invasive results only showed a statistically comparable AUC (0.784 [0.724-0.845]), improved using random survival forests (AUC: 0.942 [0.913-0.964]). For the intermediate risk subgroup (N=274), a gradient boosting classifier model showed the best performance (AUC: 0.814 [0.791-0.832]). A simple risk score based on clinical and electrocardiographic variables showed a good performance for predicting VT/VF, improved using machine learning. Abstract: The management of Brugada Syndrome (BrS) patients at intermediate risk of arrhythmic events remains controversial. This study evaluated the predictive performance of published risk scores in a cohort of BrS patients from Hong Kong (N=548) and its intermediate risk subgroup (N=274). A novel risk score developed by modifying the best performing existing score (by. Sieira et al.) showed an area under the curve of 0.855 and 0.760 for the whole BrS cohort and the intermediate risk subgroup, respectively. The performance of the different scores was significantly improved machine learning-based methods, such as random survival forests and gradient boosting classifier. [Abstract copyright: Copyright © 2022 The Authors. Published by Elsevier Inc. All rights reserved.

A territory-wide Study of arrhythmogenic right ventricular cardiomyopathy patients from Hong Kong

Background: Arrhythmogenic right ventricular cardiomyopathy/dysplasia (ARVC/D) is a hereditary disease characterized by fibrofatty infiltration of the right ventricular myocardium that predisposes affected patients to malignant ventricular arrhythmias, dual-chamber cardiac failure and sudden cardiac death (SCD). The present study aims to investigate the risk of detrimental cardiovascular events in an Asian population of ARVC/D patients, including the incidence of malignant ventricular arrhythmias, new-onset heart failure with reduced ejection fraction (HFrEF), as well as long-term mortality. Methods and Results: This was a territory-wide retrospective cohort study of patients diagnosed with ARVC/D between 1997 and 2019 in Hong Kong. This study consisted of 109 ARVC/D patients (median age: 61 [46–71] years; 58% male). Of these, 51 and 24 patients developed incident VT/VF and new-onset HFrEF, respectively. Five patients underwent cardiac transplantation, and 14 died during follow-up. Multivariate Cox regression identified prolonged QRS duration as a predictor of VT/VF (p <0.05). Female gender, prolonged QTc duration, the presence of epsilon waves and T-wave inversion (TWI) in any lead except aVR/V1 predicted new-onset HFrEF (p <0.05). The presence of epsilon waves, in addition to the parameters of prolonged QRS duration and worsening ejection fraction predicted all-cause mortality (p <0.05). Clinical scores were developed to predict incident VT/VF, new-onset HFrEF and all-cause mortality, and all were significantly improved by machine learning techniques. Conclusions: Clinical and electrocardiographic parameters are important for assessing prognosis in ARVC/D patients and should in turn be used in tandem to aid risk stratification in the hospital setting

Territory-wide cohort study of Brugada syndrome in Hong Kong: predictors of long-term outcomes using random survival forests and non-negative matrix factorisation

Objectives: Brugada syndrome (BrS) is an ion channelopathy that predisposes affected patients to spontaneous ventricular tachycardia/fibrillation (VT/VF) and sudden cardiac death. The aim of this study is to examine the predictive factors of spontaneous VT/VF. Methods: This was a territory-wide retrospective cohort study of patients diagnosed with BrS between 1997 and 2019. The primary outcome was spontaneous VT/VF. Cox regression was used to identify significant risk predictors. Non-linear interactions between variables (latent patterns) were extracted using non-negative matrix factorisation (NMF) and used as inputs into the random survival forest (RSF) model. Results: This study included 516 consecutive BrS patients (mean age of initial presentation=50±16 years, male=92%) with a median follow-up of 86 (IQR: 45–118) months. The cohort was divided into subgroups based on initial disease manifestation: asymptomatic (n=314), syncope (n=159) or VT/VF (n=41). Annualised event rates per person-year were 1.70%, 0.05% and 0.01% for the VT/VF, syncope and asymptomatic subgroups, respectively. Multivariate Cox regression analysis revealed initial presentation of VT/VF (HR=24.0, 95% CI=1.21 to 479, p=0.037) and SD of P-wave duration (HR=1.07, 95% CI=1.00 to 1.13, p=0.044) were significant predictors. The NMF-RSF showed the best predictive performance compared with RSF and Cox regression models (precision: 0.87 vs 0.83 vs. 0.76, recall: 0.89 vs. 0.85 vs 0.73, F1-score: 0.88 vs 0.84 vs 0.74). Conclusions: Clinical history, electrocardiographic markers and investigation results provide important information for risk stratification. Machine learning techniques using NMF and RSF significantly improves overall risk stratification performance

Successful percutaneous retrieval of a leadless pacemaker due to an acute rise in pacing threshold

Leadless cardiac pacemakers (LCP) have become available recently. Both its acute and long-term performance in a large population of patients remain to be tested. Subacute rise in pacing threshold has been reported as an uncommon complication. On the other hand, the retrieval technique for LCP with passive fixation mechanism has not been previously described in details. Herein we report a newly recognized complication of an acute rise in pacing threshold very soon after implantation of an LCP without radiographic dislodgement. Percutaneous retrieval of this LCP with passive fixation mechanism was successful using a novel technique with the cryoballoon steerable sheath and a snare. Keywords: Leadless pacemaker, Percutaneous retrieval, Pacing threshold, Bradycardia, Dislodgemen

Territory-wide cohort study of Brugada syndrome in Hong Kong: predictors of long-term outcomes using random survival forests and non-negative matrix factorisation

Objectives Brugada syndrome (BrS) is an ion channelopathy that predisposes affected patients to spontaneous ventricular tachycardia/fibrillation (VT/VF) and sudden cardiac death. The aim of this study is to examine the predictive factors of spontaneous VT/VF.Methods This was a territory-wide retrospective cohort study of patients diagnosed with BrS between 1997 and 2019. The primary outcome was spontaneous VT/VF. Cox regression was used to identify significant risk predictors. Non-linear interactions between variables (latent patterns) were extracted using non-negative matrix factorisation (NMF) and used as inputs into the random survival forest (RSF) model.Results This study included 516 consecutive BrS patients (mean age of initial presentation=50±16 years, male=92%) with a median follow-up of 86 (IQR: 45–118) months. The cohort was divided into subgroups based on initial disease manifestation: asymptomatic (n=314), syncope (n=159) or VT/VF (n=41). Annualised event rates per person-year were 1.70%, 0.05% and 0.01% for the VT/VF, syncope and asymptomatic subgroups, respectively. Multivariate Cox regression analysis revealed initial presentation of VT/VF (HR=24.0, 95% CI=1.21 to 479, p=0.037) and SD of P-wave duration (HR=1.07, 95% CI=1.00 to 1.13, p=0.044) were significant predictors. The NMF-RSF showed the best predictive performance compared with RSF and Cox regression models (precision: 0.87 vs 0.83 vs. 0.76, recall: 0.89 vs. 0.85 vs 0.73, F1-score: 0.88 vs 0.84 vs 0.74).Conclusions Clinical history, electrocardiographic markers and investigation results provide important information for risk stratification. Machine learning techniques using NMF and RSF significantly improves overall risk stratification performance