BACKGROUND:Optimisation of medical therapy is recommended for patients with newly diagnosed non-ischaemic cardiomyopathies (NICM) before consideration of a primary preventive implantable cardioverter-defibrillator (ICD). During this optimisation period, patients face a potentially elevated risk for sudden cardiac death (SCD) that can be countered with a wearable cardioverter-defibrillator (WCD). This systematic review aims to assess the risk for SCD in patients with newly diagnosed NICM. METHODS:A systematic review was performed in Medline, Embase and Cochrane Library last updated on March 2025. Studies with patients aged ≥18 years with newly diagnosed NICM (≤90 days) who were recipients of WCD were included. Study selection, study quality assessment and data extraction were performed by two reviewers independently. Data on percentage of patients with appropriate WCD shocks (as proxy for sustained ventricular arrhythmia, potentially leading to SCD), inappropriate WCD shocks and device implantation were pooled by random-effects model. RESULTS:50 non-controlled observational studies were included, comprising a total of 10 066 patients with NICM. The percentage of appropriate shocks was 1% (87/7708; 95% CI 1% to 2%) in patients with NICM, 2% (16/1049; 95% CI 1% to 2%) in patients with myocarditis, 3% (7/183; 95% CI 0% to 20%) in peripartum cardiomyopathy, 2% (2/102; 95% CI 0% to 7%) in Takotsubo syndrome and 1% (8/594; 95% CI 1% to 3%) for congenital/inherited or genetic cardiomyopathy. Inappropriate shocks ranged from 0% to 1%. At the end of follow-up, between 6% (Takotsubo syndrome) and 43% (congenital/inherited or genetic cardiomyopathy) of patients received an ICD. CONCLUSION:Patients with NICM face a significant risk of SCD during the drug optimisation period before deciding if they qualify for ICD implantation. Results of this meta-analysis are based on non-comparative studies; however, the assessment of an appropriate shock delivered and recorded by the WCD is highly reliable. PROSPERO REGISTRATION NUMBER:CRD42024555879.

BACKGROUND AND AIMS:Although use of the subcutaneous implantable cardioverter defibrillator (S-ICD) is increasing, evidence from industry-independent and unselected populations remains limited. METHODS:HONEST is a ongoing nationwide academic observational study enrolling 98.2% of patients implanted with an S-ICD across France (2012-2019). Five-year clinical endpoints were centrally adjudicated. RESULTS:Overall, 4924 patients were enrolled (mean age 49.9 ± 15 years, 76.7% male, 63.0% for primary prevention). Implants used general anaesthesia (78.9%), and defibrillation testing (82.6%). Perioperative complications (within 30 days) occurred in 4.4%. At 5 years, cumulative incidence rates were 13.8% for inappropriate shocks, 10.8% for early battery depletion, 2.4% for infections, 1.5% for lead dysfunction, and 1.4% for chronic discomfort. Reoperation was required in 16.9%, need for cardiac pacing in 3.1%, and definite S-ICD extraction in 8.4%. Inappropriate shocks were independently associated with male sex (hazard ratio [HR] 1.29, 95% confidence interval [CI] 1.14-1.46, P < .001), obesity (HR 1.35, 95% CI 1.02-1.79, P = .032), arrhythmogenic right ventricular cardiomyopathy (HR 1.70, 95% CI 1.03-2.81, P = .036), and the presence of a pacemaker (HR 2.20, 95% CI 1.16-4.17, P = .016). SMART Pass filtering significantly reduced inappropriate shocks (HR 0.67, 95% CI 0.50-0.89, P = .007). Among patients with inappropriate shocks, ∼1% developed induced ventricular fibrillation (one fatality), and 10% underwent device extraction. Ineffective shocks or undetected arrhythmias occurred in only 0.2%. Among 547 deaths (11.1%), 53.9% were cardiovascular, including 26 sudden deaths, and 8 were S-ICD/procedure-related, with none related to S-ICD extraction. CONCLUSIONS:This nationwide study refines the long-term event profile of S-ICD therapy and may inform clinical practice and device selection.

BACKGROUND:Evidence supporting the Micra AV leadless pacing system has largely derived from highly experienced centers, potentially limiting generalizability to routine clinical practice. METHODS:The AV-CESAR study (French Cohort Evaluating the Effectiveness of Atrioventricular Synchrony by the micRa AV) is a nationwide retrospective cohort, including the first 1000 patients implanted with a Medtronic Micra AV leadless pacemaker in France (2020-2024). Mean follow-up was 13.4±10.6 months. Primary end points were early (in-hospital) and late (postdischarge) device-related major complications; pacemaker syndrome and need for implantation of a new pacing system were centrally adjudicated. RESULTS:Among 1003 patients, device implantation was successful in 1000 (99.7%). Mean age was 72.0±15 years; 62.8% were men, 44.0% had ≥2 comorbidities, and 62.4% were unsuitable for transvenous pacemakers. The primary indication was permanent complete atrioventricular block with preserved sinus rhythm (78.0%). Early major complications occurred in 2.4%, including pericardial effusion (0.8%; 3 requiring surgery), access-site complications (0.8%), and thromboembolism (0.3%). Late major complications included pacemaker syndrome (2.5%), pacing-induced cardiomyopathy (1.2%), high thresholds (>4 V/0.24ms, 0.3%), and premature battery depletion (0.2%). No device infections or dislodgements were observed. Overall, 2.5% of patients required implantation of a new pacing system (pacing-induced cardiomyopathy n=11; pacemaker syndrome n=7; high threshold n=3; battery/software failure n=3; tricuspid regurgitation n=1) and 12.7% were permanently reprogrammed to ventricular paced/sensed, inhibited (VVI) mode. In pacing-dependent patients with ambulatory Holter monitoring (>3.4 million paced cycles), mean atrioventricular synchrony was 67.6±17.3% and correlated with device-reported AM-VP (74.8±17.1%; R2=0.92; P<0.001). Atrioventricular synchrony declined at heart rates >90 beats per minute (5.6% of monitored time). All-cause mortality was 13.8%, with 0.2% directly device-related; 41.7% of deaths were cardiovascular. CONCLUSIONS:The Micra AV system is primarily used as an alternative when dual-chamber conventional pacemakers are not feasible. It demonstrated acceptable safety and clinical performance in a high-risk population. The marked reduction in atrioventricular synchrony at higher heart rates may suggest limited clinical benefit in patients with higher exertional heart rates. REGISTRATION:URL: https://clinicaltrials.gov/study/NCT05953558; Unique identifier: NCT05953558.

An audible alarm from an implantable cardioverter defibrillator (ICD) can provoke considerable anxiety in the patient. An alarm may result from several causes, some of which require urgent attention. A knowledge of the different types of audible alerts as well as methodical device interrogation is needed to unravel the cause of ICD alarms. The present case instructively illustrates the systematic approach to a patient presenting with an audible alarm from an ICD, discusses appropriate management and details of the relevant device algorithms involved.

Background:Sudden death remains a major global cause of mortality, yet recent European trends are poorly characterized. We analyzed sudden death mortality across Europe from 2010 to 2020, assessing variations by age, sex, and region. Methods:We extracted sudden death-attributable mortality data from the World Health Organization (WHO) mortality dataset for 2010-2020. Age-adjusted mortality rates (AAMRs) were analyzed using joinpoint regression modeling, expressed as average annual percent change (AAPC) with 95% confidence intervals (CIs). A parallelism test compared trend differences across groups. Findings:From 2010 to 2020, there were 2,583,559 attributed sudden death (1,935,741 men and 647,818 women) in 26 European countries. Overall, the AAMR increased [AAPC: +2.9% (95% CI: 2.0-4.1), p < 0.001], with a significantly greater increase in women compared to men (p = 0.01). Regionally, AAMRs decreased in Western Europe [AAPC: -2.0% (95% CI: -2.1 to -0.1), p = 0.02], plateaued in Northern Europe [AAPC: -2.0% (95% CI: -4.7 to 0.8), p = 0.15], while increasing in Southern [+3.3% (95% CI: 1.5-8.2, p = 0.001] and Eastern Europe [AAPC: +3.4% (95% CI: 1.7-5.0), p < 0.001]. At the country level, substantial differences were observed, with Austria and Belgium showing the highest reduction of AAPC (-8.0% and -7.9%, respectively), contrasting with an increase in Spain and Germany (+3.3% and +2.8%, respectively). Interpretation:Rising sudden death mortality in Europe likely reflected evolving sex- and region-specific patterns, including the increasing cardiovascular risk burden among women and broader demographic changes across different parts of Europe. Equitable, multidisciplinary strategies are needed to curb this trend. Funding:None.

Summary: Background: Sudden death remains a major global cause of mortality, yet recent European trends are poorly characterized. We analyzed sudden death mortality across Europe from 2010 to 2020, assessing variations by age, sex, and region. Methods: We extracted sudden death-attributable mortality data from the World Health Organization (WHO) mortality dataset for 2010–2020. Age-adjusted mortality rates (AAMRs) were analyzed using joinpoint regression modeling, expressed as average annual percent change (AAPC) with 95% confidence intervals (CIs). A parallelism test compared trend differences across groups. Findings: From 2010 to 2020, there were 2,583,559 attributed sudden death (1,935,741 men and 647,818 women) in 26 European countries. Overall, the AAMR increased [AAPC: +2.9% (95% CI: 2.0–4.1), p < 0.001], with a significantly greater increase in women compared to men (p = 0.01). Regionally, AAMRs decreased in Western Europe [AAPC: −2.0% (95% CI: −2.1 to −0.1), p = 0.02], plateaued in Northern Europe [AAPC: −2.0% (95% CI: −4.7 to 0.8), p = 0.15], while increasing in Southern [+3.3% (95% CI: 1.5–8.2, p = 0.001] and Eastern Europe [AAPC: +3.4% (95% CI: 1.7–5.0), p < 0.001]. At the country level, substantial differences were observed, with Austria and Belgium showing the highest reduction of AAPC (−8.0% and −7.9%, respectively), contrasting with an increase in Spain and Germany (+3.3% and +2.8%, respectively). Interpretation: Rising sudden death mortality in Europe likely reflected evolving sex- and region-specific patterns, including the increasing cardiovascular risk burden among women and broader demographic changes across different parts of Europe. Equitable, multidisciplinary strategies are needed to curb this trend. Funding: None.

BACKGROUND:Bradyarrhythmia is a common and potentially serious cause of syncope, often difficult to detect due to its intermittent nature. Traditional ECG monitoring methods either provide low diagnostic accuracy or delay diagnosis, increasing the risk of recurrence. We hypothesized that a deep learning-enabled, 24-hour, single-lead ECG could detect past episodes of bradyarrhythmia. METHODS:Using unselected 14-day single-lead ambulatory ECG recordings, we developed a deep learning model to identify patients with prior asystole from sinus arrest or complete heart block. The model was trained using the last 24 hours of each recording, free of bradyarrhythmias, to identify daytime sinus pause of ≥3 s, anytime sinus pause of ≥6 s, complete heart block, or a composite of these bradyarrhythmias from the previous 13 days. RESULTS:A total of 320 959 unselected 14-day ambulatory ECG recordings (mean age, 60.5±17.8 years; 60% female) were split into training (n=189 414), tuning (n=45 982), internal validation (n=43 390), and external validation (n=42 173) sets. External validation of prior daytime sinus pause ≥3 s, anytime sinus pause ≥6 s, complete heart block, and a composite end point demonstrated an area under the receiver operating characteristic curve of 0.89, 0.87, 0.93, and 0.89, respectively, with negative predictive values between 97.9 and 99.9%. In addition to this approach of uncovering past events, our model was also tested for its ability to predict bradyarrhythmias within the following 13 days using the first 24 hours of ECG data, achieving an AUC of 0.88 for the composite end point. CONCLUSIONS:A deep learning-enabled ambulatory ECG is capable of unmasking underlying conduction tissue system disease. This tool may help identify patients with significant intermittent bradyarrhythmia, potentially improving timely diagnosis and management.

BACKGROUND AND AIMS:Accurate near-term prediction of life-threatening ventricular arrhythmias would enable pre-emptive actions to prevent sudden cardiac arrest/death. A deep learning-enabled single-lead ambulatory electrocardiogram (ECG) may identify an ECG profile of individuals at imminent risk of sustained ventricular tachycardia (VT). METHODS:This retrospective study included 247 254, 14 day ambulatory ECG recordings from six countries. The first 24 h were used to identify patients likely to experience sustained VT occurrence (primary outcome) in the subsequent 13 days using a deep learning-based model. The development set consisted of 183 177 recordings. Performance was evaluated using internal (n = 43 580) and external (n = 20 497) validation data sets. Saliency mapping visualized features influencing the model's risk predictions. RESULTS:Among all recordings, 1104 (.5%) had sustained ventricular arrhythmias. In both the internal and external validation sets, the model achieved an area under the receiver operating characteristic curve of .957 [95% confidence interval (CI) .943-.971] and .948 (95% CI .926-.967). For a specificity fixed at 97.0%, the sensitivity reached 70.6% and 66.1% in the internal and external validation sets, respectively. The model accurately predicted future VT occurrence of recordings with rapid sustained VT (≥180 b.p.m.) in 80.7% and 81.1%, respectively, and 90.0% of VT that degenerated into ventricular fibrillation. Saliency maps suggested the role of premature ventricular complex burden and early depolarization time as predictors for VT. CONCLUSIONS:A novel deep learning model utilizing dynamic single-lead ambulatory ECGs accurately identifies patients at near-term risk of ventricular arrhythmias. It also uncovers an early depolarization pattern as a potential determinant of ventricular arrhythmias events.

Background: Patient characteristics, technology and clinical practice surrounding primary prevention implantable cardioverter defibrillators have evolved continuously over time. Aim: To explore the temporal changes in patient characteristics, pharmacological therapy and device types among implantable cardioverter defibrillator recipients implanted for the primary prevention of sudden cardiac death over the last two decades in France. Methods: Characteristics of participants and type of device from the retrospective DAI-PP Pilot Study (2002-2012) were compared with those from the ongoing prospective DAI-PP Consortium (2018 onwards). Results: This study included 9588 participants overall (DAI-PP Pilot Study, n = 5539; DAI-PP Consortium, n = 4049). Compared with the DAI-PP Pilot Study, the DAI-PP Consortium subjects were older at implantation (62.5 vs 65.2 years; P = 0.001) and had a higher proportion of women (15.1% vs 20.6%; P < 0.001), a similar proportion of ischaemic heart disease (60.2% vs 60.2%; P = 0.98), a higher left ventricular ejection fraction (27 +/- 7% vs 30 +/- 8%; P < 0.001) and more patients with narrow QRS complexes (30.5% vs 46.0%; P < 0.001). The proportion of patients treated with heart failure drugs increased significantly (70.1% vs 83.1%; P < 0.001), whereas the use of amiodarone became much less frequent (22.7% vs 14.7%; P < 0.001). Finally, the proportions of cardiac resynchronization therapy defibrillators (53.8% vs 46.4%; P < 0.001) and dual-chamber defibrillators (23.3% vs 17.3%; P < 0.001) decreased, whereas subcutaneous implantable cardioverter defibrillators now account for a sizeable proportion of implants (14.6%). Conclusions: Over a 20-year period, the primary prevention implantable cardioverter defibrillator population has evolved significantly, with an older age and a higher proportion of women. The type of device has changed, with fewer cardiac resynchronization therapy defibrillators and more subcutaneous implantable cardioverter defibrillators. (c) 2025 Published by Elsevier Masson SAS.

The use of artificial intelligence (AI) in medical science has seen a rapid evolution, especially in the last few years. The use of AI in the field of arrhythmias and sudden cardiac death is especially relevant given the need for urgent, accurate decision-making in these clinical scenarios. AI and machine learning have heralded a new era in improving the precision and automation of diagnosis in arrhythmias ranging from ventricular tachycardia, atrial fibrillation, and bradyarrhythmias. However, the rapid pace of developments in this field also calls for caution in ensuring that progress is based on sound scientific evidence. This paper provides an overview of the basics of AI for clinicians and considers some key applications of AI in the field of arrhythmias through illustrative case examples.

ABSTRACT Narrow QRS complex tachycardia (NCT) refers to a heart rate more than 100 bpm with a QRS duration of <120 ms. Most NCTs are supraventricular tachycardias (SVTs) with only rare instances of ventricular tachycardia. Understanding the mechanisms of SVT is crucial for the diagnosis and management. Regular NCTs include sinus tachycardia, atrioventricular (AV) nodal reentrant tachycardia, AV reentrant tachycardia atrial tachycardia (AT), and atrial flutter (AFL) with fixed conduction. Irregular NCTs encompass atrial fibrillation, AT, and AFL with variable AV block. Key features for analyzing NCT include the regularity of the rhythm, the relationship between P waves and QRS complexes, the RP interval, the morphology of the P wave, the mode of initiation and termination of the tachycardia, and the response to vagal maneuvers or adenosine. In this review, we outline a systematic approach to electrocardiogram diagnosis of the NCT.

Ganesan Karthikeyan, DM; Mpiko Ntsekhe, PhD; Shofiqul Islam, PhD; Sumathy Rangarajan, MSc; Alvaro Avezum, PhD; Alexander Benz, MD; Tantchou Tchoumi Jacques Cabral, PhD; Ma Changsheng, MD; Philly Chillo, MD; J. Antonio Gonzalez-Hermosillo, MD; Bernard Gitura, MMed; Albertino Damasceno, PhD; Antonio Miguel L. Dans, MD; Kairat Davletov, MD; Alaa Elghamrawy, MD; Ahmed ElSayed, MD; Golden Tafadzwa Fana, MMed; Lillian Gondwe, MBBS; Abraham Haileamlak, MD; Azhar Mahmood Kayani, MD; Peter Lwabi, MMed; Fathi Maklady, MD; Onkabetse Julia Molefe-Baikai, MMed; John Musuku, MMed; Okechukwu Samuel Ogah, PhD; Maria Paniagua, MD; Emmanuel Rusingiza, MD; Sanjib Kumar Sharma, DM; Liesl Zuhlke, PhD; Stuart Connolly, MD; Salim Yusuf, DPhil; INVICTUS Investigators; Monkgogi Goepamang; Julius Mwita; Auristela Ramos; Flavio Tarasoutchi; Milena Ribeiro Paixao; Marcelo Kirschbaum; Mariana Pezzute Lopes; Walkiria Avila; Lilia Maia; Marcelo Nakazone; Osana Costa; Maria Lemos; Livia Oliveira; Jose Ferreira; Jose Francisco Kerr Saraiva; Midia Costa; Marina Marengo; Oscar Dutra; Raphael Guimaraes; Humberto Vaz; Sergio Luiz Zimmerman; Weimar Souza; Weimar Queiroz; Adriana Souza; Maria Helena Vidotti; Jose Guilherme de Paula; Guilherme Fazolli; Mauro Hernandes ; Jose Luiz Torati; Grazielly Pantano; Vanessa Pelarin; Flavia Arantes; Rodrigo Silva; Monique Cardoso; Gilmar Reis; Cesar Franca; Tulio Quadros; Flavio Giorgeto; Resende Elmiro; Silva Aguinaldo; Cesar Minelli; Helen Mbuoh Anshoma; Jean Claude Ambassa; Liliane Mfevkev Kuate; Chris Nadege Nganou Gninotio; Ngo Youmba Ntep Gweth; Dzudie Anastase; Djomou Ngongang Florent Armel; Lionel Nana Keptukoua; Xin Du; Rong Hu; Jiahui Wu; Qiang Lv; Jing Cui; Yu Qing; Zhu Xudong; Wei Su; Wang Xiaomei; Chen Shiyi; Zhang Zhipeng; Qi Wang; Xin Zheng; Liu Pengfei; Cheng Rang; Sitao Xie; Chongwen Liu; Hailong Wang ; Shudong Wang; Xuxia Zhang; Yinzhu Lian; Rui Wang; Ma Mingfu; Lan Dou Li ; Yunlian Tan; Shouyan Zhang; Gu Yunfei; Chen Jianfeng; Wang Hao; Wu Pengyu; Luan Hong; Li Fu; Xu Yongbin; Xiao Jundan; Li Qingfu; Jinpo Sun ; Cui Pei; Yanbo Niu; Yidi Wu; Honghua Yang; Xin Li; Chunyan Yang ; Yanhui Shi; Chenglin Wu; Yandong Qu ; Mingzhong Zhao; Yong Cheng; Yiqiang Yuan; Qiong Huang; Xiuzhen Kong; Zhizhong Zhao; Qixia Heng; Xinjing Shi; Jing Zhang; Liu Ying; Gao Xin; Zhaoping Yu; Xi Wu; Guo Hunayu; Wang Xiaoying; Wei Zhang; Chichang Li; Wang Zhongtao; Hao Ding; Min Huang; Zhao Jinguo; Mingshui Yu; Cuiling Cao; Xiaoli Zhu; Xiaoqin Shi; Khalid Eltamawy; Osama Arafa; Mahmoud Youssif; Aly Kassem; Omar Saleh; Mohamed Hussam Al Shair; Khaled Maghraby; Sameh Shaheen; Aly Ahmed Abouelhoda; Suliman Gharib; Ramadan Sadek; Yasser Abd El Hady; Elsah Asefa; Esayas Kebede Gudina; Ermias Habte Michael; Tadesse Dukessa Gemechu; Markos Duguma; Dejuma Yadeta; Berhanu N Alemu; Sintayehu Abebe; Tamrat Assefa; Desalew Mekonnen; Tigist Seleshi; Chala Fekadu; Abraha Hailu; Hagazi Tesfay; Berhane Yohannes Hailu; Hagos Kahsay; Kibreab Gidey; Teklay Gebrehawaria; Samuel Berhane; Teshome Abegaz Kamil; Tariku Egeno Shifa; Agete Tedewos Hirigo; Sisay Tesfaye Teshome; Seyife Kibru Yirdaw; Sandeep Singh; Nitish Naik; Deepti Siddharthan; Satyavir Yadav; Mohit Gupta; Girish MP; Ajay Sharma; Bhagya Narayan Pandit; Kumar Sudeep; Kapoor Aditya; Akshyaya Pradhan; Rishi Sethi; Gaurav Chaudhry; Yaday Virendra; Agarwal Smriti; Cholenahally Manjnath; Surya Prakash Narayanappa; Cholenahally Satvic; Lachikarthman Devegowda; Chandra Bhan Meena; Rajiv Bagarhatta; Shashi Mohan Sharma; Shekhar Kunal; Nutan Kumar; Alibek Mereke; Elijah Ogola; Wilson Sugut; Felix Barasa; Anthony Gikonyo; Stephen Omondi; Frank Sinyiza; John Chipolombwe; Tamara Phiri; Laura Leticia Rodriguez Chavez; Ernesto Gutierrez; Fransisco Mazon Flores; Edgar Rodriguez; Susano Lara Vaca; Juan Cabra; Sandra Saavedra; Manuel De los Rios; Gilmer Ruvalcaba; Esteban Lopez; Marco Alcocer; Ana Ramirez; Guillermo Llamas; Paola Hernandez; Angelica Delgado; Ana Muholove; Angela Mateus; Ana Mocumbi; Jyoti Agarwal; Roshan Chhetri; Prashant Mani Tripathi; Chandra Mani Adhikari; Urmila Shakya; Dipanker Prajapati; Reeju Manandhar; Rajesh Nepal; Sahadeb Prasad Dhungana; Rinku Ghimire; Sunil Babu Khanal; Samir Gautam; Mazhar Khan; Bishal KC; Shankar Laudari; Madhu Gupta; Shyam Raj Regmi; Bishnu Mani Dhital; Sudhir Regmi; Krishna Adhikari; Bhagawan Koirala; Ratnamani Gajurel; Hemant Shrestha; Sanjeev Thapa; ADESEYE AKINTUNDE; Taiwo Olunuga; Julius Adesina; Mahmoud Sani; Fidelia Bode-Thomas; Basil Okeahialam; Christopher Yilgwan; Ganiyu Amusa; Olukemi IGE; Solomon Danbauchi; Abiodun Moshood Adeoye; Ejiroghene Umuerri; Amam Mbakwem; Casmir Amadi; Oyewole Kushimo; Muhammad Isa; Muhammad Awwal Abdullahi; Nelson Oguanobi; Zohaib Ullah Zahid; Jabar Ali; Mohammad Hafizullah; Feroz Memon; Shazia Kazi; Azhar Mahmood Kayani; Adeel Rehman; Abdul Wajid Khan Faisal; Aftab Ahmad Tarique; Abdul Sattar; Nadeem Hayat Mallick; Syed Asif Ali; Veronica Mayans; Luciano Pereira; Jose Alderete; Javier Galeano; Alberto Moran Salinas; Rocío del Pilar Falcón; Gustavo Escalada; Luz Cabral; Liz Fatecha; Gladys Bogado de Atobe; Carlos Gutierrez; Cesar Delmas; Claudine Coronel; Dahiana Ibarrola; Jose Donato Magno; Lauren Kay Evangelista; Maria Teresa Abola; Leahdette Padua; Christie Mendoza-Reyes; Dennis Jose Sulit; Ma Jojo Mercado; Candy Angelica Sigua Cabaddu; Josefina Cruz; Jean Marie Vianney Ganza Gapira; Vincent Dusingizimana; Blanche Cupido; John Lawrenson; KISHENDREE NAICKER; JACQUELINE RACHELLE CIROTA; Sliwa Hahnle Karen; Mookenthottathil Thomas Baby; Kandathil Mathew Thomas; MOEKETSI KHULILE; Samuel Yao Alomatu; PINDILE MNTLA; MAKGOTSANE MPHAHLELE; Andrew Ratsela; Pravin Manga; Doné Fourie ; Allana Hemus; Ellen M Makotoko; A K M NOWSHAD ALAM; Richard Nethononda; Theema Nunkoo; Ruchika Meel; Elsadig Askar; Amna Elfaki; Lana Mohamed; Mohammed ElSayed; Alia Hagahmed; Sumia Mohammed; Hiba Algaali; Khalid Eltalib; Tagwa S. I. Badawe; Inas Hassab Elrasoul Kbashi; Huda Hamid Elhassan; Maysa Hamza; Molhim M.I. Ahmed ; Rayan Elhussain; Rufaida Mutwali; Mohammad Qurashi Ahmed Medani; Nazar F.A. Mohamed; Hwida A.M. Elamin; Manal H.A. Elmadih; Maha Abdelgader; Magdi (Gameel) Yousif; Tagwa Elfatih; Osama Hafiz Elshazali; Elaf Esmaeel Esawi; Awad A.M.A. Mohammed; Omer I.A. Hassan; Khansa Mahgoub; Maarib Maki; Omaima A.M.Abozaid; Naiz Majani; Emmanuel Stephano Mtullo; Clement Kabakama; Issakwisa Mwakyula; John Meda; Emmy Okello; Pamela Chansa; Ngosa Mumba; Fastone Goma; Caroline Musemwa; Rudo Gwini

BACKGROUND Electrocardiographic screening before subcutaneous implantable cardioverter-defibrillator (S-ICD) implantation is unsuccessful in around 10% of cases. A personalized screening method, by slightly moving the electrodes, to obtain a better R/T ratio has been described to overcome traditional screening failure. OBJECTIVE The objectives of the SIS study were to assess to what extent a personalized screening method improves eligibility for S-ICD implantation and to evaluate the inappropriate shock rate after such screening success. METHODS All consecutive patients eligible for an S-ICD implantation were prospectively recruited across 20 French centers between December 2019 and January 2022. In case of traditional screening failure, patients received a second personalized screening. If at least 1 vector was positive, the personalized screening was considered successful, and the patient was eligible for implantation. RESULTS The study included 474 patients (mean age, 50.4 6 14.1 years; 77.4% men). Traditional screening was successful in 456 (96.2%) cases. This fi gure rose to 98.3% (n = 466; P = . 002) when personalized screening was performed. All patients implanted after successful personalized screening had correct signal detection on initial device interrogation. Nevertheless, after 1year follow-up, 3 of the 7 patients (43%) implanted with personalized screening experienced inappropriate shock vs 18 of the 427 patients (4.2%) with traditional screening and S-ICD implantation (P = . 003). CONCLUSION Traditional S-ICD screening was successful in our study in a high proportion of patients. Considering the small improvement in success of screening and a higher rate of inappropriate shock, a strategy of personalized screening cannot be routinely recommended.