ArticleHeart rhythm2020
Eligibility for subcutaneous implantable cardioverter-defibrillator in congenital heart disease.
Article in Heart rhythm, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT03209726 (Assessment of Subcutaneous Implantable Cardioverter Defibrillator Eligibility With 12-lead Electrocardiogram), which is not on this map. Cited by 17 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Assessment of Subcutaneous Implantable Cardioverter Defibrillator Eligibility With 12-lead Electrocardiogram
Who cites it
17 citing papers in PubMed, 33 citations in OpenAlex.
- Response to cardiac resynchronisation therapy in men and women: a secondary analysis of the SMART-AV randomised controlled trial.BMJ open · 2021Trial
- Repaired tetralogy of Fallot across adulthood: from right ventricular remodelling to targeted intervention.Heart failure reviews · 2026Review
- [Consensus recommendation of the Austrian Society of Cardiology: anatomy, pathophysiology, diagnosis and treatment of arrhythmias in adult patients with congenital heart disease].Wiener klinische Wochenschrift · 2026Review
- Advancements in pacing and ICD technologies: Potential implications for complex congenital heart disease in adults.International journal of cardiology. Congenital heart disease · 2026Review
- Significance of 3-dimensional cardiac anatomical axis as the predictor of low QRS amplitude of subcutaneous implantable cardioverter-defibrillator.Heart rhythm O2 · 2025Article
- Deep learning-based insights on T:R ratio behaviour during prolonged screening for S-ICD eligibility.Journal of interventional cardiac electrophysiology : an international journal of arrhythmias and pacing · 2025Article
- Medical Therapy for Heart Failure in Adult Congenital Heart Disease Patients.Structural heart : the journal of the Heart Team · 2024Review
- Comparison of Preoperative ECG Screening and Device-Based Vector Analysis in Patients Receiving a Subcutaneous Implantable Cardioverter-Defibrillator.Medicina (Kaunas, Lithuania) · 2023Article
- Risk Stratification for Sudden Cardiac Death in Repaired Tetralogy of Fallot.CJC pediatric and congenital heart disease · 2023Review
- The Lifelong Impact of Artificial Intelligence and Clinical Prediction Models on Patients With Tetralogy of Fallot.CJC pediatric and congenital heart disease · 2023Review
- S-ICD Implantation "Tips and Tricks".Reviews in cardiovascular medicine · 2023Review
- Sudden cardiac death in adults with congenital heart disease: Lessons to Learn from the ATROPOS registry.International journal of cardiology. Congenital heart disease · 2022Review
- Digitizing ECG image: A new method and open-source software code.Computer methods and programs in biomedicine · 2022Article
- The role of machine learning applications in diagnosing and assessing critical and non-critical CHD: a scoping review.Cardiology in the young · 2021Article
- Author reply: S-ICD eligibilities in adults with congenital heart disease.ESC heart failure · 2021Article
- To the editor: S-ICD eligibility in adult congenital heart disease.ESC heart failure · 2021Article
- Using artificial intelligence and deep learning to optimise the selection of adult congenital heart disease patients in S-ICD screening.Indian pacing and electrophysiology journalArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 1 institution in 1 country.
Funding
Abstract
backgroundAdult congenital heart disease (ACHD) patients can benefit from a subcutaneous implantable cardioverter-defibrillator (S-ICD).
objectiveThe purpose of this study was to assess left- and right-sided S-ICD eligibility in ACHD patients, use machine learning to predict S-ICD eligibility in ACHD patients, and transform 12-lead electrocardiogram (ECG) to S-ICD 3-lead ECG, and vice versa.
methodsACHD outpatients (n = 101; age 42 ± 14 years; 52% female; 85% white; left ventricular ejection fraction [LVEF] 56% ± 9%) were enrolled in a prospective study. Supine and standing 12-lead ECG were recorded simultaneously with a right- and left-sided S-ICD 3-lead ECG. Peak-to-peak QRS and T amplitudes; RR, PR, QT, QTc, and QRS intervals; Tmax, and R/Tmax (31 predictor variables) were tested. Model selection, training, and testing were performed using supine ECG datasets. Validation was performed using standing ECG datasets and an out-of-sample non-ACHD population (n = 68; age 54 ± 16 years; 54% female; 94% white; LVEF 61% ± 8%).
resultsForty percent of participants were ineligible for S-ICD. Tetralogy of Fallot patients passed right-sided screening (57%) more often than left-sided screening (21%; McNemar χ
conclusionNearly half of the contemporary ACHD population is ineligible for S-ICD. The odds of S-ICD eligibility are greater for female than for male ACHD patients. Machine learning prediction of S-ICD eligibility can be used for screening of S-ICD candidates.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.