ArticleMayo Clinic proceedings2021
Artificial Intelligence-Augmented Electrocardiogram Detection of Left Ventricular Systolic Dysfunction in the General Population.
Article in Mayo Clinic proceedings, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers, 1 of them a synthesis that pooled it.
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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.
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Who cites it
31 citing papers in PubMed, 1 synthesis or guideline pooled it, 57 citations in OpenAlex.
- Artificial intelligence enabled ECG screening for left ventricular systolic dysfunction: a systematic review.Heart failure reviews · 2023Pooled it
- TEERAI-Pre: A Multiview Artificial Intelligence Model for Preoperative Assessment of Transcatheter Edge-to-Edge Mitral Valve Repair Using Multiview, Multimodal Echocardiography.Journal of the American Heart Association · 2026Trial
- Trial
- External validation of artificial intelligence-guided electrocardiogram (AI-ECG) in detecting asymptomatic left ventricular dysfunction: A systematic review and meta-analysis.American journal of preventive cardiology · 2027Article
- Deep Learning Applied to 12-Lead ECGs for Detection of Structural, Metabolic and Systemic Disease.Diagnostics (Basel, Switzerland) · 2026Review
- An artificial intelligence model to detect abnormal ejection fraction from non-contrast chest computed tomography: the CT-LVEF study.European heart journal. Digital health · 2026Article
- Smarter FoCUS: AI-guided focused cardiac ultrasound enables novice detection of left ventricular dysfunction.European heart journal. Digital health · 2026Article
- Heart failure detection in electrocardiograms using artificial intelligence and pragmatic labelling.NPJ digital medicine · 2026Article
- Artificial Intelligence-Driven Electrocardiogram Screening for Asymptomatic Left Ventricular Systolic Dysfunction in the General Population.JACC. Advances · 2026Article
- Development and temporal validation of a two-stage ECG-based machine learning model for LVEF screening: a Middle Eastern cohort study.BMC cardiovascular disorders · 2026Article
- Artificial Intelligence-enhanced Electrocardiography for Heart Failure Screening and Risk Stratification.Current heart failure reports · 2026Review
- Validation of AI-enhanced ECG image analysis for identifying extreme cardiac magnetic resonance metrics in a cross-ethnic UK biobank study.Scientific reports · 2026Article
- Structural heart disease screening using artificial intelligence-enabled electrocardiogram and novice handheld cardiac ultrasound: a cost analysis.European heart journal open · 2026Article
- Deep learning to predict left ventricular hypertrophy from the electrocardiogram.Europace : European pacing, arrhythmias, and cardiac electrophysiology : journal of the working groups on cardiac pacing, arrhythmias, and cardiac cellular electrophysiology of the European Society of Cardiology · 2026Article
- Prognostic Value of Artificial Intelligence-Enabled Electrocardiography-Derived Diastolic Dysfunction Grading and Trajectory in Patients Undergoing Transcatheter Aortic Valve Replacement.Journal of the American Heart Association · 2026Article
- A Screening Method for Determining Left Ventricular Systolic Function Based on Spectral Analysis of a Single-Channel Electrocardiogram Using Machine Learning Algorithms.Diagnostics (Basel, Switzerland) · 2026Article
- Enhanced prediction of left ventricular ejection fraction using electrocardiography with the addition of clinical metadata.The Korean journal of internal medicine · 2026Article
- [AI-enabled clinical decision support systems: challenges and opportunities].Bundesgesundheitsblatt, Gesundheitsforschung, Gesundheitsschutz · 2025Review
- Artificial intelligence in ECG-based diagnosis of low left ventricular ejection fraction: a systematic review and meta-analysis.Biomedical engineering letters · 2025Review
- An Artificial Intelligence Algorithm for Early Detection of Left Ventricular Systolic Dysfunction in Patients with Normal Sinus Rhythm.Journal of clinical medicine · 2025Article
Corrections and comments
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Authors and funding
11 authors at 2 institutions in 1 country.
Funding
Abstract
objectiveTo validate an artificial intelligence-augmented electrocardiogram (AI-ECG) algorithm for the detection of preclinical left ventricular systolic dysfunction (LVSD) in a large community-based cohort.
methodsWe identified a randomly selected community-based cohort of 2041 subjects age 45 years or older in Olmsted County, Minnesota. All participants underwent a study echocardiogram and ECG. We first assessed the performance of the AI-ECG to identify LVSD (ejection fraction ≤40%). After excluding participants with clinical heart failure, we further assessed the AI-ECG to detect preclinical LVSD among all patients (n=1996) and in a high-risk subgroup (n=1348). Next we modelled an imputed screening program for preclinical LVSD detection where a positive AI-ECG triggered an echocardiogram. Finally, we assessed the ability of the AI-ECG to predict future LVSD. Participants were enrolled between January 1, 1997, and September 30, 2000; and LVSD surveillance was performed for 10 years after enrollment.
resultsFor detection of LVSD in the total population (prevalence, 2.0%), the area under the receiver operating curve for AI-ECG was 0.97 (sensitivity, 90%; specificity, 92%); in the high-risk subgroup (prevalence 2.7%), the area under the curve was 0.97 (sensitivity, 92%; specificity, 93%). In an imputed screening program, identification of one preclinical LSVD case would require 88.3 AI-ECGs and 8.7 echocardiograms in the total population and 65.7 AI-ECGs and 5.5 echocardiograms in the high-risk subgroup. The unadjusted hazard ratio for a positive AI-ECG for incident LVSD over 10 years was 2.31 (95% CI, 1.32 to 4.05; P=.004).
conclusionArtificial intelligence-augmented ECG can identify preclinical LVSD in the community and warrants further study as a screening tool for preclinical LVSD.
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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.