ReviewHerzschrittmachertherapie & Elektrophysiologie2024
[Digital precision medicine in rhythmology : Risk prediction of recurrences, sudden cardiac death, and outcome].
Review in Herzschrittmachertherapie & Elektrophysiologie, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
5 citing papers in PubMed, 3 citations in OpenAlex.
- Integrating AI-Driven Diagnostics in Arrhythmia Care to Enhance Patient Outcomes: A Narrative Review.Cureus · 2026Review
- Artificial intelligence for patient selection in pulsed-field ablation: promise, pragmatism, and the need for standards.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
- [Clinician and medical scientists in internal medicine: cardiology].Innere Medizin (Heidelberg, Germany) · 2026Review
- Smartphone app-based approximation of time spent with atrial fibrillation and symptoms in patients after catheter ablation: data from the TeleCheck-AF project.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 · 2024Article
- [eCardiology in cardiac electrophysiology].Herzschrittmachertherapie & Elektrophysiologie · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Digital precision medicine is gaining increasing importance in rhythmology, especially in the treatment of cardiac arrhythmias. This trend is driven by the advancing digitization in healthcare and the availability of large amounts of data from various sources such as electrocardiograms (ECGs), implants like pacemakers and implantable cardioverter-defibrillators (ICDs), as well as wearables like smartwatches and fitness trackers. Through the analysis of this data, physicians can develop more precise and individualized diagnoses and treatment strategies for patients with cardiac arrhythmias. For example, subtle changes in ECGs can be identified, indicating potentially dangerous arrhythmias. Genetic analyses and resulting large datasets also play an increasingly significant role, especially in hereditary ion channel disorders such as long QT syndrome (LQTS) and Brugada syndrome (BrS), as well as in lone atrial fibrillation (AF). Precision medicine enables the development of individualized treatment approaches tailored to the specific needs and risk factors of each patient. This can help improve screening strategies, reduce adverse events, and ultimately enhance the quality of life for patients. Technological advancements such as big data, artificial intelligence, machine learning, and predictive analytics play a crucial role in predicting the risk of arrhythmias and sudden cardiac death. These concepts enable more precise and personalized predictions and support physicians in the treatment and monitoring of their patients.
Indexed as
Identifiers
What OpenQuestion holds
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.