ArticleJournal of electrocardiology
Population-based beat-to-beat QT analysis from Holter recordings in the long QT syndrome.
Article in Journal of electrocardiology. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed.
- Holter Recordings at Initial Assessment for Long QT Syndrome: Relationship to Genotype Status and Cardiac Events.Journal of cardiovascular development and disease · 2022Article
- QT Assessment in Early Drug Development: The Long and the Short of It.International journal of molecular sciences · 2019Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
The increasing dissemination of wearable ECG recorders (e.g. Holter, patches, and strap sensors) enables the acquisition of large amounts of data during long periods of time. However, the clinical value of these long-term continuous recordings is hindered by the lack of automatic tools to extract clinically relevant information (other than non-sinus and life-threatening rhythms) from such long-term data, particularly when targeting population-based research. In this work, we propose and test a new tool for analyzing beat-to-beat interval measurements and extracting features from Holter ECGs. Specifically, we assess the adaptation of the QT interval following sudden changes in heart rate in the primary long QT types (1 & 2). We find that in long QT syndrome type 2, certain QT adaptation patterns can indicate a higher risk for cardiac events.
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Registered trials
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