ReviewAPL bioengineering2020
Quantification and classification of potassium and calcium disorders with the electrocardiogram: What do clinical studies, modeling, and reconstruction tell us?
Review in APL bioengineering, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 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.
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Who cites it
7 citing papers in PubMed.
- Review
- The effect of clinically relevant changes in extracellular electrolyte concentrations on human atrial arrhythmias.Communications medicine · 2025Article
- Computational modelling of biological systems now and then: revisiting tools and visions from the beginning of the century.Philosophical transactions. Series A, Mathematical, physical, and engineering sciences · 2025Review
- MedalCare-XL: 16,900 healthy and pathological synthetic 12 lead ECGs from electrophysiological simulations.Scientific data · 2023Article
- Differences in ventricular wall composition may explain inter-patient variability in the ECG response to variations in serum potassium and calcium.Frontiers in physiology · 2023Article
- Monitoring of Serum Potassium and Calcium Levels in End-Stage Renal Disease Patients by ECG Depolarization Morphology Analysis.Sensors (Basel, Switzerland) · 2022Article
- Incorporating structural abnormalities in equivalent dipole layer based ECG simulations.Frontiers in physiology · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Diseases caused by alterations of ionic concentrations are frequently observed challenges and play an important role in clinical practice. The clinically established method for the diagnosis of electrolyte concentration imbalance is blood tests. A rapid and non-invasive point-of-care method is yet needed. The electrocardiogram (ECG) could meet this need and becomes an established diagnostic tool allowing home monitoring of the electrolyte concentration also by wearable devices. In this review, we present the current state of potassium and calcium concentration monitoring using the ECG and summarize results from previous work. Selected clinical studies are presented, supporting or questioning the use of the ECG for the monitoring of electrolyte concentration imbalances. Differences in the findings from automatic monitoring studies are discussed, and current studies utilizing machine learning are presented demonstrating the potential of the deep learning approach. Furthermore, we demonstrate the potential of computational modeling approaches to gain insight into the mechanisms of relevant clinical findings and as a tool to obtain synthetic data for methodical improvements in monitoring approaches.
Identifiers
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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.