Objectives: Deep brain stimulation (DBS) is known to interfere with electrocardiographic (ECG) examinations. In emergency situations, such electrical interferences can not only thwart ECG diagnostics, but even induce an ECG pattern that causes the emergency medical service to initiate inadequate or even harmful therapy. Aim of this prospective study was to evaluate factors influencing ECG interpretation in DBS and to evaluate the susceptibility of ECG criteria 'frequency', 'rhythm', 'regularity', 'QRS-configuration', and 'ST-segment' on neurostimulation.
Patients And Methods: In 33 DBS patients (17 male, 16 female, mean age 64 years), limb-, 12 channel-, Nehb, and adhesive paddle-lead ECG were performed in activated (n = 33) and deactivated (n = 31) stimulation mode during outpatient follow-up examinations. The examinations were carried out using three different ECG devices (two portable emergency ECG-monitor/defibrillation/pacer-devices, one stationary hospital device), resulting in 4096 ECG leads. Statistics have been based on regression analyses and on a maximum likelihood estimation regression model.
Results: Monopolar settings were found to be a relevant factor interfering significantly more often with ECG recording than bipolar parameters (p < 0.0001). Due to recurring movement artefacts, deactivation of bipolar stimulation might even significantly worsen ECG quality (p < 0.0001). Interpretability of 'rhythm' (β = -0.088, p = 0.03) and 'frequency' (β = -0.110, p = 0.02) revealed significant negative correlation to the applied neurostimulation voltage. Nehb lead yielded in highest ECG interpretability.
Conclusion: Bipolar neurostimulation mode barely affected the ECGs; furthermore, the suppression of motion artefacts by neurostimulation can improve ECG quality. If monopolar neurostimulation is required, at least, stimulation voltage should be as low as possible to obtain good stimulation results.
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http://dx.doi.org/10.1016/j.clineuro.2021.106557 | DOI Listing |
Europace
December 2024
Translational Cardiology, Department of Cardiology and Department of Physiology, Inselspital University Hospital Bern, University of Bern, 3012 Bern, Switzerland.
Europace
December 2024
Gottfried Schatz Research Center, Division of Medical Physics and Biophysics, Medical University of Graz, Graz, Austria.
In 1924, the Dutch physiologist Willem Einthoven received the Nobel Prize in Physiology or Medicine for his discovery of the mechanism of the electrocardiogram (ECG). Anno 2024, the ECG is commonly used as a diagnostic tool in cardiology. In the paper 'Le Télécardiogramme', Einthoven described the first recording of the now most common cardiac arrhythmia: atrial fibrillation (AF).
View Article and Find Full Text PDFPediatr Rep
December 2024
Department of Pediatric Neurology, Queen Rania Children's Hospital, Royal Medical Services, Amman 11118, Jordan.
Background/objectives: Routine screening electrocardiograms (ECGs) prior to starting medications for attention-deficit/hyperactivity disorder (ADHD) remain controversial. This real-world study assessed corrected QT (QTc) interval data from pediatric patients who had a baseline ECG performed prior to initiating treatment with ADHD medications and ≥6 months of clinical follow-up.
Methods: A retrospective chart review of children aged 2-18 years diagnosed with ADHD with/without autism spectrum disorder (ASD) at child neurology clinics in Jordan (June 2019 and June 2021) was performed, and children were prescribed with ADHD medications to manage symptoms.
J Cardiovasc Dev Dis
December 2024
Cardiovascular Section, Department of Internal Medicine, Wake Forest University School of Medicine, Winston-Salem, NC 27101, USA.
: Fatal coronary heart disease (FCHD) affects ~650,000 people yearly in the US. Electrocardiographic artificial intelligence (ECG-AI) models can predict adverse coronary events, yet their application to FCHD is understudied. : The study aimed to develop ECG-AI models predicting FCHD risk from ECGs.
View Article and Find Full Text PDFBiosensors (Basel)
December 2024
Corsano Health B.V., Wilhelmina van Pruisenweg 35, 2595 AN The Hague, The Netherlands.
Monitoring respiration rate (RR) is crucial in various healthcare settings, particularly during demanding (physical) activities where respiratory dynamics are critical indicators of health status. This study aimed to evaluate the accuracy of photoplethysmography (PPG)-based monitoring of RR during high-intensity interval training (HIIT) and its potential applications in healthcare. Between January and March 2024, healthy volunteers participated in a cycling HIIT session with increasing resistance levels.
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