This consensus guideline discusses the electrocardiographic phenomenon of beat-to-beat QT interval variability (QTV) on surface electrocardiograms. The text covers measurement principles, physiological basis, and clinical value of QTV. Technical considerations include QT interval measurement and the relation between QTV and heart rate variability. Research frontiers of QTV include understanding of QTV physiology, systematic evaluation of the link between QTV and direct measures of neural activity, modelling of the QTV dependence on the variability of other physiological variables, distinction between QTV and general T wave shape variability, and assessing of the QTV utility for guiding therapy. Increased QTV appears to be a risk marker of arrhythmic and cardiovascular death. It remains to be established whether it can guide therapy alone or in combination with other risk factors. QT interval variability has a possible role in non-invasive assessment of tonic sympathetic activity.
Epidemiologic studies report associations between particulate air pollution and cardiovascular morbidity and mortality, but the underlying pathophysiologic mechanisms are still unclear. We tested the hypothesis that patients with preexisting coronary heart disease experience changes in the repolarization parameters in association with rising concentrations of air pollution. A prospective panel study was conducted in Erfurt, East Germany, with 12 repeated electrocardiogram (ECG) recordings in 56 males with ischemic heart disease. Hourly particulate and gaseous air pollution and meteorologic data were acquired. The following ECG parameters reflecting myocardial substrate and vulnerability were measured: QT duration, T-wave amplitude, T-wave complexity, and variability of T-wave complexity. Fixed effect regression analysis was used adjusting for subject, trend, weekday, and meteorology. The analysis showed a significant increase in QT duration in response to exposure to organic carbon; a significant decrease in T-wave amplitude with exposure to ultrafine, accumulation mode, and PM2.5 particles (particles < 2.5 μm in aerodynamic diameter); and a corresponding significant increase of T-wave complexity in association with PM2.5 particles for the 24 hr before ECG recordings. Variability of T-wave complexity showed a significant increase with organic and elemental carbon in the same time interval. This study provides evidence suggesting an immediate effect of air pollution on repolarization duration, morphology, and variability representing myocardial substrate and vulnerability, key factors in the mechanisms of cardiac death.
Background and ObjectiveExposure to ambient particles has been shown to be responsible for cardiovascular effects, especially in elderly with cardiovascular disease. The study assessed the association between deceleration capacity (DC) as well as heart rate variability (HRV) and ambient particulate matter (PM) in patients with coronary artery disease (CAD).MethodsA prospective study with up to 12 repeated measurements was conducted in Erfurt, Germany, between October 2000 and April 2001 in 56 patients with physician-diagnosed ischemic heart disease, stable angina pectoris or prior myocardial infarction at an age of at least 50 years. Twenty-minute ECG recordings were obtained every two weeks and 24-hour ECG recordings every four weeks. Exposure to PM (size range from 10 nm to 2.5 μm), and elemental (EC) and organic (OC) carbon was measured. Additive mixed models were used to analyze the association between PM and ECG recordings.ResultsThe short-term recordings showed decrements in the high-frequency component of HRV as well as in RMSSD (root-mean-square of successive differences of NN intervals) in association with increments in EC and OC 0-23 hours prior to the recordings. The long-term recordings revealed decreased RMSSD and pNN50 (% of adjacent NN intervals that differed more than 50 ms) in association with EC and OC 24-47 hours prior to the recordings. In addition, highly significant effects were found for DC which decreased in association with PM2.5, EC and OC concurrent with the ECG recordings as well as with a lag of up to 47 hours.ConclusionsThe analysis showed significant effects of ambient particulate air pollution on DC and HRV parameters reflecting parasympathetic modulation of the heart in patients with CAD. An air pollution-related decrease in parasympathetic tone as well as impaired heart rate deceleration capacity may contribute to an increased risk for cardiac morbidity and sudden cardiac death in vulnerable populations.
Epidemiological studies associate ambient particulate pollution with adverse health outcomes in elderly individuals with cardiopulmonary diseases. We hypothesized that freshly generated ultrafine particles (UFP) contribute to these effects, as they are present in high number concentrations on highways and vehicle passengers are exposed directly to them. Aged spontaneously hypertensive rats (9-12 mo) with implanted radiotelemetry devices were exposed to highway aerosol or filtered, gas-denuded (clean) air using an on-road exposure system to examine effects on heart rate (HR) and heart-rate variability (HRV). On the day of exposure, rats were pretreated with low-dose inhaled or injected lipopolysaccharide (LPS) to simulate respiratory tract or systemic inflammation, respectively. Exposures (6 h) in compartmentalized whole-body chambers were performed in an air conditioned compartment of a mobile laboratory on I-90 between Rochester and Buffalo, NY. HRV parameters were calculated from telemetric blood pressure signals and analyzed for the baseline period and for the first 32 h postexposure. The aerosol size (count median diameter = 15-20 nm; geometric standard deviation = 1.4-4.3) and number concentration (1.95-5.62 x 105/cm3) indicated the predominance of UFP. Intraperitoneal LPS significantly affected all of the parameters in a time-dependent manner; response patterns after inhaled or injected LPS pretreatment were similar, but more prolonged and greater in LPS-injected rats. A significant effect of highway aerosol was found, irrespective of pretreatment, which resulted in decreased HR in comparison to clean air-exposed rats. This effect was more persistent ( approximately 14 h) in those rats that received ip LPS as compared to saline. The highway aerosol also significantly affected short-term alterations in autonomic control of HR, as evidenced by elevations in normalized high frequency power and decreased vagosympathetic balance. These findings show that environmental exposure concentrations of mixed traffic-related UFP/gas-phase emissions can affect the autonomic nervous system.
Long QT syndrome (LQTS) is an inherited disorder associated with prolongation of the QT/QTc interval on the surface electrocardiogram (ECG) and a markedly increased risk of sudden cardiac death due to cardiac arrhythmias. Up to 25% of genotype-positive LQTS patients have QT/QTc intervals in the normal range. These patients are, however, still at increased risk of life-threatening events compared to their genotype-negative siblings. Previous studies have shown that analysis of T-wave morphology may enhance discrimination between control and LQTS patients. In this study we tested the hypothesis that automated analysis of T-wave morphology from Holter ECG recordings could distinguish between control and LQTS patients with QTc values in the range 400-450 ms. Holter ECGs were obtained from the Telemetric and Holter ECG Warehouse (THEW) database. Frequency binned averaged ECG waveforms were obtained and extracted T-waves were fitted with a combination of 3 sigmoid functions (upslope, downslope and switch) or two 9th order polynomial functions (upslope and downslope). Neural network classifiers, based on parameters obtained from the sigmoid or polynomial fits to the 1 Hz and 1.3 Hz ECG waveforms, were able to achieve up to 92% discrimination between control and LQTS patients and 88% discrimination between LQTS1 and LQTS2 patients. When we analysed a subgroup of subjects with normal QT intervals (400-450 ms, 67 controls and 61 LQTS), T-wave morphology based parameters enabled 90% discrimination between control and LQTS patients, compared to only 71% when the groups were classified based on QTc alone. In summary, our Holter ECG analysis algorithms demonstrate the feasibility of using automated analysis of T-wave morphology to distinguish LQTS patients, even those with normal QTc, from healthy controls.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.