scholarly journals Association between physical performance and electrocardiographic heart rate corrected-QT interval in elderly subjects

2013 ◽  
Vol 62 (4) ◽  
pp. 283-291 ◽  
Author(s):  
Ryoma Michishita ◽  
Chika Fukae ◽  
Rikako Mihara ◽  
Masahiro Ikenaga ◽  
Kazuhiro Morimura ◽  
...  
Keyword(s):  
Heart Rate ◽  
Physical Performance ◽  
Qt Interval ◽  
Elderly Subjects ◽  
Corrected Qt Interval

scholarly journals Influence of Dietary Sodium and Potassium Intake on the Heart Rate Corrected-QT Interval in Elderly Subjects

2015 ◽  
Vol 61 (2) ◽  
pp. 138-146 ◽  
Author(s):  
Ryoma MICHISHITA ◽  
Kazuko ISHIKAWA-TAKATA ◽  
Eiichi YOSHIMURA ◽  
Rikako MIHARA ◽  
Masahiro IKENAGA ◽  
...  
Keyword(s):  
Heart Rate ◽  
Qt Interval ◽  
Dietary Sodium ◽  
Elderly Subjects ◽  
Potassium Intake ◽  
Corrected Qt Interval ◽  
Sodium And Potassium

Electrocardiographic characteristics and associated outcomes in patients with Takotsubo syndrome. Insights from the RETAKO registry

2020 ◽  
Vol 41 (Supplement_2) ◽  
Author(s):  
I Martin-Demiguel ◽  
I Nunez-Gil ◽  
A Perez-Castellanos ◽  
O Vedia ◽  
A Uribarri ◽  
...  
Keyword(s):  
Heart Rate ◽  
Primary Endpoint ◽  
Qt Interval ◽  
Protective Factor ◽  
Independent Predictor ◽  
Prognostic Significance ◽  
Takotsubo Syndrome ◽  
St Segment Elevation ◽  
Corrected Qt Interval ◽  
St Segment

Abstract Background Our aim was to describe the prevalence and prognostic significance of electrocardiographic features in patients with Takotsubo syndrome (TTS). Methods Our data come from the Spanish Multicenter REgistry of TAKOtsubo syndrome (RETAKO). All patients with complete electrocardiogram were included. Results 246 patients were studied, mean age was 71.3±11.5 and 215 (87.4%) were women. ST-segment elevation was seen in 143 patients (59.1%) and was present in ≥2 wall leads in 97 (39.8%). Exclusive elevation in inferior leads was infrequent (5 - 2.0%). After 48 hours, 198 patients (88.0%) developed negative T-waves in a median of 8 leads with a mean amplitude of 0.7±0.5 mV. Mean corrected QT interval was 520±72 ms and it was independently associated with the primary endpoint of all-cause death and nonfatal cardiovascular events (p=0.002) and all-cause death (p=0.008). A higher heart rate at admission was also an independent predictor of the primary endpoint (p=0.001) and of developing acute pulmonary edema (p=0.04). ST-segment elevation with reciprocal depression was an independent predictor of all-cause death (p=0.04). Absence of ST-segment deviation was a protective factor (p=0.005) for the primary endpoint. Arrhythmias were independently associated with cardiogenic shock (p<0.001). Conclusion Prolonged corrected QT interval, arrhythmia, heart rate at admission and broader repolarization alterations are associated with a poor outcome in TTS. Typical ECG at admission and after 48h. Funding Acknowledgement Type of funding source: None

Abstract 187: Electrocardiographic Heart Rate-corrected Qt Interval And Risk Of Stroke In The REasons For Geographic And Racial Differences In Stroke (REGARDS) Study

Stroke ◽  
2012 ◽  
Vol 43 (suppl_1) ◽  
Author(s):  
Elsayed Z Soliman ◽  
George Howard ◽  
George Howard ◽  
Mary Cushman ◽  
Brett Kissela ◽  
...  
Keyword(s):  
Heart Rate ◽  
Racial Differences ◽  
Qt Interval ◽  
Proportional Hazards ◽  
Left Ventricular ◽  
Cox Proportional Hazards ◽  
Corrected Qt Interval ◽  
Cardiovascular Morbidity And Mortality ◽  
Increased Risk ◽  
Regards Study

Background: Prolongation of heart rate-corrected QT interval (QTc) is a well established predictor of cardiovascular morbidity and mortality. Little is known, however, about the relationship between this simple electrocardiographic (ECG) marker and risk of stroke. Methods: A total of 27,411 participants aged > 45 years without prior stroke from the REasons for Geographic and Racial Differences in Stroke (REGARDS) study were included in this analysis. QTc was calculated using Framingham formula (QTcFram). Stroke cases were identified and adjudicated during an up to 7 years of follow-up (median 2.7 years). Cox proportional hazards analysis was used to estimate the hazard ratios for incident stroke associated with prolonged QTcFram interval (vs. normal) and per 1 standard deviation (SD) increase, separately, in a series of incremental models. Results: The risk of incident stroke in the study participants with baseline prolonged QTcFram was almost 3 times the risk in those with normal QTcFram [HR (95% CI): 2.88 (2.12, 3.92), p<0.0001]. After adjustment for age, race, sex, antihypertensive medication use, systolic blood pressure, current smoking, diabetes, left ventricular hypertrophy, atrial fibrillation, prior cardiovascular disease, QRS duration, warfarin use, and QT-prolonging drugs (full model), the risk of stroke remained significantly high [HR (95% CI): 1.67 (1.16, 2.41), p=0.0060)], and was consistent across several subgroups of REGARDS participants. When the risk of stroke was estimated per 1 SD increase in QTcFram, a 24% increased risk was observed [HR (95% CI): 1.24 (1.16, 1.33), p<0.0001)]. This risk remained significant in the fully adjusted model [HR (95% CI): 1.12 (1.03, 1.21), p=0.0055]. Similar results were obtained when other QTc correction formulas including Hodge’s, Bazett’s and Fridericia’s were used. Conclusions: QTc prolongation is associated with a significantly increased risk of incident stroke independently from known stroke risk factors. In light of our results, examining the risk of stroke associated with QT-prolonging drugs may be warranted.

PREDICTION OF THE HEART RATE CORRECTED QT INTERVAL (QTC) FROM A NOVEL, MULTILEAD SMARTPHONE-ENABLED ECG USING A DEEP NEURAL NETWORK

2019 ◽  
Vol 73 (9) ◽  
pp. 368 ◽  
Author(s):  
Matthew Schram ◽  
Jacqueline Baras Shreibati ◽  
Martijn Bos ◽  
Conner Galloway ◽  
Alexander Valys ◽  
...  
Keyword(s):  
Neural Network ◽  
Heart Rate ◽  
Qt Interval ◽  
Deep Neural Network ◽  
Corrected Qt Interval

Prolongation of heart rate-corrected QT interval is a predictor of cardiac autonomic dysfunction in patients with systemic lupus erythematosus

2013 ◽  
Vol 34 (5) ◽  
pp. 643-647 ◽  
Author(s):  
Atsushi Nomura ◽  
Mitsumasa Kishimoto ◽  
Osamu Takahashi ◽  
Gautam A. Deshpande ◽  
Kenichi Yamaguchi ◽  
...  
Keyword(s):  
Systemic Lupus Erythematosus ◽  
Heart Rate ◽  
Autonomic Dysfunction ◽  
Lupus Erythematosus ◽  
Qt Interval ◽  
Systemic Lupus ◽  
Corrected Qt Interval ◽  
Cardiac Autonomic Dysfunction

Influence of age, the autonomic nervous system and anxiety on QT-interval variability

2001 ◽  
Vol 101 (4) ◽  
pp. 429-438 ◽  
Author(s):  
Gianfranco PICCIRILLO ◽  
Mauro CACCIAFESTA ◽  
Marco LIONETTI ◽  
Marialuce NOCCO ◽  
Vincenza DI GIUSEPPE ◽  
...  
Keyword(s):  
Heart Rate ◽  
Qt Interval ◽  
Spectral Power ◽  
Low Frequency ◽  
Elderly Subjects ◽  
Rr Interval ◽  
T Wave ◽  
Qt Variability ◽  
Qt Interval Variability ◽  
Sympathetic Stress

As QT variability increases and heart rate variability diminishes, the QT variability index (QTVI)-a non-invasive measure of beat-to-beat fluctuations in QT interval on a single ECG lead-shows a trend towards positive values. Increased QT variability is a risk factor for sudden death. Aging lengthens the QT interval and reduces RR-interval variability. In the present study we investigated the influence of aging and the autonomic nervous system on QT-interval variability in healthy subjects. We studied 143healthy subjects, and divided them into two age ranges (younger and older than 65 years). For each subject we measured two QTVIs: from the q wave to the end of the T wave (QTeVI) and to the apex of the T wave (QTaVI). Both indexes were calculated at baseline and after sympathetic stress. In 10 non-elderly subjects, both QTVIs were determined after β-adrenoreceptor blockade induced by intravenous infusion of propranolol or sotalol. The QTVI was higher in elderly than in younger subjects (P < 0.001). QTVIs obtained during sympathetic stress remained unchanged in the elderly, but became more negative in the younger group (P < 0.05). QTeVI and QTaVI at baseline were correlated positively with age (P < 0.01) and anxiety scores (P < 0.05), but inversely with the low-frequency spectral power of RR-interval variability (P < 0.001). QTVIs were higher in subjects with higher anxiety scores. In younger subjects, sotalol infusion increased both QTVIs significantly, whereas propranolol infusion did not. In conclusion, aging increases QT-interval variability. Whether this change is associated with an increased risk of sudden death remains unclear. The association of abnormal QT-interval variability with anxiety and with reduced low-frequency spectral power of heart rate variability merits specific investigation. In healthy non-elderly subjects, acute sympathetic stress (tilt) decreases the QTVI. β-Adrenoreceptor blockade inhibits this negative trend, thus showing its sympathetic origin. Because a negative trend in QTVI induced by sympathetic stress increases only in younger subjects, it could represent a protective mechanism that is lost with aging.

Heart rate-corrected QT interval is a novel risk marker for the progression of albuminuria in people with Type 2 diabetes

2015 ◽  
Vol 32 (9) ◽  
pp. 1221-1226 ◽  
Author(s):  
Y. Hashimoto ◽  
M. Tanaka ◽  
T. Senmaru ◽  
H. Okada ◽  
M. Hamaguchi ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Heart Rate ◽  
Qt Interval ◽  
Risk Marker ◽  
Corrected Qt Interval

scholarly journals Artificial Intelligence-Enabled Assessment of the Heart Rate Corrected QT Interval Using a Mobile Electrocardiogram Device

Circulation ◽  
2021 ◽  
Author(s):  
John R. Giudicessi ◽  
Matthew Schram ◽  
J. Martijn Bos ◽  
Connor D. Galloway ◽  
Jacqueline B. Shreibati ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Heart Rate ◽  
Qt Interval ◽  
Effective Means ◽  
Area Under The Curve ◽  
Cost Effective ◽  
Qtc Prolongation ◽  
Corrected Qt Interval ◽  
The Difference ◽  
Congenital Lqts

Background: Heart rate-corrected QT interval (QTc) prolongation, whether secondary to drugs, genetics including congenital long QT syndrome (LQTS), and/or systemic diseases including SARS-CoV-2-mediated COVID19, can predispose to ventricular arrhythmias and sudden cardiac death. Currently, QTc assessment and monitoring relies largely on 12-lead electrocardiography. As such, we sought to train and validate an artificial intelligence (AI)-enabled 12-lead electrocardiogram (ECG) algorithm to determine the QTc, and then prospectively test this algorithm on tracings acquired from a mobile ECG (mECG) device in a population enriched for repolarization abnormalities. Methods: Using over 1.6 million 12-lead ECGs from 538,200 patients, a deep neural network (DNN) was derived (n = 250,767 patients for training and n = 107,920 patients for testing) and validated (n = 179,513 patients) to predict the QTc using cardiologist over-read QTc values as the gold standard. The ability of this DNN to detect clinically-relevant QTc prolongation (e.g. QTc ≥ 500 ms) was then tested prospectively on 686 genetic heart disease (GHD) patients (50% with LQTS) with QTc values obtained from both a 12-lead ECG and a prototype mECG device equivalent to the commercially-available AliveCor KardiaMobile 6L. Results: In the validation sample, strong agreement was observed between human over-read and DNN-predicted QTc values (-1.76 ± 23.14 ms). Similarly, within the prospective, GHD-enriched dataset, the difference between DNN-predicted QTc values derived from mECG tracings and those annotated from 12-lead ECGs by a QT expert (-0.45 ± 24.73 ms) and a commercial core ECG laboratory [+10.52 ms ± 25.64 ms] was nominal. When applied to mECG tracings, the DNN's ability to detect a QTc value ≥ 500 ms yielded an area under the curve, sensitivity, and specificity of 0.97, 80.0%, and 94.4%, respectively. Conclusions: Using smartphone-enabled electrodes, an AI-DNN can predict accurately the QTc of a standard 12-lead ECG. QTc estimation from an AI-enabled mECG device may provide a cost-effective means of screening for both acquired and congenital LQTS in a variety of clinical settings where standard 12-lead electrocardiography is not accessible or cost-effective.

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