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Boletin Medico Del Hospital Infantil de... 2022Atrial flutter is a rare condition in pediatrics that usually occurs as a late complication after surgery for congenital heart diseases, although it can also appear in...
BACKGROUND
Atrial flutter is a rare condition in pediatrics that usually occurs as a late complication after surgery for congenital heart diseases, although it can also appear in structurally normal hearts.
CLINICAL CASES
We conducted a retrospective study of cases of atrial flutter with no structural heart disease diagnosed in a pediatric population (between 0 and 15 years of age) during 2015-2021 in a tertiary hospital. A total of seven cases were diagnosed, with a clear predominance of males (6/7). Of the seven patients, five debuted in the perinatal period: two were diagnosed at 20 and 36 hours of life, and three, prenatally. Among these perinatal cases, more than half (3/5) were preterm. The treatment was electrical cardioversion. The evolution was satisfactory in these cases, and there were no tachycardias in their subsequent development. In contrast, when the debut occurred at a later age (5-7 years), it was associated with channelopathy (Brugada syndrome and catecholaminergic polymorphic ventricular tachycardia), and electrical ablation of the ectopic focus was required due to poor response to pharmacological treatment.
CONCLUSIONS
This study confirms the low incidence of this pathology in pediatrics and the benignity and good prognosis of neonatal flutter in most cases. The prognosis worsens when atrial flutter is diagnosed in older children, and the probability of concomitant associated heart disease increases.
Topics: Male; Infant, Newborn; Pregnancy; Female; Child; Humans; Child, Preschool; Atrial Flutter; Retrospective Studies; Spain; Anti-Arrhythmia Agents; Treatment Outcome; Hospitals
PubMed: 36264896
DOI: 10.24875/BMHIM.21000202 -
Journal of Electrocardiology 2018Patch electrocardiographic (ECG) monitors permit extended noninvasive ambulatory monitoring. To guide use of these devices, information is needed about their...
BACKGROUND
Patch electrocardiographic (ECG) monitors permit extended noninvasive ambulatory monitoring. To guide use of these devices, information is needed about their performance. We sought to determine in a large general population sample the acceptability of patch ECG monitors, the yield of arrhythmia detection, and the consistency of findings in participants monitored twice.
METHODS
In the Multi-Ethnic Study of Atherosclerosis, 1122 participants completed one or two monitoring episodes using the Zio Patch XT, a single-channel ECG patch monitor capable of recording for 14 days. Recordings were analyzed for atrial fibrillation (AF), atrial flutter, atrioventricular block, pauses, and supraventricular and ventricular ectopy.
RESULTS
The mean(SD) age at the time of monitoring was 75(8) years, 52% were men, and 15% had a prior history of clinically-recognized AF/flutter. The median monitoring duration was 13.8 days. Among 804 participants with no prior clinical history of AF/flutter and at least 12 days of monitoring on a single device, AF/flutter was detected in 32 (4.0%); in 38% of these, AF/flutter was first detected during days 3 through 12 of monitoring. In participants monitored twice, findings from the two devices showed excellent agreement for supraventricular and ventricular ectopic beats per hour, but only fair agreement for high-grade atrioventricular block and pauses of >3 s duration.
CONCLUSIONS
In a general population of older individuals, new diagnoses of AF/flutter were made in 4.0% of participants without a prior history. A single monitoring episode accurately estimated rates of supraventricular and ventricular ectopy.
Topics: Aged; Aged, 80 and over; Atherosclerosis; Atrial Fibrillation; Atrial Flutter; Atrioventricular Block; Electrocardiography, Ambulatory; Female; Humans; Male; Mass Screening; Middle Aged; United States; Ventricular Premature Complexes
PubMed: 30497763
DOI: 10.1016/j.jelectrocard.2018.07.027 -
Indian Pacing and Electrophysiology... Jul 2014Hypertrophic cardiomyopathy's (HCM) association with sudden cardiac death is well recognised. The risk of sudden cardiac death is known to increase when there is a...
Hypertrophic cardiomyopathy's (HCM) association with sudden cardiac death is well recognised. The risk of sudden cardiac death is known to increase when there is a history of unexplained syncope, abnormal blood pressure response during exercise, severe left ventricular hypertrophy or a family history of unexplained death. Implantable Cardioverter Defibrillator (ICD) implantation has been widely used for primary and secondary prevention of sudden cardiac death (SCD) in people with HCM. Subcutaneous ICD (S-ICD) therapy has been developed to overcome some of the problems associated with the transvenous leads used in conventional ICDs. In this article, we report the use of S-ICD in a patient with HCM and multiple risk factors for sudden cardiac death, this device had to be extracted due to recurrent inappropriate shocks caused by over sensing of atrial flutter and failure to treat a VT episode. We are not aware of any reports of inappropriate shocks caused by atrial flutter in people with a S-ICD.
PubMed: 25057223
DOI: No ID Found -
Cardiac Electrophysiology Clinics Sep 2014Late after surgical repair of complex congenital heart disease, atrial arrhythmias are a major cause of morbidity, and ventricular arrhythmias and sudden cardiac death...
Late after surgical repair of complex congenital heart disease, atrial arrhythmias are a major cause of morbidity, and ventricular arrhythmias and sudden cardiac death are a major cause of mortality. The six cases in this article highlight common challenges in the management of arrhythmias in the adult congenital heart disease population.
PubMed: 25197326
DOI: 10.1016/j.ccep.2014.05.014 -
Circulation Journal : Official Journal... Jun 2019
Topics: Atrial Fibrillation; Atrial Flutter; Humans; Morpholines; Tachycardia; Urea; Ventricular Dysfunction, Left
PubMed: 31189754
DOI: 10.1253/circj.CJ-19-0256 -
Diagnostics (Basel, Switzerland) Sep 2023This study aims to compare the effectiveness of using discrete heartbeats versus an entire 12-lead electrocardiogram (ECG) as the input for predicting future occurrences...
This study aims to compare the effectiveness of using discrete heartbeats versus an entire 12-lead electrocardiogram (ECG) as the input for predicting future occurrences of arrhythmia and atrial fibrillation using deep learning models. Experiments were conducted using two types of inputs: a combination of discrete heartbeats extracted from 12-lead ECG and an entire 12-lead ECG signal of 10 s. This study utilized 326,904 ECG signals from 134,447 patients and categorized them into three groups: true-normal sinus rhythm (T-NSR), atrial fibrillation-normal sinus rhythm (AF-NSR), and clinically important arrhythmia-normal sinus rhythm (CIA-NSR). The T-NSR group comprised patients with at least three normal rhythms in a year and no atrial fibrillation or arrhythmias history. Clinically important arrhythmia included atrial fibrillation, atrial flutter, atrial premature contraction, atrial tachycardia, ventricular premature contraction, ventricular tachycardia, right and left bundle branch block, and atrioventricular block over the second degree. The AF-NSR group included normal sinus rhythm paired with atrial fibrillation or atrial flutter within 14 days, and the CIA-NSR group comprised normal sinus rhythm paired with CIA occurring within 14 days. Three deep learning models, ResNet-18, LSTM, and Transformer-based models, were utilized to distinguish T-NSR from AF-NSR and T-NSR from CIA-NSR. The experiments demonstrated the potential of using discrete heartbeats in predicting future arrhythmia and atrial fibrillation incidences extracted from 12-lead electrocardiogram (ECG) signals alone, without any additional patient information. The analysis reveals that these discrete heartbeats contain subtle patterns that deep learning models can identify. Focusing on discrete heartbeats may lead to more timely and accurate diagnoses of these conditions, improving patient outcomes and enabling automated diagnosis using ECG signals as a biomarker.
PubMed: 37685387
DOI: 10.3390/diagnostics13172849 -
Journal of the American Heart... Sep 2022Background Marfan syndrome (MFS) is an autosomal dominant connective tissue disorder affecting multiple systems, particularly the cardiovascular system. The leading...
Background Marfan syndrome (MFS) is an autosomal dominant connective tissue disorder affecting multiple systems, particularly the cardiovascular system. The leading causes of death in MFS are aortopathies and valvular disease. We wanted to identify the frequency of arrhythmia and postural orthostatic tachycardia syndrome, length of hospital stay, health care-associated costs (HAC), and in-hospital mortality in patients with MFS. Methods and Results The National Inpatient Sample database from 2005 to 2014 was queried using () codes for MFS and arrhythmias. Patients were classified into subgroups: supraventricular tachycardia, ventricular tachycardia (VT), atrial fibrillation, atrial flutter, and without any type of arrhythmia. Data about length of stay, HAC, and in-hospital mortality were also abstracted from National Inpatient Sample database. Adjusted HAC was calculated as multiplying HAC and cost-to-charge ratio; 12 079 MFS hospitalizations were identified; 1893 patients (15.7%) had an arrhythmia; and 4.9% of the patients had postural orthostatic tachycardia syndrome. Median values of length of stay and adjusted HAC in VT group were the highest among the groups (VT: 6 days, $18 975.8; supraventricular tachycardia: 4 days, $11 906.6; atrial flutter: 4 days, $11 274.5; atrial fibrillation: 5 days, $10431.4; without any type of arrhythmia: 4 days, $8336.6; both =0.0001). VT group had highest in-patient mortality (VT: 5.3%, atrial fibrillation: 4.1%, without any type of arrhythmia: 2.1%, atrial flutter: 1.7%, supraventricular tachycardia: 0%; <0.0001) even after adjustment for potential confounders (without any type of arrhythmia versus VT; odds ratio [95% CI]: 3.18 [1.62-6.24], =0.001). Conclusions Arrhythmias and postural orthostatic tachycardia syndrome in MFS were high and associated with increased length of stay, HAC, and in-hospital mortality especially in patients with VT.
Topics: Atrial Fibrillation; Atrial Flutter; Humans; Inpatients; Marfan Syndrome; Postural Orthostatic Tachycardia Syndrome; Tachycardia, Paroxysmal; Tachycardia, Supraventricular
PubMed: 36000435
DOI: 10.1161/JAHA.121.024939 -
Journal of the American Heart... Mar 2017The incidence, predictors, and impact of atrial arrhythmias along with left atrial structural changes in patients with left ventricular assist devices (LVADs) remain...
BACKGROUND
The incidence, predictors, and impact of atrial arrhythmias along with left atrial structural changes in patients with left ventricular assist devices (LVADs) remain undetermined.
METHODS AND RESULTS
All patients who underwent LVAD implantation from 2008 to 2015 at the University of Chicago Medical Center were included. Electronic medical records, electrocardiograms, echocardiograms, and cardiac electrical device interrogations were reviewed. The association of arrhythmias and clinical covariates with survival was evaluated by Kaplan-Meier and Cox proportional hazards analyses. A total of 331 patients were followed for a median of 330 days (range 0-2306 days). Mean age was 57.8±12.8 years, 256 participants (77.3%) were male, mean left ventricular ejection fraction was 20±6.6%, and 124 (37.5%) had ischemic cardiomyopathy. Atrial arrhythmias (53.8%) were highly prevalent and frequently coexisted before LVAD implantation: atrial fibrillation (AF) in 45.9%, atrial flutter in 13.9%, atrial tachycardia in 6.9%, and atrioventricular nodal reentrant tachycardia in 1.2%. New-onset AF was documented in 14 patients (7.8% of patients without prior AF) after the first 30 days with an LVAD. Increasing age, renal insufficiency, and lung disease were predictors of new-onset AF after LVAD implantation. Of patients with paroxysmal AF, 43% had no further AF after LVAD. Left atrial size and volume index improved with LVAD (<0.005). History of persistent AF, atrial tachycardia, ventricular arrhythmia, coronary artery bypass, and low albumin were associated with decreased survival.
CONCLUSIONS
Atrial arrhythmias are significantly prevalent in patients who require LVAD and are associated with increased mortality; however, LVADs induce favorable atrial structural and electrical remodeling.
Topics: Age Factors; Aged; Arrhythmias, Cardiac; Atrial Fibrillation; Atrial Flutter; Atrial Remodeling; Cardiomyopathies; Coronary Artery Bypass; Echocardiography; Electrocardiography; Female; Heart Failure; Heart-Assist Devices; Humans; Hypoalbuminemia; Kaplan-Meier Estimate; Lung Diseases; Male; Middle Aged; Myocardial Ischemia; Proportional Hazards Models; Prosthesis Implantation; Renal Insufficiency; Retrospective Studies; Stroke Volume; Survival Rate; Tachycardia; Tachycardia, Atrioventricular Nodal Reentry; United States
PubMed: 28275069
DOI: 10.1161/JAHA.116.005340 -
Sensors (Basel, Switzerland) Jun 2022In this research, a heartbeat classification method is presented based on evolutionary feature optimization using differential evolution (DE) and classification using a...
In this research, a heartbeat classification method is presented based on evolutionary feature optimization using differential evolution (DE) and classification using a probabilistic neural network (PNN) to discriminate between normal and arrhythmic heartbeats. The proposed method follows four steps: (1) preprocessing, (2) heartbeat segmentation, (3) DE feature optimization, and (4) PNN classification. In this method, we have employed direct signal amplitude points constituting the heartbeat acquired from the ECG holter device with no secondary feature extraction step usually used in case of hand-crafted, frequency transformation or other features. The heartbeat types include normal, left bundle branch block, right bundle branch block, premature ventricular contraction, atrial premature, ventricular escape, ventricular flutter and paced beat. Using ECG records from the MIT-BIH, heartbeats are identified to start at 250 ms before and end at 450 ms after the respective R-peak positions. In the next step, the DE method is applied to reduce and optimize the direct heartbeat features. Although complex and highly computational ECG heartbeat classification algorithms have been proposed in the literature, they failed to achieve high performance in detecting some minority heartbeat categories, especially for imbalanced datasets. To overcome this challenge, we propose an optimization step for the deep CNN model using a novel classification metric called the Matthews correlation coefficient (MCC). This function focuses on arrhythmia (minority) heartbeat classes by increasing their importance. Maximum MCC is used as a fitness function to identify the optimum combination of features for the uncorrelated and non-uniformly distributed eight beat class samples. The proposed DE-PNN scheme can provide better classification accuracy considering 8 classes with only 36 features optimized from a 253 element feature set implying an 85.77% reduction in direct amplitude features. Our proposed method achieved overall 99.33% accuracy, 94.56% F1, 93.84% sensitivity, and 99.21% specificity.
Topics: Algorithms; Arrhythmias, Cardiac; Electrocardiography; Heart Rate; Humans; Neural Networks, Computer; Signal Processing, Computer-Assisted
PubMed: 35746232
DOI: 10.3390/s22124450 -
Medicine Jul 2017Stroke remains one of the leading causes of death in the United States. Current evidence identified electrocardiographic abnormalities and cardiac arrhythmias in 50% of...
Stroke remains one of the leading causes of death in the United States. Current evidence identified electrocardiographic abnormalities and cardiac arrhythmias in 50% of patients with an acute stroke. The purpose of this study was to assess whether the presence of ventricular arrhythmia (VA) in adult patients hospitalized in Florida with acute stroke increased the risk of in-hospital mortality.Secondary data analysis of 215,150 patients with ischemic and hemorrhagic stroke hospitalized in the state of Florida collected by the Florida Agency for Healthcare Administration from 2008 to 2012. The main outcome for this study was in-hospital mortality. The main exposure of this study was defined as the presence of VA. VA included the ICD-9 CM codes: paroxysmal ventricular tachycardia (427.1), ventricular fibrillation (427.41), ventricular flutter (427.42), ventricular fibrillation and flutter (427.4), and other - includes premature ventricular beats, contractions, or systoles (427.69). Differences in demographic and clinical characteristics and hospital outcomes were assessed between patients who developed versus did not develop VA during hospitalization (χ and t tests). Binary logistic regression was used to estimate unadjusted and adjusted odds ratios and 95% confidence intervals (CIs) between VA and in-hospital mortality.VA was associated with an increased risk of in-hospital mortality after adjusting for all covariates (odds ratio [OR]: 1.75; 95% CI: 1.6-1.2). There was an increased in-hospital mortality in women compared to men (OR: 1.1; 95% CI: 1.1-1.14), age greater than 85 years (OR: 3.9, 95% CI: 3.5-4.3), African Americans compared to Whites (OR: 1.1; 95% CI: 1.04-1.2), diagnosis of congestive heart failure (OR: 2.1; 95% CI: 2.0-2.3), and atrial arrhythmias (OR: 2.1, 95% CI: 2.0-2.2). Patients with hemorrhagic stroke had increased odds of in-hospital mortality (OR: 9.0; 95% CI: 8.6-9.4) compared to ischemic stroke.Identifying VAs in stroke patients may help in better target at risk populations for closer cardiac monitoring during hospitalization. The impact of implementing methods of quick assessment could potentially reduce VA associated sudden cardiac death.
Topics: Age Factors; Aged; Aged, 80 and over; Arrhythmias, Cardiac; Brain Ischemia; Female; Florida; Hospital Mortality; Hospitalization; Humans; Intracranial Hemorrhages; Male; Middle Aged; Multivariate Analysis; Prospective Studies; Risk Factors; Sex Factors; Stroke
PubMed: 28700475
DOI: 10.1097/MD.0000000000007403