Characterization and classification of intracardiac atrial fibrillation signals using the time-singularity multifractal spectrum distribution

2021 ◽  
Vol 96 ◽  
pp. 105675
Author(s):  
Robert D. Urda-Benitez ◽  
Andrés E. Castro-Ospina ◽  
Andrés Orozco-Duque
Keyword(s):  
Atrial Fibrillation ◽  
Multifractal Spectrum ◽  
Time Singularity ◽  
Spectrum Distribution

scholarly journals Feature extraction based on time-singularity multifractal spectrum distribution in intracardiac atrial fibrillation signals

TecnoLógicas ◽  
2017 ◽  
Vol 20 (40) ◽  
pp. 97-111
Author(s):  
Robert D. Urda-Benitez ◽  
Andrés E. Castro-Ospina ◽  
Andrés Orozco-Duque
Keyword(s):  
Atrial Fibrillation ◽  
Roc Curve ◽  
Multifractal Analysis ◽  
Operating Characteristic ◽  
Multifractal Spectrum ◽  
Time Singularity ◽  
Continuous Activity ◽  
Spectrum Distribution ◽  
Critical Activity ◽  
Stationary Behavior

Non-linear analysis of electrograms (EGM) has been proposed as a tool to detect critical conduction sites (e.g., rotors vortex, multiple wavefronts) in atrial fibrillation (AF). Likewise, studies have shown that multifractal analysis is useful to detect critical activity in EGM signals. However, the multifractal spectrum does not consider the temporal information. There is a new mathematical formalism to overcome this limitation: the time-singularity multifractal spectrum distribution (TS-MFSD), which involves the time variation of the spectrum. In this manuscript, we describe the methodology to compute the TS-MFSD from EGM signals. Moreover, we propose a methodology to extract features from time-singularity spectrum and from singularity energy spectrum (SES). We tested the features in an EGM database labeled by experts as: non-fragmented, discrete fragmented potentials, disorganized activity, and continuous activity. We tested the area under the receiver operating characteristic (ROC) curve. The proposed features achieve an area under the ROC curve of 95.17% when detecting signals with continuous activity. These results outperform those reported using multifractal analysis. To our knowledge, this is the first work that report the use of TS-MFSD in biomedical signals and our findings suggest that time-singularity has the potential to be used in the study of non-stationary behavior of EGM signals in AF.

Increased prevalence of psychosis in patients who get admitted with atrial fibrillation with worse outcomes

2017 ◽  
Vol 41 (S1) ◽  
pp. S575-S576
Author(s):  
Z. Mansuri ◽  
S. Patel ◽  
P. Patel ◽  
O. Jayeola ◽  
A. Das ◽  
...  
Keyword(s):  
Atrial Fibrillation ◽  
Hospital Admissions ◽  
Temporal Trends ◽  
International Classification Of Diseases ◽  
Trend Test ◽  
Classification Of Diseases ◽  
Competing Interest ◽  
Armitage Trend Test ◽  
The Impact

ObjectiveTo determine trends and impact on outcomes of atrial fibrillation (AF) in patients with pre-existing psychosis.BackgroundWhile post-AF psychosis has been extensively studied, contemporary studies including temporal trends on the impact of pre-AF psychosis on AF and post-AF outcomes are largely lacking.MethodsWe used Nationwide Inpatient Sample (NIS) from the healthcare cost and utilization project (HCUP) from year's 2002–2012. We identified AF and psychosis as primary and secondary diagnosis respectively using validated international classification of diseases, 9th revision, and Clinical Modification (ICD-9-CM) codes, and used Cochrane–Armitage trend test and multivariate regression to generate adjusted odds ratios (aOR).ResultsWe analyzed total of 3.887.827AF hospital admissions from 2002–2012 of which 1.76% had psychosis. Proportion of hospitalizations with psychosis increased from 5.23% to 14.28% (P trend < 0.001). Utilization of atrial-cardioversion was lower in patients with psychosis (0.76%v vs. 5.79%, P < 0.001). In-hospital mortality was higher in patients with Psychosis (aOR 1.206; 95%CI 1.003–1.449; P < 0.001) and discharge to specialty care was significantly higher (aOR 4.173; 95%CI 3.934–4.427; P < 0.001). The median length of hospitalization (3.13 vs. 2.14 days; P < 0.001) and median cost of hospitalization (16.457 vs. 13.172; P < 0.001) was also higher in hospitalizations with psychosis.ConclusionsOur study displayed an increasing proportion of patients with Psychosis admitted due to AF with higher mortality and extremely higher morbidity post-AF, and significantly less utilization of atrial-cardioversion. There is a need to explore reasons behind this disparity to improve post-AF outcomes in this vulnerable population.Disclosure of interestThe authors have not supplied their declaration of competing interest.

Overview on prediction, detection, and classification of atrial fibrillation using wavelets and AI on ECG

2022 ◽  
pp. 105168
Author(s):  
Hassan Serhal ◽  
Nassib Abdallah ◽  
Jean-Marie Marion ◽  
Pierre Chauvet ◽  
Mohamad Oueidat ◽  
...  
Keyword(s):  
Atrial Fibrillation

Abstract 16199: Trend of Hypertensive Emergencies in Atrial Fibrillation Hospitalization; National Estimate

Circulation ◽  
2020 ◽  
Vol 142 (Suppl_3) ◽  
Author(s):  
Mae'n Al-Dabbas ◽  
Jay Shah ◽  
devina adalja ◽  
Archana Gundabolu ◽  
Ashish Kumar ◽  
...  
Keyword(s):  
Atrial Fibrillation ◽  
International Classification Of Diseases ◽  
Primary Diagnosis ◽  
Hypertensive Emergency ◽  
P Value ◽  
National Inpatient Sample ◽  
Common Risk Factor ◽  
The Past ◽  
Classification Of Diseases

Introduction: Hypertension has been reported as one of the most common risk factor causing atrial fibrillation (AF). Also, hypertension is associated with more persistent AF. However the epidemiology for incidence of hypertensive emergency in AF hospitalization is not well documented. Hypothesis: We hypothesize that frequency of hypertensive emergency has been increasingly associated with Atrial fibrillation. Methods: National inpatient sample from 2005 -2015 was used for the present analysis. Patients over 18 years, with AF as the primary diagnosis were identified using International Classification of Diseases, Ninth Revision-Clinical Modification (ICD-9-CM) code, 427.31. Patients with hypertensive emergency were identified using ICD-9-CM code. 401.0, 402.0, 403.0, 404.0, 405.0. Results: A total of 4,988,269 AF patients over 18 years of age were included in the present analysis. Of these hospitalization 49,423 had hypertensive emergency during hospitalizations and the rest 4,938,846 had no hypertensive emergency. There was a monotonic increase in the trend of rates of hypertensive emergency per 1000 AF hospitalizations, from 2005 - 2015. (P value <0.001) [Figure 1]. Conclusion: There has been a significant increase in the rates of hypertensive emergency among AF hospitalization, over the past decade. Further research is needed to investigate the reason for this increased trend.

Abstract 14682: Impact of Atrial Fibrillation in Aortic Stenosis Patients: Insights From the United States Readmissions Database

Circulation ◽  
2020 ◽  
Vol 142 (Suppl_3) ◽  
Author(s):  
Shashank Shekhar ◽  
Anas M Saad ◽  
Toshiaki Isogai ◽  
Mohamed M Gad ◽  
Keerat Ahuja ◽  
...  
Keyword(s):  
Atrial Fibrillation ◽  
Aortic Stenosis ◽  
Hospital Mortality ◽  
Large Scale ◽  
International Classification Of Diseases ◽  
The United States ◽  
Large Scale Data ◽  
Classification Of Diseases

Introduction: Even though atrial fibrillation (AF) is present in >30% of patients with aortic stenosis (AS), it is not typically included in the decision-making algorithm for the timing or need for aortic valve replacement (AVR), either by transcatheter (TAVR) or surgical (SAVR) approaches. Large scale data on how AF affects outcomes of AS patients remain scarce. Methods: From the Nationwide Readmissions Database (NRD), we retrospectively identified AS patients aged ≥18years, with and without AF admitted between January and June in 2016 and 2017 (to allow for a six month follow up), using the International Classification of Diseases-10 th revision codes. Multivariable logistic regression was performed to examine the predictors of in-hospital mortality during index hospitalization. In-hospital complications and 6 month in-hospital mortality during any readmission after being discharged alive were compared in patients with and without AF, for patients undergoing TAVR, SAVR or no-AVR. Results: We identified 403,089 AS patients, of which 41% had AF. Patients with AF were older (median age in years: 83 vs. 79) and were more frequently females (52% vs. 48%; p<0.001). Table summarizes outcomes of AS patients with and without AF. TAVR in patients with AF was associated with higher in-hospital mortality and follow-up mortality as compared to patients without AF. Although AF did not influence in-hospital mortality in SAVR population, follow-up mortality was also significantly higher after SAVR in patients with AF compared to patients without AF. For patients not undergoing AVR, in-hospital and follow-up mortality were higher in AF population compared to no AF and was higher than patients undergoing AVR (Table). Conclusions: AF is associated with worse outcomes in patients with AS irrespective of treatment (TAVR, SAVR or no-AVR). More studies are needed to understand the implications of AF in AS population and whether earlier treatment of AS in patients with AF can improve outcomes.

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