Variation Of Atrial Fibrillation Research Articles

Abstract 4127792: Age-stratified Monogenic and Polygenic Contributions for Atrial Fibrillation in the All of Us Research Program

Background: Rare and common genetic variation both contribute to atrial fibrillation (AF), but the effects may not be uniform across ages. The All of Us Research Program contains whole-genome sequencing of 100,574 adult participants with electronic health records. Hypothesis: Rare genetic variants are associated with early-onset AF; common genetic variants are associated with late-onset AF. Aims: To quantify the diagnostic yield provided by rare and common genetic variation in AF across age. Methods: The clinical, monogenic, and polygenic contributions to AF were assessed in a cross-sectional group of participants in the NIH-funded All of Us Research Program, stratified by three age groups: <45 years (n=22,290), 45-60 years (n= 26,805), >60 years (n=51,659). Variant discovery was performed for pathogenic or likely pathogenic (P/LP) variants among 145 candidate cardiac genes with dominant inheritance for cardiomyopathy and arrhythmia. A previously established polygenic risk score (PRS) was calculated. After adjusting for known clinical factors, multivariable analysis quantified the associations between monogenic and polygenic factors versus AF status in each age group. Results: There were 100,574 participants: 7,811 with AF and 92,763 without AF. The presence of ≥1 P/LP variant(s) were associated with AF across all age groups, with stronger associations in the age <45 group (OR 2.3 [95% CI 1.4-4.1]) compared older groups (OR 1.5 [95% CI 1.1-2.1] in age 45-60, and OR 1.4 [95% CI 1.2-1.7] in age >60). In contrast, PRS was not associated with AF in participants <45 years (OR 1.02 [95% CI 0.88-1.17]) but was associated with AF in the older groups: OR 1.54 [95% CI 1.31-1.80] in age 45-60 and OR 1.49 [95% CI 1.40-1.59] for age >60. Overall, clinical risk factors are highly associated with AF (AUC 0.84 [0.83-0.85]); adding polygenic and monogenic factors contribute only marginal improvement (AUC 0.86 [0.85-0.87]). Conclusion: In this cross-sectional dataset, monogenic and polygenic factors have opposite associations with AF. Monogenic variants are associated with early-onset AF, whereas PRS has no association with AF at younger ages. Clinical risk factors continue to explain the majority of the variation in AF status.

Abstract 4118387: Artificial Intelligence-Enhanced Echocardiogram Assessment Helps Distinguish Cardiomyopathy from Beat-to-Beat Variation in Atrial Fibrillation

Background: Atrial fibrillation (AF) can be associated with reductions in left ventricular ejection fraction (LVEF) that improve upon conversion of AF to sinus rhythm. Such LVEF changes during AF may be due to LVEF measurement error from beat-to-beat variations related to AF itself. More precise artificial intelligence (AI)-enhanced LVEF assessment could help distinguish between such LVEF “pseudo-reduction” during AF and true cardiomyopathy, thus potentially preventing unnecessary downstream workup and treatment. Methods: Using a transthoracic echocardiogram database at a large academic medical center, we identified all patients whose LVEF fell below 50% while in AF who had subsequent LVEF recovery to over 50% within 90 days after converting from AF to sinus rhythm. For echocardiograms in AF, we compared the clinically assessed LVEF with AI-enhanced LVEF assessment by EchoNet-Dynamic, a validated deep learning algorithm. Results: In our cohort of 84 patients, the mean age was 74 years old, 36.9% were female, and 26.2% non-White. The mean LVEF recovery was 19.3% (95% CI 17.1-21.5%) after converting from AF to sinus rhythm with a mean duration of 27.4 days between the AF and sinus rhythm echocardiograms (Figure 1). For AF echocardiograms, the LVEF when reassessed by deep learning was 8.4% (6.3-10.5%) higher than the original clinical read, resulting in 30.3% of patients being reclassified as no longer having a reduced LVEF less than 50% while in AF. Among these patients with LVEF reductions during AF, 27.4% and 19.0% were given a new or worsened heart failure with reduced ejection fraction (HFrEF) diagnosis, 15.5% underwent ischemic testing, and 17.9% were started on new HFrEF medications. Discussion: LVEF reductions during AF can lead to new HFrEF diagnosis, workup, and treatment. However, such LVEF reductions may be temporary and partially explained by undermeasurement of LVEF during AF. AI-enhanced LVEF assessment may help reduce such measurement errors during AF and thereby prevent overdiagnosis of HFrEF. Further research is needed to understand the clinical significance of true but temporary LVEF reductions during AF.

Arrhythmia and Time of Day in Maintenance Hemodialysis: Secondary Analysis of the Monitoring in Dialysis Study

Rationale & ObjectiveThe incidence of arrhythmia varies by time of day. How this impacts individuals on maintenance dialysis is uncertain. Our objective was to quantify the relationship of arrhythmia with the time of day and the timing of dialysis. Study DesignSecondary analysis of Monitoring in Dialysis study- a multicenter prospective cohort study. Settings & ParticipantsLoop recorders were implanted for continuous cardiac monitoring in 66 participants on maintenance dialysis with a follow up of 6 months. ExposureTime of day based on 6-hour intervals OutcomesEvent rates of clinically significant arrhythmia Analytical ApproachNegative binomial mixed effects regression models for repeated measures were used to evaluate data from the Monitoring in Dialysis study for differences in diurnal patterns of clinically significant arrhythmia among those with end stage kidney disease with heart failure and end stage kidney disease alone. We additionally analyzed rates according to presence of heart failure, time of dialysis shift, and dialysis vs. non dialysis day. ResultsRates of clinically significant arrhythmia peaked between 0:00 AM-<6:00 AM and were more than 1.5-fold as frequent during this interval compared with the rest of the day. In contrast, variations in atrial fibrillation peaked between 6:00 AM-<12: PM, but variations across the day were qualitatively small. Clinically significant arrhythmia occurred at numerically higher rate in individuals with end stage kidney disease and heart failure (5.9 events/month, 95% CI: 1.3-26.8) than those without heart failure (4.0 events/month, 95% CI: 0.9-17.9). Although differences in overall rate were not significant, their periodicity was significantly different (P<0.001) with a peak between 0:00 AM-6:00 AM with kidney failure alone and between 6:00 AM-<12:00 PM in those with heart failure. Although the overall clinically significant arrhythmia rate was similar with morning compared with evening dialysis shifts (P=0.43), their periodicity differed with a peak between 0:00 AM-<6:00 AM in those with AM dialysis and a later peak between 6:00 AM-<12:00 PM in those with PM shifts LimitationsPost hoc analysis, unable to account for unmeasured confounders ConclusionClinically significant arrhythmias showed strong diurnal patterns with a maximal peak between 0:00-<6:00 AM and noon. Although overall arrhythmia rates were similar the peak rate occurred overnight in individuals without heart failure and during the morning in individuals with heart failure. Further exploration of the influence of circadian rhythm on arrhythmia in the setting of hemodialysis is needed.

PO-03-182 ASSESSMENT OF PRICE VARIATION IN CARDIOVASCULAR CATHETER ABLATIONS AT US HOSPITALS

Ablation of atrial fibrillation (AF) and ventricular tachycardia (VT) comprise a significant proportion of catheter ablation procedures. However, few studies have explored the commercial cost footprint of these procedures, despite the 2021 Hospital Price Transparency Final Rule mandating US hospitals publish their insurer-negotiated prices. This study sought to characterize and identify factors contributing to variation in AF and VT ablation prices across the US. We queried a commercial database containing hospital-disclosed prices to characterize variation in ablation procedure prices within and across US hospitals. This price data was linked to hospital characteristics using Medicare Facility IDs. Univariate analysis was conducted to compare median prices across multiple factors. In total, 1,030 hospitals reported commercial prices for AF ablation, while 1,006 reported prices for VT ablation. For AF ablation, median prices were higher at major investor-owned facilities (p<0.01), while for VT ablation, investor-owned facilities had lower prices (p<0.01). For both AF and VT ablation, the New England region exhibited the highest median price ($28,141 and $28,145, respectively), while the Middle Atlantic exhibited the lowest median price ($16,829 and $15,666, respectively). Higher prices were associated with better than average all-cause readmission rates (p<0.01 for AF and VT ablation) and higher patient hospital ratings (p<0.01 for both). However, CMS hospital ratings (AF: p=0.42; VT: p=0.08) and hospital-wide mortality were not associated with price (AF: p=0.36; VT: p=0.56). For both AF and VT ablation, commercial rates did not differ widely from the Medicare price. Within hospitals, the 90th percentile payer-negotiated rate was 2.42 (IQR 1.34-4.61) times the 10th percentile rate (within-center ratio) for AF ablation and 2.40 (IQR 1.41-5.16) for VT ablation. Across hospitals within the same hospital referral region (HRR), the median price at the 90th percentile hospital was 1.54 (IQR 1.00-2.63) times that at the 10th percentile hospital (between-center ratio) for AF ablation and 1.47 (IQR 1.00-2.61) for VT ablation. Prices for ablation procedures varied widely within and between hospitals. Commercial markup from the Medicare price was limited. Several factors correlated closely with reimbursement, including hospital-wide readmissions and patient ratings. However, there was no association between price and hospital-wide mortality or CMS rating.Tabled 1Univariate Analysis of Factors Associated with Cardiovascular Catheter Ablations Commercial Price (PO-03-182)Atrial Fibrillation AblationVentricular Tachycardia AblationCategorical Values(% Reporting)# ofHospitals(%)MedianPrice($)IQR($)P-Value †# ofHospitals(%)MedianPrice($)IQR($)P-Value †Region (92.1, 92.4)<0.01<0.01 New England (CT, MA, ME, NH, RI, VT)Middle Atlantic (NJ, NY, PA)South Atlantic (DC, DE, MD, VA, WV, C, SC, GA, FL)East North Central (OH, IN, IL, MI, WI)East South Central (KY, TN, AL, MS)West North Central (MN, IA, MO, ND, SD, NE, KS)West South Central (AR, LA, OK, TX)Mountain (MT, ID, WY, CO, NM, AZ, UT, NV)Pacific (WA, OR, CA, AK, HI)37 (3.9)112 (11.8)226 (23.8)188 (19.8)79 (8.3)97 (10.2)140 (14.8)42 (4.4)28 (3.0)28141168291808220065215512439926517258912460626243-305588362-2330411750-2588211817-2913316087-2799216203-2839416641-3176322631-3315017616-3916037 (4.0)108 (11.6)226 (24.3)176 (18.9)81 (8.7)91 (9.8)142 (15.3)40 (4.3)29 (3.1)28145156661808217831211982081224674258892727725174-309468071-2164711019-2589111817-2823914531-2789011792-2672412432-3169522516-3274423006-42535Hospital Type (88.7, 89.2)0.06<0.01 For-ProfitNot-For-ProfitGovernment194 (21.2)651 (71.2)69 (7.5)21798216562256111338-2817712739-3033818147-31958190 (21.2)640 (71.3)67 (7.5)1734020544233759273-2646612003-3020416843-36485Major Investor Owned (96.6, 96.7)<0.01<0.01 Major Investor OwnedNot Major Investor Owned222 (22.3)773 (77.7)221512002711751-2798113330-30470215 (22.1)758 (77.9)16841211819273-2588912720-30719Teaching Status (92.1, 92.4)0.830.59 Major TeachingMinor TeachingNon-Teaching132 (13.9)624 (65.8)193 (20.3)21940216132165611551-3022112443-2962315899-30347129 (13.9)492 (52.9)309 (33.2)20856198602085510934-3090211763-2852812365-28998Urban/Rural (99.9, 100.0)0.760.35 UrbanRural937 (91.1)92 (8.9)217882167712584-2960114804-30488917 (91.2)89 (8.8)201252161911823-2895314803-29936Disproportionate Share Hospital (82.4, 83.0)0.02<0.01 Disproportionate Share Hospital (DSH)Sole Community Hospital (not DSH-eligible)Not DSH692 (81.5)38 (4.5)119 (14.0)21583264502113412124-2958119779-3331412829-30029684 (81.9)35 (4.2)116 (13.9)19706263661900511782-2885921826-3236511935-28034CMS Hospital-Wide Mortality (80.4, 80.7)0.360.56 Above National AverageSame as National AverageBelow National Average159 (19.2)553 (66.8)116 (14.0)21470216212383713394-30164127226-2968912021-32762158 (19.5)537 (66.1)117 (14.4)19465203562162111985-2811311854-2927311834-33024CMS Hospital-Wide Readmission Rate (82.2, 82.7)<0.01<0.01 Above National AverageSame as National AverageBelow National Average346 (40.9)123 (14.5)378 (44.6)23431237131916215948-3173916936-2945211091-28180340 (40.9)121 (14.5)371 (44.6)22515221981855914028-3145011730-3021710846-27912HCAHPS Patient Overall Hospital Rating (80.8, 81.2)<0.01<0.01 1234540 (4.8)149 (17.9)303 (36.4)311 (37.4)29 (3.5)156711863621198243192950211775-2284713066-2704511718-2878915103-3175120076-3437136 (4.4)142 (17.4)298 (36.5)312 (38.2)29 (3.5)168121684519526239822823610945-2206610870-2393610687-2799114446-3180418905-34272CMS Overall Hospital Rating (82.0, 83.2)0.420.08 1234543 (5.1)160 (18.9)246 (29.1)264 (31.2)132 (15.6)184712122321716223762208312445-2486412816-2831411471-2992111841-3046515648-3180541 (4.9)154 (18.6)244 (29.4)260 (31.3)131 (15.8)154061861620466203732252710378-2254411751-2589311228-2914511782-3060212829-31296† Comparisons were done via the Kruskal-Wallis test. 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Geographical variation and clustering are found in atrial fibrillation beyond socioeconomic differences: a Danish cohort study, 1987\u20132015

BackgroundThe prevalence and incidence rate of atrial fibrillation (AF) increase worldwide and AF is a risk factor for more adverse cardiovascular diseases including stroke. Approximately 44% of AF cases cannot be explained by common individual risk factors and risk might therefore also be related to the environment. By studying geographical variation and clustering in risk of incident AF adjusted for socioeconomic position at an individual level, potential neighbourhood risk factors could be revealed.MethodsInitially, yearly AF incidence rates 1987–2015 were estimated overall and stratified by income in a register-based cohort study. To examine geographical variation and clustering in AF, we used both spatial scan statistics and a hierarchical Bayesian Poisson regression analysis of AF incidence rates with random effect of municipalities (n = 98) in Denmark in 2011–2015.ResultsThe 1987–2015 cohort included 5,453,639 individuals whereof 369,800 were diagnosed with an incident AF. AF incidence rate increased from 174 to 576 per 100,000 person-years from 1987 to 2015. Inequality in AF incidence rate ratio between highest and lowest income groups increased from 23% in 1987 to 38% in 2015. We found clustering and geographical variation in AF incidence rates, with incidence rates at municipality level being up to 34% higher than the country mean after adjusting for socioeconomic position.ConclusionsGeographical variations and clustering in AF incidence rates exist. Compared to previous studies from Alberta, Canada and the United States, we show that geographical variations exist in a country with free access to healthcare and even when accounting for socioeconomic differences at an individual level. An increasing social inequality in AF was seen from 1987 to 2015. Therefore, when planning prevention strategies, attention to individuals with low income should be given. Further studies focusing on identification of neighbourhood risk factors for AF are needed.

Estimation of properties of the heart from beat­to­beat pulse pressure variations in atrial fibrillation using a mechanistic mathematical model: Insights from inference with full uncertainty quantification

Estimation of properties of the heart from beat­to­beat pulse pressure variations in atrial fibrillation using a mechanistic mathematical model: Insights from inference with full uncertainty quantification

Common variation in atrial fibrillation: navigating the path from genetic association to mechanism.

Atrial fibrillation (AF) is the most common cardiac arrhythmia with well-established clinical and genetic risk components. Genome-wide association studies (GWAS) have identified 17 independent susceptibility signals for AF at 14 genomic regions, but the mechanisms through which these loci confer risk to AF remain largely undefined. This problem is not unique to AF, as the field of functional genomics, which attempts to bridge this gap from genotype to phenotype, has only uncovered the mechanisms for a handful of GWAS loci. Recent functional genomic studies have made great strides towards translating genetic discoveries to an underlying mechanism, but the large-scale application of these techniques to AF has remain limited. These advances, as well as the continued unresolved challenges for both common variation in AF and the functional genomics field in general, will be the subject of the following review.

Global epidemiology of atrial fibrillation.

Atrial fibrillation (AF) is a major public health burden worldwide, and its prevalence is set to increase owing to widespread population ageing, especially in rapidly developing countries such as Brazil, China, India, and Indonesia. Despite the availability of epidemiological data on the prevalence of AF in North America and Western Europe, corresponding data are limited in Africa, Asia, and South America. Moreover, other observations suggest that the prevalence of AF might be underestimated-not only in low-income and middle-income countries, but also in their high-income counterparts. Future studies are required to provide precise estimations of the global AF burden, identify important risk factors in various regions worldwide, and take into consideration regional and ethnic variations in AF. Furthermore, in response to the increasing prevalence of AF, additional resources will need to be allocated globally for prevention and treatment of AF and its associated complications. In this Review, we discuss the available data on the global prevalence, risk factors, management, financial costs, and clinical burden of AF, and highlight the current worldwide inadequacy of its treatment.

Atrial Fibrillation and Race – A Contemporary Review

Atrial fibrillation (AF) is the most commonly encountered clinical arrhythmia and is associated with adverse outcomes and increased healthcare costs. Racial variations in AF are recognized yet poorly understood. In this review we summarize racial differences in AF epidemiology, risk factors, genetics, and outcomes. We identify novel risk factors, inflammatory mediators and biomarkers associated with AF, which have had limited study in racial and ethnic minorities. We describe the mismatch between risk factor burden and AF. We highlight the limited participation of minorities in trials for AF management and stroke prevention that contrasts with observed racial variability in anticoagulation efficacy and practice. Throughout we provide specific strategies for future directions to address gaps in the epidemiology of racial differences and to meet identified racial disparities. We specifically identify areas for further research. We conclude that addressing disparities in prevention and healthcare resource allocation will likely improve AF-related outcomes in minorities.

Atrial fi brillation in Middle Eastern Arab and South Asian patients hospitalized with acute myocardial infarction: experience from a 20-year Registry in Qatar (1991–2010)

Background Recent evidence suggests that there are ethnic variations in atrial fi brillation (AF) susceptibility and incidence following acute myocardial infarction (AMI).Objectives The aim of this study was to evaluate the incidence and predictors of AF in the setting of AMI in Middle Eastern Arab and South Asian patients and its impact on in-hospital morbidity and mortality.Methods A retrospective analysis of a prospective registry of all patients hospitalized with AMI in the state of Qatar from 1991 through 2010 was made. Clinical characteristics and outcomes of AMI patients with and without AF were compared. Sub-analysis according to ethnicity was also performed.Results During the 20-year period; a total of 12,881 patients were hospitalized with AMI. Of these 5028 were Arabs and 5985 were South Asians. A total of 227 had AF during hospitalization with an overall incidence of 1.8% (156 Arabs; incidence 3.1% and 48 South Asians; incidence 0.8%). The mean age of AF patients was 65 years (Arabs 69, South Asians 54). Patients with AF were signifi cantly older and had more cardiovascular co-morbidities than patients without AF, and were more likely to have non-ST elevation AMI on presentation. Patients with AF had signifi cantly higher in-hospital mortality rate (20.3% versus 7.1%; P= 0.001) and stroke rates (1.8% versus 0.3%; P= 0.001) when compared to patients without AF. Age was the only independent predictor of AF development in patients with AMI in our study.Conclusions Our study reports variability in the prevalence of AF among AMI patients according to ethnicity using a 20-year registry from a Middle Eastern country. Advancing age was the major independent predictor of AF in our AMI patients. Further prospective studies are required evaluating optimal therapeutic approaches for these high-risk patients in order to reduce the high mortality observed.

Impaired endothelial function in lone atrial fibrillation

Impaired endothelial function has been previously documented in patients with atrial fibrillation (AF) and underlying comorbidities or older patients with idiopathic AF. The aim of this study was to evaluate systemic endothelial function in younger AF patients (less than < 60 years old) with lone AF (that is, without associated cardiopulmonary comorbidities, including arterial hypertension), by comparing brachial artery flow-mediated dilation (FMD) in lone AF patients with FMD of healthy subjects in sinus rhythm. Two groups of participants were prospectively enrolled. The first group comprised of 38 AF patients (the mean age 45 +/- 11 years, 68% male) with persistent (> 7 days) lone AF. The second group comprised of 28 healthy controls in sinus rhythm (the mean age 43 +/- 13, 53% male), matched by age, gender and atherosclerotic risk factors. All the participants underwent physical examination, laboratory analysis [including determination of C-reactive protein (CRP)], standard echocardiography and exercise-stress testing. Brachial artery FMD and endothelium independent dilation (NMD) were assessed with a high-resolution ultrasound probe and arterial diameters taken from 5 consecutive cardiac cycles were averaged for each measurement to accommodate to beat-to-beat flow variations in AF. There were no differences between the 2 groups regarding age, gender and most clinical, laboratory and echocardiographic characteristics (all p > 0.05), apart from the increased heart rate (p = 0.018), body mass index (p = 0.027), CRP levels (p = 0.007) and left atrial anteroposterior dimension (p < 0.001) in AF patients. FMD of AF patients [median value 5.0%, interquartile range (IQR) 2.87%-7.50%] was significantly lower (p < 0.001) than FMD of healthy controls (median value 8.85%, IQR 5.80%-12.50%), whereas there were no differences in median NMD values (p > 0.05). In the multivariate analysis, the independent FMD determinants in our study population were the presence of AF, smoking and total cholesterol levels (all p < 0.001). In patients with AF, the strongest independent FMD determinant was arrhythmia duration (p < 0.001), followed by smoking (p = 0.013) and total cholesterol levels (p = 0.045). Our findings confirm that sustained AF is associated with systemic endothelial dysfunction even in relatively young patients with no cardiovascular disorders or risk factors. AF is an independent contributor to lower FMD and a prolonged arrhythmia duration may confer the risk for more profound endothelial damage.

Circadian variation in dominant atrial fibrillation frequency in persistent atrial fibrillation

Circadian variation in atrial fibrillation (AF) frequency is explored in this paper by employing recent advances in signal processing. Once the AF frequency has been estimated and tracked by a hidden Markov model approach, the resulting trend is analyzed for the purpose of detecting and characterizing the presence of circadian variation. With cosinor analysis, the results show that the short-term variations in the AF frequency exceed the variation that may be attributed to circadian. Using the autocorrelation method, circadian variation was found in 13 of 18 ambulatory ECG recordings (Holter) acquired from patients with long-standing persistent AF. Using the ensemble correlation method, the highest AF frequency usually occurred during the afternoon, whereas the lowest usually occurred during late night. It is concluded that circadian variation is present in most patients with long-standing persistent AF though the short-term variation in the AF frequency is considerable and should be taken into account.

Seasonal variation in AF-related admissions to a coronary care unit in a "hot" climate: fact or fiction?

Seasonal variations in atrial fibrillation (AF)-related morbidity and mortality have been demonstrated in "cold" northern European climates, but there are few data describing such a phenomenon in a "hot" climate. To examine the pattern of AF-related admissions to a coronary care unit (CCU) in South Australia operating within a Mediterranean climate, and to determine potential differences according to mean daily temperatures. PATIENT COHORT AND METHODS: A total of 144 admissions to the CCU during the 30 hottest and coldest days (60 days in total) during the calendar year 2001 were analyzed in respect to the absolute number of admissions and the profile of those admitted during "hot" and "cold" days. Overall, there were significantly more admissions to the CCU on "cold" as opposed to "hot" days (90 vs 54 patients in 30 days, P < or = .001). Of the 24 patients found to be in AF on presentation to hospital, 18 (75%) were admitted on cold days (P < .05). Alternatively, during "hot" days, patients were more likely to be diagnosed with unstable angina rather than acute myocardial infarction (46% vs 30%, P = .07) with proportionately fewer patients in AF at the time (11% vs 20%, P = NS). These preliminary data suggest that the phenomenon of seasonal variations in AF-related morbidity extend beyond colder climates to hotter climates with sufficiently large relative (as opposed to absolute) changes in ambient temperatures during the year.

Circadian variation in atrial fibrillation in patients with frequent paroxysms.

Determinants of the duration of episodes of atrial fibrillation (AF) in patients with paroxysmal atrial fibrillation (PAF) are poorly understood. However, autonomic tone shows circadian variation and is known to affect atrial electrophysiology. We therefore compared the duration of episodes of AF with an onset during the day (08:00-22:00) to those with an onset during the night in a database of 24-hour ECG recordings in patients with frequent symptomatic PAF. The heart rate in the 30 seconds prior to AF onset was also compared. From 42 recordings, 296 episodes of AF > 30 seconds duration and preceded by > 60 seconds sinus rhythm were identified. The 165 nocturnal episodes tended to be shorter (median = 1.15 min) than the 131 diurnal episodes (median = 1.5 min) and the distribution of nocturnal and diurnal durations was significantly different (P = 0.007; Kolgomorov-Smirnov test). This was also true in recordings containing at least 1 diurnal and at least 1 nocturnal episode. The mean heart rate prior to AF onset was lower at night (62.2 +/- 11.8 vs 75.6 +/- 16.4 beats/min; P < 0.0001 Wilcoxon test). These findings suggest that in patients with frequent symptomatic PAF, autonomic influences affect the duration of episodes of AF and has pathphysiological and therapeutic implications.

Computer analysis of myocardial tension and pressure variations in atrial fibrillation.

ARTICLESComputer analysis of myocardial tension and pressure variations in atrial fibrillationY. Mahler, and S. RogelY. Mahler, and S. RogelPublished Online:01 Jul 1970https://doi.org/10.1152/jappl.1970.29.1.77MoreSectionsPDF (1 MB)Download PDF ToolsExport citationAdd to favoritesGet permissionsTrack citations ShareShare onFacebookTwitterLinkedInWeChat Previous Back to Top Next Download PDF FiguresReferencesRelatedInformation Cited ByBeat-to-beat left ventricular performance in atrial fibrillation: Radionuclide assessment with the computerized nuclear probeThe American Journal of Cardiology, Vol. 51, No. 7Quantitative analysis of myocardial force and contractile state in in vivo rate and rhythm disturbancesJournal of Biomechanics, Vol. 14, No. 2 More from this issue > Volume 29Issue 1July 1970Pages 77-81 Copyright & PermissionsCopyright © 1970 the American Physiological Societyhttps://doi.org/10.1152/jappl.1970.29.1.77PubMed4912875History Published online 1 July 1970 Published in print 1 July 1970 Metrics