Hypertrophic Cardiomyopathy Patients With Paroxysmal Atrial Fibrillation Have a High Burden of Left Atrial Fibrosis by Cardiac Magnetic Resonance Imaging

Sivalokanathan, Sanjay; Zghaib, Tarek; Greenland, Gabriela V.; Vasquez, Nestor; Kudchadkar, Shibani M.; Kontari, Effrosyni; Lu, Dai Yin; Dolores-Cerna, Ketty; Geest, Rob J. van der; Kamel, Ihab R.; Olgin, Jeffrey E.; Abraham, Theodore P.; Nazarian, Saman; Zimmerman, Stefan L.; Abraham, M. Roselle

doi:10.1016/j.jacep.2018.10.016

Cited by 68 publications

(55 citation statements)

References 27 publications

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“…[53][54][55] A recent CMR study in HCM patients reported greater amounts of LA fibrosis in HCM patients with PAF, as well as a positive association between atrial and ventricular fibrosis (LGE). [56] Since fibrosis slows conduction and predisposes to reentry, LA fibrosis would be expected to increase risk for AF.…”

Section: Discussionmentioning

confidence: 99%

“…Similar results of exercise intolerance in HCM patients with PAF have been reported in a previous study of 265 HCM patients during sinus rhythm [57] -here, the authors did not observe an association between lower exercise capacity and diastolic dysfunction or LA volume. Additionally, ECHO [58] and CMR [5,56] studies in HCM patients have revealed greater impairment of LA function and greater degree of LA fibrosis in HCM patients with PAF, suggesting that PAF is a marker of LA myopathy.…”

Section: Discussionmentioning

confidence: 99%

“…We grouped all AF cases (paroxysmal, persistent, permanent), as well as prevalent and incident AF into one set (because of low event number) and only included ECHO/CMR imaging features obtained at the patients' first clinic visit in the model. Left atrial volume, [46] LA strain, [58] LA fibrosis, [56] EKG/blood biomarkers, [66] genotype, [67][68][69] or sleep apnea were not included in our model, because this data is not available for a large proportion of our cohort. Lastly, we were unable to assess the generalizability of our approach by applying our developed model to additional HCM patients -beyond the cross-validation study, due to the unavailability of data from other HCM cohorts reported in other studies.…”

Section: Limitationsmentioning

confidence: 99%

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HCM-AF-Risk Model to Identify Cases and Predictors of Atrial Fibrillation in Hypertrophic Cardiomyopathy

Bhattacharya

Greenland

et al. 2020

Preprint

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Background AF in HCM is associated with high stroke risk despite low CHA2DS2-VASc scores. Hence, there is need to understand AF pathophysiology and predict AF in HCM. We develop/apply a data-driven, machine learning-based method to identify AF cases and clinical features associated with AF in HCM, using electronic health record (EHR) data. Methods Patients with documented paroxysmal/ persistent/permanent AF (n=191) were considered AF cases, and the remaining patients in sinus rhythm (n=640) were tagged as No-AF. We evaluated 93 clinical variables; the most informative variables useful for distinguishing AF from No-AF cases were selected based on the 2-sample t-test and information gain criterion. Results We identified 18 highly informative clinical variables: 11 are positively associated (e.g. LA-diameter, LV-diastolic dysfunction, LV-LGE), and 7 are negatively correlated (e.g. several exercise parameters) with AF in HCM. Next, patient records were represented via these 18 variables. Data imbalance resulting from the relatively low number of AF cases was addressed via a combination of over-and under-sampling strategies. We trained and tested multiple classifiers under this sampling approach, showing effective classification. Specifically, an ensemble of logistic regression and naïve Bayes classifiers, trained based on the 18 variables and corrected for data imbalance, proved most effective for separating AF from No-AF cases (sensitivity=0.74, specificity=0.72, C-index=0.80). Conclusions Our model (HCM-AF-Risk Model), the first machine learning-based method for identification of AF cases in HCM, demonstrates good performance, and suggests that AF is associated with a more severe cardiac HCM-phenotype.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Limitationsmentioning

confidence: 99%

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HCM-AF-Risk Model to Identify Cases and Predictors of Atrial Fibrillation in Hypertrophic Cardiomyopathy

Bhattacharya

Greenland

et al. 2020

Preprint

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“…In addition to the classical echocardiography parameters, the parameters of speckle tracking echocardiography (STE) have been started to be used for the evaluation of left atrial functions. In the paroxysmal atrial fibrillation (PAF) patient group; STE-based left atrial strain was correlated with fibrosis distribution as evaluated by cardiac magnetic resonance imaging (MRI) and, in another study, it was correlated with low voltage areas observed during radiofrequency mapping 8,9 .…”

Section: Introductionmentioning

confidence: 99%

Left Atrial Dispersion Predicts Atrial Fibrillation in Patients with Hypertrophic Cardiomyopathy: A 5-year Follow-up study

Candan

Çakmak

Geçmen

et al. 2020

Preprint

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Purpose:The aim of our study was to examine whether left atrial dispersion and left atrial strain as measured by speckle tracking echocardiography and clinic paramaters are predictors for the development of atrial fibrillation (AF) in patients with hypertrophic cardiomyopathy. Methods: A total of 137 patients (70% male, mean age 49.6 ± 14.2 years) with HCM were included in the study. Patients' clinical, electrocardiographic, 2D classic and speckle tracking echocardiographic (STE) data were collected. AF was searched by 12-lead electrocardiograms or 24-hour Holter recordings during follow-up period. Atrial dispersion was defined as the standard deviation of time to peak strain in 12 left atrial segments Results: During a follow-up period of 5 years 37 patients (16.9%) developed AF. At follow-up, the patients with occurrence of AF were older than in patients without AF. Atrial dispersion was observed to be higher in the AF developing group (61.4 ± 23.2 vs 43.1±15.8, p=<0.001). The multivariate in Cox regression analysis (including atrial dispersion, PALS, age, LA) atrial dispersion (msn) (HR 1.017, 95% CI: 1.001-1.03, p= 0.035) and age were found to be independent predictors of AF occurrence. In the ROC analysis atrial dispersion > 44.7 msn predicted occurrence of AF with 82.4% sensitivity and 64 % specificity. Conclusion: In patients with hypertrophic cardiomyopathy, atrial dispersion and age are predictive of the development of atrial fibrillation. Atrial dispersion measured by the speckle tracking-based method may provide further information in evaluating left atrial functions in patients with hypertrophic cardiomyopathy or other disease states

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“…[1,2] However, it has been reported that in HCM, LA dysfunction can occur as a myopathic process itself, irrespective of loading conditions. [4,5] In this regard, genetic contribution to LA structural and functional remodeling has not been well investigated.…”

Section: Introductionmentioning

confidence: 99%

Contribution of Sarcomere Gene Mutations to Left Atrial Function in Patients With Hypertrophic Cardiomyopathy

Chung

Kim

Park

et al. 2020

Preprint

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Background: Left atrial (LA) enlargement and dysfunction are related to clinical course in patients with hypertrophic cardiomyopathy (HCM). We aimed to investigate genetic contribution to LA structural and functional remodeling.Methods: 212 patients were consecutively enrolled, and echocardiography and extensive genetic analysis were performed. Cardiac magnetic resonance (CMR) was performed in 135 patients. Echocardiography was also performed in controls (n=30). Results: Patients with HCM had lower late-diastolic mitral annular velocity (a’) and higher LA volume index (LAVI) than controls. Patients with pathogenic or likely pathogenic sarcomere gene mutations (PSM, n = 67, 32%) had higher LAVI and lower CMR-derived LA total emptying fraction (37.0 ± 18.5 vs. 44.2 ± 12.4%, p=0.025). In patients without AF (n = 187), the PSM had lower a’ (6.9 ± 2.0 vs. 7.8 ± 1.9 cm/s, p = 0.004) than others. The PSM had higher prevalence and amount of late gadolinium enhancement (LGE) in the left ventricle (LV). In multivariate analysis, PSM was significantly related to lower a’ independent of E/e’, LV mass index, and LAVI. However, the relation significantly attenuated after adjustment for the extent of LGE in the LV, suggesting common myopathy in the LV and LA.Conclusions: PSM was related to LA dysfunction independent of LV filling pressure and LAVI, suggesting its contribution to atrial myopathy in HCM.

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Hypertrophic Cardiomyopathy Patients With Paroxysmal Atrial Fibrillation Have a High Burden of Left Atrial Fibrosis by Cardiac Magnetic Resonance Imaging

Cited by 68 publications

References 27 publications

HCM-AF-Risk Model to Identify Cases and Predictors of Atrial Fibrillation in Hypertrophic Cardiomyopathy

HCM-AF-Risk Model to Identify Cases and Predictors of Atrial Fibrillation in Hypertrophic Cardiomyopathy

Left Atrial Dispersion Predicts Atrial Fibrillation in Patients with Hypertrophic Cardiomyopathy: A 5-year Follow-up study

Contribution of Sarcomere Gene Mutations to Left Atrial Function in Patients With Hypertrophic Cardiomyopathy

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