Heart rate variability and microvolt T wave alternans changes during ajmaline test may predict prognosis in Brugada syndrome.
Brugada syndrome
Heart rate variability
Sudden cardiac death
T wave alternans
Journal
Clinical autonomic research : official journal of the Clinical Autonomic Research Society
ISSN: 1619-1560
Titre abrégé: Clin Auton Res
Pays: Germany
ID NLM: 9106549
Informations de publication
Date de publication:
02 2023
02 2023
Historique:
received:
20
07
2022
accepted:
03
01
2023
pubmed:
17
1
2023
medline:
8
3
2023
entrez:
16
1
2023
Statut:
ppublish
Résumé
Drug-induced type I Brugada syndrome (BrS) is associated with a ventricular arrhythmia (VA) rate of 1 case per 100 person-years. This study aims to evaluate changes in electrocardiographic (ECG) parameters such as microvolt T wave alternans (mTWA) and heart rate variability (HRV) at baseline and during ajmaline testing for BrS diagnosis. Consecutive patients diagnosed with BrS during ajmaline testing with 5-year follow-up were included in this study. For comparison, a negative ajmaline control group and an isoproterenol control group were also included. ECG recordings during ajmaline or isoproterenol test were divided in two timeframes from which ECG parameters were calculated: a 5-min baseline timeframe and a 5-min drug timeframe. A total of 308 patients with BrS were included, 22 (0.7%) of which suffered VAs during follow-up. One hundred patients were included in both isoproterenol and negative ajmaline control groups. At baseline, there was no difference in ECG parameters between control groups and patients with BrS, nor between BrS with and without VAs. During ajmaline testing, BrS with VAs presented longer QRS duration [159 ± 34 ms versus 138 (122-155) ms, p = 0.006], higher maximum mTWA [33.8 (14.0-114) µV versus 8.00 (3.67-28.2) µV, p = 0.001], and lower power in low frequency band [25.6 (5.8-53.8) ms Ajmaline induced important HRV changes similar to those observed during isoproterenol. Increased mTWA was observed only in patients with BrS. BrS with VAs during follow-up presented worse changes during ajmaline test, including lower LF power and higher maximum mTWA which were independent predictors of events.
Identifiants
pubmed: 36645559
doi: 10.1007/s10286-023-00922-4
pii: 10.1007/s10286-023-00922-4
doi:
Substances chimiques
Ajmaline
1PON08459R
Isoproterenol
L628TT009W
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
51-62Informations de copyright
© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany.
Références
Brugada P, Brugada J (1992) Right bundle branch block, persistent ST segment elevation and sudden cardiac death: a distinct clinical and electrocardiographic syndrome: a multicenter report. J Am Coll Cardiol 20:1391–1396
pubmed: 1309182
doi: 10.1016/0735-1097(92)90253-J
Probst V, Veltmann C, Eckardt L et al (2010) Long-term prognosis of patients diagnosed with Brugada syndrome. Circulation 121:635–643
pubmed: 20100972
doi: 10.1161/CIRCULATIONAHA.109.887026
Zeppenfeld k, Tfelt-Hansen j, de Riva M et al (2022) 2022 ESC Guidelines for the management of patients with ventricular arrhythmias and the prevention of sudden cardiac death: developed by the task force for the management of patients with ventricular arrhythmias and the prevention of sudden cardiac death of the European Society of Cardiology (ESC) Endorsed by the Association for European Paediatric and Congenital Cardiology (AEPC). Eur Heart J 43:3997–4126. https://doi.org/10.1093/eurheartj/ehac262
Priori SG, Gasparini M, Napolitano C et al (2012) Risk stratification in Brugada syndrome: results of the PRELUDE (PRogrammed ELectrical stimUlation preDictive valuE) registry. J Am Coll Cardiol 59:37–45
pubmed: 22192666
doi: 10.1016/j.jacc.2011.08.064
Chow J-J, Leong KMW, Yazdani M et al (2021) A multicenter external validation of a score model to predict risk of events in patients with Brugada syndrome. Am J Cardiol 160:53–59
pubmed: 34610873
doi: 10.1016/j.amjcard.2021.08.035
de Asmundis C, Mugnai G, Chierchia G-B et al (2017) Long-term follow-up of probands with Brugada syndrome. Am J Cardiol 119:1392–1400
pubmed: 28274576
doi: 10.1016/j.amjcard.2017.01.039
Sieira J, Ciconte G, Conte G et al (2017) Long-term prognosis of drug-induced Brugada syndrome. Heart Rhythm 14:1427–1433
pubmed: 28479512
doi: 10.1016/j.hrthm.2017.04.044
Russo V, Pafundi PC, Caturano A et al (2021) Electrophysiological study prognostic value and long-term outcome in drug-induced type 1 Brugada syndrome. JACC Clin Electrophysiol 7:1264–1273
pubmed: 33933405
doi: 10.1016/j.jacep.2021.03.010
Gray B, Kirby A, Kabunga P, Freedman SB, Yeates L, Kanthan A, Medi C, Keech A, Semsarian C, Sy RW (2017) Twelve-lead ambulatory electrocardiographic monitoring in Brugada syndrome: potential diagnostic and prognostic implications. Heart Rhythm 14:866–874
pubmed: 28528724
doi: 10.1016/j.hrthm.2017.02.026
Daw JM, Chahal CAA, Arkles JS et al (2022) Longitudinal electrocardiographic assessment in Brugada syndrome. Heart Rhythm O2. https://doi.org/10.1016/j.hroo.2022.01.011
doi: 10.1016/j.hroo.2022.01.011
pubmed: 36589910
pmcid: 9795306
Veltmann C, Schimpf R, Echternach C, Eckardt L, Kuschyk J, Streitner F, Spehl S, Borggrefe M, Wolpert C (2006) A prospective study on spontaneous fluctuations between diagnostic and non-diagnostic ECGs in Brugada syndrome: implications for correct phenotyping and risk stratification. Eur Heart J 27:2544–2552
pubmed: 16952922
doi: 10.1093/eurheartj/ehl205
Vitali F, Brieda A, Balla C, Pavasini R, Tonet E, Serenelli M, Ferrari R, Delise P, Rapezzi C, Bertini M (2021) Standard ECG in Brugada syndrome as a marker of prognosis: from risk stratification to pathophysiological insights. J Am Heart Assoc 10:e020767
pubmed: 33977759
pmcid: 8200706
doi: 10.1161/JAHA.121.020767
Delinière A, Baranchuk A, Giai J et al (2019) Prediction of ventricular arrhythmias in patients with a spontaneous Brugada type 1 pattern: the key is in the electrocardiogram. EP Eur 21:1400–1409
Delinière A, Baranchuk A, Bessière F et al (2020) Prognostic significance of a low T/R ratio in Brugada syndrome. J Electrocardiol 63:6–11
pubmed: 33011474
doi: 10.1016/j.jelectrocard.2020.08.023
Ueoka A, Morita H, Watanabe A, Morimoto Y, Kawada S, Tachibana M, Miyamoto M, Nakagawa K, Nishii N, Ito H (2018) Prognostic significance of the sodium channel blocker test in patients with Brugada syndrome. J Am Heart Assoc 7:e008617
pubmed: 29748178
pmcid: 6015319
doi: 10.1161/JAHA.118.008617
Pannone L, Monaco C, Sorgente A et al (2022) Ajmaline-induced abnormalities in Brugada syndrome: evaluation with ECG imaging. J Am Heart Assoc 11:e024001
pubmed: 35023354
pmcid: 9238512
doi: 10.1161/JAHA.121.024001
Rizzo A, Borio G, Sieira J et al (2020) Ajmaline testing and the Brugada syndrome. Am J Cardiol 135:91–98
pubmed: 32861732
doi: 10.1016/j.amjcard.2020.08.024
Antzelevitch C, Yan G-X, Ackerman MJ et al (2016) J-wave syndromes expert consensus conference report: emerging concepts and gaps in knowledge. Heart Rhythm 13:e295–324
pubmed: 27423412
pmcid: 5035208
doi: 10.1016/j.hrthm.2016.05.024
Sieira J, Conte G, Ciconte G et al (2017) A score model to predict risk of events in patients with Brugada syndrome. Eur Heart J. https://doi.org/10.1093/eurheartj/ehx119
doi: 10.1093/eurheartj/ehx119
pubmed: 29020354
Priori SG, Blomstrom-Lundqvist C, Mazzanti A et al (2015) 2015 ESC Guidelines for the management of patients with ventricular arrhythmias and the prevention of sudden cardiac death the task force for the management of patients with ventricular arrhythmias and the prevention of sudden cardiac death of the European Society of Cardiology (ESC) endorsed by: Association for European Paediatric and Congenital Cardiology (AEPC). Eur Heart J. https://doi.org/10.1093/eurheartj/ehv316
doi: 10.1093/eurheartj/ehv316
pubmed: 26745817
Kemp B, Olivan J (2003) European data format ‘plus’ (EDF+), an EDF alike standard format for the exchange of physiological data. Clin Neurophysiol 114:1755–1761
pubmed: 12948806
doi: 10.1016/S1388-2457(03)00123-8
Goldberger AL, Amaral LAN, Glass L, Hausdorff JM, Ivanov PCh, Mark RG, Mietus JE, Moody GB, Peng C-K, Stanley HE (2000) PhysioBank, PhysioToolkit, and PhysioNet. Circulation 101:e215–e220
pubmed: 10851218
doi: 10.1161/01.CIR.101.23.e215
Tarvainen MP, Niskanen J-P, Lipponen JA, Ranta-aho PO, Karjalainen PA (2014) Kubios HRV – heart rate variability analysis software. Comput Methods Programs Biomed 113:210–220
pubmed: 24054542
doi: 10.1016/j.cmpb.2013.07.024
Bauer A, Malik M, Schmidt G et al (2008) Heart rate turbulence: standards of measurement, physiological interpretation, and clinical use: International Society for Holter and Noninvasive Electrophysiology Consensus. J Am Coll Cardiol 52:1353–1365
pubmed: 18940523
doi: 10.1016/j.jacc.2008.07.041
Akaike H (1974) A new look at the statistical model identification. IEEE Trans Autom Control 19:716–723
doi: 10.1109/TAC.1974.1100705
Saito T, Rehmsmeier M (2015) The precision-recall plot is more informative than the ROC plot when evaluating binary classifiers on imbalanced datasets. PLoS One 10:e0118432
pubmed: 25738806
pmcid: 4349800
doi: 10.1371/journal.pone.0118432
Shaffer F, Ginsberg JP (2017) An overview of heart rate variability metrics and norms. Front Public Health 5:258
pubmed: 29034226
pmcid: 5624990
doi: 10.3389/fpubh.2017.00258
Goldstein DS, Bentho O, Park M-Y, Sharabi Y (2011) Low-frequency power of heart rate variability is not a measure of cardiac sympathetic tone but may be a measure of modulation of cardiac autonomic outflows by baroreflexes. Exp Physiol 96:1255–1261
pubmed: 21890520
pmcid: 3224799
doi: 10.1113/expphysiol.2010.056259
Pan Q, Zhou G, Wang R, Cai G, Yan J, Fang L, Ning G (2016) Do the deceleration/acceleration capacities of heart rate reflect cardiac sympathetic or vagal activity? A model study. Med Biol Eng Comput 54:1921–1933
pubmed: 27059998
doi: 10.1007/s11517-016-1486-9
Călburean P-A, Osório TG, Sieira J et al (2021) High parasympathetic activity as reflected by deceleration capacity predicts atrial fibrillation recurrence after repeated catheter ablation procedure. J Interv Card Electrophysiol 60:21–29
pubmed: 31912449
doi: 10.1007/s10840-019-00687-9
Călburean P-A, Osorio TG, Sorgente A et al (2021) High vagal tone predicts pulmonary vein reconnection after cryoballoon ablation for paroxysmal atrial fibrillation. Pacing Clin Electrophysiol 44:2075–2083
pubmed: 34773413
doi: 10.1111/pace.14408
Fauchier L, Babuty D, Autret L, Poret P, Cosnay P, Fauchier JP (1998) Effect of flecainide on heart rate variability in subjects without coronary artery disease or congestive heart failure. Cardiovasc Drugs Ther 12:483–486
Myerburg RJ, Kessler KM, Cox MM, Huikuri H, Terracall E, Interian A, Fernandez P, Castellanos A (1989) Reversal of proarrhythmic effects of flecainide acetate and encainide hydrochloride by propranolol. Circulation 80:1571–1579
pubmed: 2480856
doi: 10.1161/01.CIR.80.6.1571
Alboni P, Paparella N, Cappato R, Candini GC (1988) Direct and autonomically mediated effects of oral flecainide. Am J Cardiol 61:759–763
pubmed: 3128098
doi: 10.1016/0002-9149(88)91062-4
Echt DS, Liebson PR, Mitchell LB et al (1991) Mortality and morbidity in patients receiving encainide, flecainide, or placebo. N Engl J Med 324:781–788
pubmed: 1900101
doi: 10.1056/NEJM199103213241201
Bacic D, Carneiro JS, Bento AA, Nearing BD, Rajamani S, Belardinelli L, Verrier RL (2017) Eleclazine, an inhibitor of the cardiac late sodium current, is superior to flecainide in suppressing catecholamine-induced ventricular tachycardia and T-wave alternans in an intact porcine model. Heart Rhythm 14:448–454
pubmed: 27777148
doi: 10.1016/j.hrthm.2016.10.021
Pham Q, Quan KJ, Rosenbaum DS (2003) T-wave alternans: marker, mechanism, and methodology for predicting sudden cardiac death. J Electrocardiol 36:75–81
pubmed: 14716596
doi: 10.1016/j.jelectrocard.2003.09.018
Richter S, Duray G, Hohnloser SH (2005) How to analyze T-wave alternans. Heart Rhythm 2:1268–1271
pubmed: 16253922
doi: 10.1016/j.hrthm.2005.07.020
Nakamura M, Isobe M, Imamura H (1998) Incessant ventricular fibrillation attacks in a patient with Brugada syndrome. Int J Cardiol 64:205–206
pubmed: 9688440
doi: 10.1016/S0167-5273(98)00014-X
Maury P, Couderc P, Delay M, Boveda S, Brugada J (2004) Electrical storm in Brugada syndrome successfully treated using isoprenaline. Europace 6:130–133
pubmed: 15018871
doi: 10.1016/j.eupc.2003.11.009
Krittayaphong R, Veerakul G, Nademanee K, Kangkagate C (2003) Heart rate variability in patients with Brugada syndrome in Thailand. Eur Heart J 24:1771–1778
pubmed: 14522573
doi: 10.1016/j.ehj.2003.06.005
Tokuyama T, Nakano Y, Awazu A et al (2014) Deterioration of the circadian variation of heart rate variability in Brugada syndrome may contribute to the pathogenesis of ventricular fibrillation. J Cardiol 64:133–138
pubmed: 24495503
doi: 10.1016/j.jjcc.2013.12.001
Bloomfield DM, Steinman RC, Namerow PB et al (2004) Microvolt T-wave alternans distinguishes between patients likely and patients not likely to benefit from implanted cardiac defibrillator therapy. Circulation 110:1885–1889
pubmed: 15451804
doi: 10.1161/01.CIR.0000143160.14610.53
Sakamoto S, Takagi M, Tatsumi H, Doi A, Sugioka K, Hanatani A, Yoshiyama M (2016) Utility of T-wave alternans during night time as a predictor for ventricular fibrillation in patients with Brugada syndrome. Heart Vessels 31:947–956
pubmed: 25989739
doi: 10.1007/s00380-015-0692-y
Tada T, Kusano KF, Nagase S, Banba K, Miura D, Nishii N, Watanabe A, Nakamura K, Morita H, Ohe T (2008) Clinical significance of macroscopic T-wave alternans after sodium channel blocker administration in patients with Brugada syndrome. J Cardiovasc Electrophysiol 19:56–61
pubmed: 17916151
Pannone L, Monaco C, Sorgente A et al (2022) High-density epicardial mapping in Brugada syndrome: depolarization and repolarization abnormalities. Heart Rhythm 19:397–404
pubmed: 34601129
doi: 10.1016/j.hrthm.2021.09.032
Pastore JM, Girouard SD, Laurita KR, Akar FG, Rosenbaum DS (1999) Mechanism linking T-wave alternans to the genesis of cardiac fibrillation. Circulation 99:1385–1394
pubmed: 10077525
doi: 10.1161/01.CIR.99.10.1385
Pannone L, Monaco C, Sorgente A et al (2022) SCN5A mutation in Brugada syndrome is associated with substrate severity detected by electrocardiographic imaging and high-density electroanatomic mapping. Heart Rhythm 19:945–951
pubmed: 35124229
doi: 10.1016/j.hrthm.2022.01.034
Monaco C, Galli A, Pannone L et al (2022) Hybrid-approach ablation in drug-refractory arrhythmogenic right ventricular cardiomyopathy. Am J Cardiol 181:45–54
pubmed: 35973836
doi: 10.1016/j.amjcard.2022.07.011
Brugada J, Campuzano O, Arbelo E, Sarquella-Brugada G, Brugada R (2018) Present status of Brugada syndrome. J Am Coll Cardiol 72:1046–1059
pubmed: 30139433
doi: 10.1016/j.jacc.2018.06.037
Călburean P-A, Grebenișan P, Nistor I-A et al (2022) Prediction of 3-year all-cause and cardiovascular cause mortality in a prospective percutaneous coronary intervention registry: machine learning model outperforms conventional clinical risk scores. Atherosclerosis 350:33–40
pubmed: 35483116
doi: 10.1016/j.atherosclerosis.2022.03.028