Risk Stratification in Brugada Syndrome: Where Scores Meet Biomarkers

Brugada syndrome remains one of the most enigmatic primary electrical disorders of the heart, carrying a polymorphic ventricular tachycardia and sudden cardiac death risk that often strikes without warning in otherwise healthy young adults. Across Australia and the Asia-Pacific region, clinicians managing families affected by an SCN5A mutation or a coved-type ST-segment elevation have learned that the clinical trajectory of this sodium channelopathy is far more variable than its reputation suggests. Stratifying arrhythmic risk has therefore moved beyond the simple presence of a type 1 pattern, towards an integrated reading of clinical, electrocardiographic, genetic and biochemical cues.

This synthesis reflects a broader shift in arrhythmia medicine: away from binary labels of "affected" or "unaffected," and towards probabilistic estimates of near-term events. Readers of special issue collections on inherited arrhythmia syndromes will recognise how rapidly the evidence base is evolving, and how scoring systems are being recalibrated against data from registries in Europe, Japan, and now Australia.

Foundations of Brugada Syndrome and Risk Assessment

The substrate in Brugada syndrome centres on a subtle but functionally important reduction in sodium current, most often encoded by SCN5A but increasingly attributed to a wider panel of genes including GPD1L, SCN1B and CACNA1C. Reduced inward sodium flux exaggerates the transmural voltage gradient between epicardium and endocardium in the right ventricular outflow tract, creating the substrate for phase 2 re-entry and polymorphic ventricular tachycardia. Australian electrophysiologists at the Royal Melbourne Hospital and Royal Prince Alfred in Sydney have participated in multicentre registries that confirmed a male predominance, a mean age of arrhythmic presentation around 40 years, and a meaningful contribution of fever as an arrhythmic trigger.

Arrhythmic risk stratification in this condition asks a deceptively simple question: who, among genotype-positive or phenotype-positive patients, will experience ventricular fibrillation or sudden death, and when? The answer shapes decisions about lifestyle modification, antiarrhythmic drug prescription, electrophysiology study referral, and the timing of implantable cardioverter-defibrillator implantation. Unlike many other inherited arrhythmia syndromes, Brugada syndrome requires a graded rather than categorical approach.

Established Clinical Scoring Systems

Several risk models have been proposed to address this graded decision-making. The Shanghai Brugada Score, the Sieira score from the FINGER registry, and the more recent EHRAS-derived BrS Risk Calculator each attempt to weight clinical variables such as syncope, family history of sudden death, type 1 ECG pattern documentation, and inducibility on programmed electrical stimulation. The Sieira cohort suggested that a combination of spontaneous type 1, history of syncope, and inducibility on ventricular stimulation identified high-risk individuals with reasonable discrimination, though the positive predictive value remained modest.

Practising cardiologists in Brisbane and Perth have pointed out that these tools were derived from Mediterranean and Northeast Asian cohorts, leaving the question of how well they translate to a population with diverse ethnic backgrounds, including the significant Southeast Asian migrant communities along Australia's eastern seaboard. Re-calibration using the CSANZ-affiliated national arrhythmia registry may eventually improve precision, but for the moment, scoring systems work best as adjuncts rather than arbiters.

Electrocardiographic Refinements and Signal-Averaged ECG

Beyond the binary reading of a type 1 pattern, the surface electrocardiogram contains a wealth of additional information. Parameters such as QRS duration in the precordial leads, fragmented QRS morphology, early repolarisation in inferolateral leads, and the aVR sign have all been investigated as modifiers of arrhythmic risk. A prolonged peripheral and precordial QRS duration, fragmented QRS, and the presence of a prominent S wave in lead aVR have all correlated with a higher likelihood of inducible ventricular fibrillation in pooled analyses.

Signal-averaged ECG adds another dimension, detecting late potentials that reflect delayed activation within the right ventricular substrate. Although its standalone predictive value is debated, late potentials can refine risk estimates when combined with clinical features. Heart rhythm trainees attending CSANZ-endorsed courses in Adelaide are now routinely taught to integrate these ECG features into their decision matrix before considering more invasive strategies.

Genetic and Molecular Determinants of Risk

Genotype alone does not, in its current form, dictate risk stratification in Brugada syndrome. While SCN5A loss-of-function variants are the most frequent finding, their presence is neither necessary nor sufficient for arrhythmic events. Variant type, location within the channel, biophysical consequence, and the patient's genetic background all modify the phenotype, with some variants producing a more severe sodium current reduction and a higher arrhythmic load.

Larger next-generation sequencing panels also reveal polygenic modifiers, including common variants in SCN10A and HEY2 that shift the population baseline of conduction and repolarisation. In Australian diagnostic laboratories accredited by the National Association of Testing Authorities, reporting of these variants in inherited arrhythmia panels is increasingly nuanced, balancing their statistical association with disease against the practical needs of clinical decision-makers. Methodological lessons can also be drawn from WPW ablation outcomes in Wolff-Parkinson-White syndrome, where substrate characterisation at invasive electrophysiology study has long informed the literature on arrhythmic substrate mapping.

Imaging-Based and Structural Substrate Findings

Cardiac magnetic resonance imaging has challenged older perceptions that Brugada syndrome represents a purely electrical disorder without structural correlates. Subtle abnormalities of the right ventricular outflow tract, including regional wall motion irregularities and areas of fibrofatty replacement, are now visible on dedicated sequences in a subset of patients. Such findings correlate with both ECG markers of conduction delay and inducibility at electrophysiology study.

In centres such as the Victor Chang Cardiac Research Institute in Sydney, investigators have explored quantitative techniques such as T1 mapping, extracellular volume assessment, and strain analysis to detect these microstructural changes. While none of these imaging parameters yet occupies a central place in routine risk scores, they help triage patients in whom the diagnosis is uncertain or in whom overlapping phenotypes are being considered.

Circulating Biomarkers and Inflammation-Linked Signatures

A particularly active area of research focuses on circulating biomarkers that reflect myocardial stress, inflammation, and autonomic modulation. Elevated high-sensitivity C-reactive protein, interleukin-6, and tumour necrosis factor alpha have been linked to arrhythmic storm presentations, and some small studies suggest that baseline inflammation predicts future events. Markers of myocardial injury such as high-sensitivity troponin, B-type natriuretic peptide, and galectin-3 are being evaluated for additive prognostic value.

Autonomic markers, including heart rate turbulence and deceleration capacity, capture vagal withdrawal that often precedes arrhythmic episodes. In Australian outpatient practice, where patients from Hobart to Darwin are increasingly monitored remotely, wearable devices that feed back these indices into electronic records are extending the reach of biomarker-based risk assessment into regional and remote communities. Continuous telemetry infrastructure is also a prerequisite for newer pacing modalities, where ongoing evaluation of competing conduction strategies continues to shape the field.

Integrating Multimodal Risk Models Into Practice

The most defensible contemporary approach combines clinical, electrocardiographic, and genetic variables into a probabilistic estimate of arrhythmic risk, with biomarkers and imaging parameters serving as supplementary evidence. A typical decision pathway might begin with risk score calculation, supplement it with ECG markers and late potentials, add genotype data where available, and reserve cardiac magnetic resonance and programmed electrical stimulation for equivocal cases. Therapeutic choices, from lifestyle modification and fever control to quinidine therapy and device implantation, are then matched to the gradient of estimated risk rather than the diagnostic label alone.

For physicians weighing alternative conduction system pacing strategies in patients with reduced left ventricular function, comparative data such as His-bundle pacing outcomes in heart failure offer useful context, even though they fall outside the inherited arrhythmia space. Such comparative data influence how electrophysiologists think about patient selection, follow-up intensity, and the threshold for upgrading from ICD to additional pacing support.

Clinicians in Australia navigate these decisions through Medicare-funded specialist consultations, with device implantation and ablation procedures governed by TGA regulations and CSANZ position statements. Pulse generator replacement, remote monitoring infrastructure, and access to electrophysiology laboratories in regional centres vary substantially across states, prompting ongoing advocacy for equitable care. As evidence accumulates, the algorithms of tomorrow will likely combine artificial-intelligence-driven ECG analysis, refined biomarker panels, and genetic risk modifiers into a single transparent score that guides therapy across health systems.

For readers keen to track the latest multicentre data and consensus updates, exploring the journal's themed collections on inherited arrhythmias is an excellent next step, alongside monitoring forthcoming CSANZ recommendations on genetic testing and device implantation thresholds in this challenging syndrome.