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Table 1 Study characteristics

From: Validation of arrhythmogenic right ventricular cardiomyopathy risk calculator for sudden cardiac death: a systematic review

Author (year) [ref]

Study design

Sample size (n)

Age (years)

Males;n(%)

Comparator

SCD/Mortality; n(%)

Aborted cardiac arrest; n(%)

VT

Sensitivity/Specificity

Predictors of major events

Summary

Aquaro (2020) [1]

Retrospective cohort

140

42 ± 17

97 (69%)

1. ITFC consensus statement

2. HRS criteria

3. ARVC risk score

3 (2.14)

12 (8.57%)

17

ITFC criteria: sensitivity = 82%

Specificity = 52%

Positive predictive value = 60%

Negative predictive value = 76%

HRS criteria:

Sensitivity = 43%

Specificity = 84%

Positive predictive value = 70%

Negative predictive value = 62%

ARVC risk score:

Sensitivity = 95%

Specificity = 31%

Positive predictive value = 54%

Negative predictive value = 88%

NSVT

Syncope

ARVC risk score > 10%

Compared with the ITFC criteria, a 5 year ARVC score > 10% would have prevented 14% more events (P = 0.01) but with 25.8% more ICD implantations (P = 0.005). Compared with the HRS criteria, the 5 year ARVC score > 10% would have been capable of preventing 50% more events (P

 < 0.0001) but with almost three times more ICD implantations. The 5 year risk score > 10% had a greater net benefit compared with other thresholds of the risk score

Aquaro (2020) [2]

Retrospective cohort

140

42 ± 17

97 (69%)

1. CMR

2. ARVC risk score

3 (2.14)

13 (9.28)

Not reported

CMR:

Sensitivity = 75%

Specificity = 67%

Positive predictive value = 69%

ARVC risk score:

Sensitivity = 83%

Specificity = 39%

Positive predictive value = 55.7%

ARVC risk score

LV involvement

Left dominant ARVC presentation

No significant differences among groups were found for conventional arrhythmic risk factors such as NSVT, syncope, and previous aborted cardiac ar- rest, and for the 5-year ARVC risk score. However, patients with lone RV and those with a biventricular presentation had higher 24-h PVC count than those with a negative CMR. Patients with a LV-dominant presentation had a significantly lower RV end- diastolic volume index than others

Gasperetti (2020) [3]

Prospective cohort

25

36.16 ± 14

20 (80%)

1.2010 Task Force Criteria

2.ARVC risk score

Not reported

Not reported

7 (28)

Not reported

Not reported

The algorithm seems to account for the practice of high-end endurance sports and does not require specific adjustments. Mandatory clinical detraining has a positive effect on the 24 h/PVC burden and occurrence of dysrhythmia on stress ECG at mid-term follow-up, with no significant reverse remodeling of RVEF observed

Casella (2020) [4]

Retrospective cohort

101

41.3 ± 14.2

76 (75.3%)

1.ITFC risk assessment model

2.ARVC risk calculator

4 (3.9%)

Not reported

10 (9.9%)

Classical form 5 years/freedom-from-VA rate 0.76 (0.66–0.89); non-classical form 5 years/freedom-from-VA rate 0.58 (0.43–0.78)]

5-year risk thresholds between 15% (Same Net Benefit, better overall protection) and 20% (Better Net Benefit, same overall Protection)

VT inducibility

Viral genome

Late potentials

The novel Caudrin-Tourigny et al. algorithm appeared very effective in predicting long-term arrhythmic risk and in guiding ICD placement in this external validation cohort of probands with the classical ACM form requiring invasive investigation. In the non-classical forms, the algorithm appears to underestimate clinical risk; an integration with invasive assessment techniques, such as PES and EAM, should be considered in those forms presenting with an early left ventricular involvement

Baudinaud (2021) [5]

Retrospective cohort

128

38.2 (27.6–49.9)

84 (73%)

1.2015 ARVC Task Force Consensus

2.ARVC risk score

4 (3.47)

3 (2.6)

6 (5.21)

ARVC risk score:

Sensitivity = 80%

Specificity = 79%

Syncope

NSVT

T-wave inversion in anterior and inferior ECG leads

RVEF

LVEF

ARVC score

During a median follow-up of 7.8 years [IQR (6.1–9.7)], 15 (12%) patients experienced VA. The model provided good discrimination, with a Cindex for 5-year VA risk prediction of 0.84 [95% confidence interval (0.74–0.93)]. However, the model led to an overestimation of the 5-year VA risk when applying thresholds

Carrick (2022) [6]

Retrospective cohort

408

37 ± 15.1

164 (40.2%)

1.ARVC risk calculator

6 (1.5%)

Not reported

41 (10.0)

Cumulative VA-free survival at 5 years = 71.3%

LVEF

Anti-arrhythmic medications

Exercise

Beta-blockers

NSVT

T-wave inversion

RV dysfunction

On repeat ambulatory cardiac monitoring assessment, the prevalence of NSVT decreased by 14% and the burden of PVCs decreased by an average of 1200 PVC per 24 h. There was a nonsignificant trend toward increased prevalence of moderate to severe RV dysfunction. The C statistics of the modified ARVC risk calculator for 5-year VA events was 0.76 ± 0.02 and was similar to that of the original ARVC risk calculator (C statistics 0.78)

Jorda (2022) [7]

Retrospective cohort

429

43.1 + 15.8

235 (54.8%)

1.ARVC risk calculator

Not reported

103 (24)

Not reported

Model validation revealed a Harrell C-index of 0.70 (95% CI 0.65–0.75). The calibration slope was 1.01 (95% CI 0.99–1.03) showing no significant difference in discrimination

Age

Sex

PVC count

NSVT

T-wave inversion

Syncope

RV dysfunction

ARVC risk prediction model not only provides accurate prognostic information in patients with ARVC without a prior history of sustained VA at diagnosis, but also performs generally better than other published decision algorithms

Protonotarios (2022) [8]

Retrospective cohort

554

41.0 (27.2,53.1)

302 (54.5%)

1.ARVC risk score

9 (1.6%)

2 (0.4%)

37 (6.7%)

Uno’s concordance index 0.82, 95% CI 0.76–0.88; calibration curve slope 0.78, 95% CI 0.53–1.06; calibration curve intercept − 0.05, 95% CI − 0.10 to − 0.01

Sex

Syncope

T-wave inversion

PVC count

The corrected 2019 ARVC risk score has a reasonable discriminative ability but suffers from risk overestimation. It performs best among gene-positive patients and, especially in the PKP2 subgroup, but its utility is limited in gene-elusive patients. The predictive power of individual risk markers also varies by genotype