Does the novel SCAAF-ERS predict sudden cardiac arrest in patients with atrial fibrillation?
The novel SCAAF-ERS effectively predicts sudden cardiac arrest risk in patients with atrial fibrillation using five specific ECG parameters.
BACKGROUND Atrial fibrillation (AF) increases the risk of sudden cardiac arrest (SCA). Patients with AF are excluded from ECG risk predictor analyses for SCA due to their complex ECG. OBJECTIVE Develop an ECG risk score (ERS) to predict SCA in the population with AF. METHODS We performed a case-control study using SCA cases from a community-based study in Oregon, USA (population∼1 million; 2002-2020). Subjects aged ≥18 with medical records and pre-arrest ECGs showing AF were included. Controls had AF ECGs without SCA history. For validation, cases and controls were selected from a California study (population∼850,000; 2015-2023). Significant ECG variables were used to develop an ECG-based score for SCA risk prediction (SCAAF-ERS). RESULTS In the discovery group (447 cases, 138 controls; mean age 74.9 years; 73.5% male), the SCAAF-ERS (0-5) was developed by assigning one point for each significant factor: prolonged QTc, QRS-T angle >100°, Tpeak-Tend >94ms, LVH, and delayed QRS transition. Adjusting for demographics and comorbidities, SCA risk increased 1.5 times (95%CI: 1.2-1.9) per point increase. An SCAAF-ERS ≥4(16%) resulted in an OR of 12.9 (95%CI: 3.4-48.1). In the validation group (315 cases, 138 controls; mean age 77.7 years; 64.5% male), SCA risk doubled per point increase (OR: 2.4,95%CI: 1.9-3.1). An SCAAF-ERS ≥3 (27%) resulted an OR 22.9 (95%CI: 9.0-58.3). CONCLUSION SCA risk was predicted successfully from AF ECGs, with a novel risk score displaying 13 to 23-fold increased odds. Further validation of the SCAAF-ERS in larger, diverse populations is warranted.
Truyen et al. (Sun,) studied this question.