Predicting postictal suppression in electroconvulsive therapy using analysis of heart rate variability.

BACKGROUND

Postictal suppression on an electroencephalogram (EEG) represents electrical silence during electroconvulsive therapy (ECT) and has been considered as a key feature associated with the efficacy of treatment. The present study aimed to predict postictal suppression using heart rate variability (HRV).

METHODS

Participants comprised 21 consecutive patients with depression who underwent bilateral pulse wave ECT. We analyzed the frequency domains of resting HRV before ECT. HRV indices such as the high-frequency component (HF) reflecting parasympathetic activity and the ratio of low-frequency component (LF)/HF reflecting sympathetic activity were natural log transformed for analysis. We evaluated ictal and peri-ictal EEG parameters and investigated their associations with HRV indices.

RESULTS

Postictal suppression and regularity were positively associated with ln[HF]. Postictal suppression remained significantly associated with ln[HF] after adjusting for age in multiple regression analysis of patients with depression.

LIMITATIONS: The present study could not examine the influence of diabetes mellitus, hypertension and polarity on HRV. In addition, the small sample size resulted in low statistical power.

CONCLUSIONS

These results suggested that ln[HF] before ECT could be utilized as a predictor of postictal suppression on EEG during ECT.