Meta-analysis on QEEG Changes to Antidepressant Treatment Among Patients with Depression.

Abstract

Introduction: Diagnostic and treatment accuracy of depression can lead to a better and possibly earlier response and remission in patients. The literature, though scanty, seems to suggest that quantitative electroencephalography (QEEG) can predict the outcome of antidepressant effects.

Methodology: Articles published between January 1990 and July 2019, including those dealing with QEEG recordings before and after the initiation of antidepressant medication, were included. The pooled effect size and subgroup analysis of waveforms were calculated to predict response to antidepressants.

Result: In all, 572 results were retrieved from the searches, of which 20 studies were included. Pooled data using a random-effects model (REM) calculated an effect size of 0.80 (95% CI [0.64-0.97]). Heterogeneity of the sample was low with Tau² = 0.02; df = 18 (P = .30); I² = 12%. Moreover, subgroup analysis showed that theta band frequencies were better at predicting response than alpha band frequencies (the standard mean difference [SMD] for theta was 0.91 compared to 0.68 for alpha waves).

Conclusions: QEEG is a valuable predictor of the antidepressant response. Among the EEG frequencies, the theta band showed the most significant change with treatment.