Electrophysiological Markers Predicting Antipsychotic Treatment Response in Patients with Schizophrenia: A Retrospective Study.

PURPOSE

This study aimed to provide an objective means of predicting treatment responses in patients with schizophrenia using quantitative electroencephalography (qEEG) as an electrophysiological indicator. We obtained qEEG recordings from patients with schizophrenia and explored them for patterns indicative of treatment responsiveness.

PATIENTS AND METHODS

The study included 68 patients had been diagnosed with schizophrenia spectrum disorder. After retrospectively gathering demographic information, clinical data such as qEEG, Positive and Negative Syndrome Scale (PANSS), a multiple regression analysis was performed. This analysis employed baseline qEEG findings as independent variables and PANSS score changes as dependent variables to discern causal relationships.

RESULTS

The mean age of the participants was 38.4 years( =13.73). The mean PANSS score on admission was 92.97, decreasing to 67.41 at discharge. Multiple regression analysis revealed that delta waves in T4 (β=0.346, t=3.165, p=0.002), and high-beta waves in Fp2 (β=0.231, t=2.361, p=0.021) were associated with PANSS changes in absolute power. In addition, the delta waves of O2 (β=0.250, t=3.288, p=0.002); beta waves of T3 (β=-1.463, t=-5.423, p<0.001) and O2 (β=0.551, t=3.366, p=0.001); high beta waves of Fp1 (β=0.307, t=4.026, p<0.001), T3 (β=0.855, t=4.414, p<0.001) and T6 (β=-0.838, t=-4.559, p<0.001) of absolute power using the Z-score were also related to PANSS changes. Pearson's correlation analysis showed that only delta waves at Cz (r= 0.246, p=0.043) in absolute power correlated with changes in the PANSS.

CONCLUSION

We found that certain qEEG wave patterns in patients with schizophrenia prior to antipsychotic treatment were linked to PANSS changes before and after treatment. Delta waves and beta waves, primarily in the frontal and temporal regions, were found to be significantly associated with changes in PANSS scores. In the future, the qEEG indicators identified in this study could serve as electrophysiological markers for predicting antipsychotic treatment responses in patients with schizophrenia.