Epilepsia OpenNeurosciencePeer-reviewed journal article
Prediction of treatment response in infantile epileptic spasms syndrome using EEG phase-amplitude coupling
Soudeh MostaghimiiD, Marco Antonio Pinto-OrellanaiD, Nathaniel GreeniD, Daniel W. ShreyiD, Makoto MiyakoshiiD, Shaun A. HussainiD, Beth A. LopouriD
Abstract
ObjectiveTreatment selection for infantile epileptic spasms syndrome (IESS) is complex and multifaceted, and currently no EEG biomarkers can guide this decision by predicting treatment response. We tested the predictive value of phase-amplitude coupling (PAC), as IESS patients are known to have elevated PAC. MethodsWe analyzed retrospective EEG recordings from 40 IESS patients, before and after treatment, and 20 healthy controls. Patients were classified as responders (n=25) or non-responders (n=15) based on short-term treatment outcomes. We measured PAC in each EEG using modulation index (MI) and mean vector length (MVL) and analyzed the relationship between pre- and post-treatment values and the ability of pre-treatment values to predict response. ResultsMI and MVL values decreased with treatment in almost all subjects. However, non-responders had significantly higher pre-treatment MI than responders (P<0.05), suggesting utility for predicting treatment response. Logistic regression modeling suggested that a 0.5 unit decrease in log(MI), which is approximately one IQR of the pre-treatment log(MI) values, results in a 6-fold increase in odds of positive treatment response. SignificanceMI reflects short-term treatment response and is a candidate predictive EEG biomarker for IESS. MI may offer individualized insights for treatment selection and management strategies for IESS. Key Points BoxO_LIInfantile epileptic spasms syndrome (IESS) is associated with high phase-amplitude coupling (PAC) that decreases with treatment C_LIO_LILow pre-treatment values of EEG PAC are predictive of positive short-term treatment response for IESS C_LIO_LIThe results were strongest when PAC was measured using the modulation index, as this method is known to be robust to noise C_LI
- organism: human
- assay: electronic health records
- research focus: drug response / drug discovery
- research focus: differential expression
- research focus: benchmarking
- approach: statistical model
- Citations
- 0
- FWCI
- 0.00
- Field percentile
- 14th percentile
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