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Predictive value of electroencephalogram, event-related potential, and general movements quality assessment in
Qinfen Zhang1, Yongsu Hu1, Xuan Dong1
1Department of Neonatology, Affiliated Changzhou Children's Hospital of Nantong University, Changzhou, China.
Insights
Combining electroencephalogram (EEG), event-related potential (ERP), and general movements (GMs) quality assessment significantly improves neurodevelopmental outcome prediction in high-risk infants. This comprehensive approach offers the highest accuracy for identifying potential developmental issues early on.
Area of Science:
- Neonatal Neurology
- Developmental Neuroscience
- Pediatric Neurophysiology
Background:
- Early identification of neurodevelopmental impairments in high-risk infants is crucial for timely intervention.
- Traditional assessment methods may have limitations in predicting long-term outcomes accurately.
- Exploring multimodal assessment strategies can enhance predictive capabilities.
Purpose of the Study:
- To evaluate the predictive value of electroencephalogram (EEG), event-related potential (ERP), and general movements (GMs) quality assessment.
- To determine the combined predictive power of EEG, ERP, and GMs for neurodevelopmental outcomes at one year of age in high-risk infants.
- To compare the efficacy of individual and combined assessment methods.
Main Methods:
- High-risk infants underwent EEG and ERP assessments at four weeks of age.
- General movements (GMs) quality was assessed at four and twelve weeks.
- Neurodevelopmental outcome was evaluated using the Gesell score at one year.
- Comparative analysis of prediction accuracy using EEG, GMs, EEG+ERP, and EEG+ERP+GMs.
Main Results:
- The combined EEG+ERP+GMs method demonstrated the highest predictive accuracy, with sensitivity of 90.00% and specificity of 95.08%.
- This multimodal approach yielded the highest positive predictive value (75.00%) and negative predictive value (98.31%) compared to individual methods.
- The EEG+ERP+GMs method showed substantial reliability (Kappa=0.785) in predicting neurodevelopmental outcomes, outperforming other combinations.
Conclusions:
- The integration of EEG, ERP, and GMs quality assessment significantly enhances the prediction of neurodevelopmental outcomes in high-risk newborns.
- This combined approach offers a more robust and reliable tool for early identification of developmental trajectories.
- Multimodal neurophysiological and movement assessments are vital for comprehensive infant neurodevelopmental evaluation.
Objective:
The objective of the study is to investigate the predictive value of electroencephalogram (EEG), event-related potential (ERP), and general movements (GMs) quality assessment in the neurodevelopmental outcome of high-risk infants at one year old.
Methods:
EEG and ERP were performed in high-risk infants at four weeks old, and GMs quality was evaluated once at 4 weeks and once at 12 weeks. The Gesell score was used to assess neurodevelopment outcome at one year old. A comparative analysis of the effects of EEG, GMs, EEG + ERP, and EEG + ERP + GMs was used to predict high-risk neonatal neurodevelopmental outcome.
Results:
Of 71 high-risk infants at the age of one year, 3 (4.23%) had cerebral palsy, 14 (19.72%) had psychomotor retardation, and 54 (76.05%) were normal. The sensitivity, specificity, positive predictive value, and negative predictive value of EEG + ERP + GMs method were 90.00%, 95.08%, 75.00%, and 98.31%, respectively, and these indexes were the highest among the four methods (EEG, GMs, EEG + ERP, and EEG + ERP + GMs). The kappa statistic for the reliability of predicting neurodevelopmental outcome of high risk newborns by the EEG + ERP + GMs method was substantial at 0.785, while the other three methods obtained relatively low Kappa values (0.599, 0.586, and 0.712, respectively).
Conclusions:
The combination of EEG, ERP, and GMs quality assessment can greatly improve the prediction of neurodevelopmental outcome of high-risk newborns.
