The guiding significance of quantitative EEG parameters in adjusting treatment plans for Alzheimers disease

DOI: 10.12201/bmr.202501.00062

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  Abstract: AbstractObjective The guiding significance of studying quantitative EEG parameters for adjusting treatment plans for Alzheimers disease (AD). Methods 150 AD patients who visited our hospital from January 2023 to January 2024 were selected as the study group, and 150 healthy individuals were selected as the healthy group. The quantitative electroencephalogram parameters (DTABR) of δ+θ and α+β power ratio (DTABR) were obtained using Nicolet companys electroencephalograph in the United States. The differences in quantitative EEG parameters DTABR between the healthy group and the study group were compared, and the differences in quantitative EEG parameters DTABR among different AD patients were analyzed. All AD patients were treated with medication and/or non medication therapy based on the severity of their condition. The differences in quantitative EEG parameters (DTABR) among patients with different clinical efficacy were compared, and the risk factors affecting the ineffectiveness of AD treatment plans and the efficacy of DTABR in predicting the treatment efficacy of AD patients were analyzed. In addition, patients who received treatment in our hospital from May to June 2024 were used as validation subjects. According to the cutoff value of DTABR obtained from the ROC curve, the predicted treatment efficacy of AD patients was divided into a treatment plan adjustment group of 60 cases and a treatment plan maintenance group of 60 cases, and the clinical efficacy of the two groups was compared. Results The DTABR of the research group was higher than that of the healthy group (P<0.05). As the severity of AD patients increases, DTABR gradually increases, with severe and moderate patients having higher DTABR than mild patients, and severe patients having higher DTABR than moderate patients (P<0.05). Logistic regression analysis showed that age, disease duration, severity of illness, and DTABR were all risk factors for ineffective treatment in AD patients (P<0.05). By plotting ROC curves, it was found that compared with factors such as age, disease duration, and severity that affect the treatment efficacy of AD patients, DTABR showed significantly higher sensitivity and specificity in predicting the treatment efficacy of AD patients. The optimal predictive power was obtained when the value was 8.94, with sensitivity and specificity of 87.75% and 82.12%, respectively. Further analysis revealed that the combination of DTABR and factors such as age, disease duration, and severity had the best therapeutic effect on AD patients, significantly better than single factor prediction, with sensitivity and specificity of 93.50% and 85.46%, respectively. Conclusion There is a certain correlation between quantitative EEG parameters DTABR and the therapeutic efficacy of AD patients, which can be used for adjusting treatment plans and has guiding significance for treatment plans.

  Key words: Alzheimers disease; Quantitative EEG parameters; Treatment plan; Clinical efficacy

  Submit time: 21 January 2025

  Copyright: The copyright holder for this preprint is the author/funder, who has granted biomedRxiv a license to display the preprint in perpetuity.
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