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Background and objectives <p>Accurate prediction of motor recovery after acute ischemic stroke remains challenging. We investigated whether integrating serum neurotrophin profiles with quantitative electroencephalography (qEEG) parameters enhances predictive accuracy for 6-month motor outcomes beyond conventional clinical predictors.</p> Methods <p>This prospective observational study enrolled 108 patients with first-ever acute ischemic stroke admitted within 24&#xa0;h of symptom onset between December 2023 and December 2024. Serum brain-derived neurotrophic factor (BDNF) and nerve growth factor (NGF) were measured at admission (Day 1) and Day 3. qEEG recording was performed within 72&#xa0;h, with calculation of delta-alpha ratio (DAR), delta-theta/alpha-beta ratio (DTABR), and brain symmetry index (BSI). The primary outcome was motor function at 6 months assessed by Fugl-Meyer Assessment upper extremity score (FMA-UE), dichotomized as good (FMA-UE ≥ 50) or poor (FMA-UE &lt; 50) outcome. Multivariate logistic regression models were developed and compared using receiver operating characteristic analysis.</p> Results <p>At 6-month follow-up, 64 patients (59.3%) achieved good motor outcome. Patients with good outcome demonstrated significantly higher BDNF levels at Day 1 (14.05 ± 5.30 vs. 10.97 ± 4.58 ng/mL, <i>P</i> = 0.002) and lower DAR (median 0.42 [IQR 0.22–0.61] vs. 0.83 [0.56–1.16], <i>P</i> &lt; 0.001) compared with poor outcome group. The clinical-only model (Model 1: comprising age, sex, NIHSS, ASPECTS, reperfusion therapy, and diabetes mellitus) achieved a cross-validated area under the receiver operating characteristic curve (AUC) of 0.884 (95% CI: 0.862–0.907). Addition of neurotrophin biomarkers improved cross-validated AUC to 0.903 (95% CI: 0.877–0.928), while addition of qEEG parameters yielded cross-validated AUC of 0.922 (95% CI: 0.901–0.943). The combined model integrating clinical variables, neurotrophins, and qEEG achieved the highest discriminative performance (cross-validated AUC = 0.930, 95% CI: 0.908–0.952) with sensitivity of 92.2% and specificity of 93.2% at the optimal threshold.</p> Conclusions <p>A multimodal prediction model combining serum neurotrophin profiles and qEEG parameters provides incremental improvement in prognostic accuracy for motor outcomes in acute ischemic stroke, though differences in discriminative performance between models did not reach statistical significance in this sample. This integrated approach may facilitate individualized rehabilitation planning and resource allocation in clinical practice.</p>

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Integrating serum neurotrophin profiles and quantitative EEG for predicting motor outcomes in acute ischemic stroke

  • 期刊论文

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  • 发表日期：

    2026年7月8日

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  • Yuyuan Lu,
  • Yuchen Guo,
  • Songhua Ma

摘要

Background and objectives

Accurate prediction of motor recovery after acute ischemic stroke remains challenging. We investigated whether integrating serum neurotrophin profiles with quantitative electroencephalography (qEEG) parameters enhances predictive accuracy for 6-month motor outcomes beyond conventional clinical predictors.

Methods

This prospective observational study enrolled 108 patients with first-ever acute ischemic stroke admitted within 24 h of symptom onset between December 2023 and December 2024. Serum brain-derived neurotrophic factor (BDNF) and nerve growth factor (NGF) were measured at admission (Day 1) and Day 3. qEEG recording was performed within 72 h, with calculation of delta-alpha ratio (DAR), delta-theta/alpha-beta ratio (DTABR), and brain symmetry index (BSI). The primary outcome was motor function at 6 months assessed by Fugl-Meyer Assessment upper extremity score (FMA-UE), dichotomized as good (FMA-UE ≥ 50) or poor (FMA-UE < 50) outcome. Multivariate logistic regression models were developed and compared using receiver operating characteristic analysis.

Results

At 6-month follow-up, 64 patients (59.3%) achieved good motor outcome. Patients with good outcome demonstrated significantly higher BDNF levels at Day 1 (14.05 ± 5.30 vs. 10.97 ± 4.58 ng/mL, P = 0.002) and lower DAR (median 0.42 [IQR 0.22–0.61] vs. 0.83 [0.56–1.16], P < 0.001) compared with poor outcome group. The clinical-only model (Model 1: comprising age, sex, NIHSS, ASPECTS, reperfusion therapy, and diabetes mellitus) achieved a cross-validated area under the receiver operating characteristic curve (AUC) of 0.884 (95% CI: 0.862–0.907). Addition of neurotrophin biomarkers improved cross-validated AUC to 0.903 (95% CI: 0.877–0.928), while addition of qEEG parameters yielded cross-validated AUC of 0.922 (95% CI: 0.901–0.943). The combined model integrating clinical variables, neurotrophins, and qEEG achieved the highest discriminative performance (cross-validated AUC = 0.930, 95% CI: 0.908–0.952) with sensitivity of 92.2% and specificity of 93.2% at the optimal threshold.

Conclusions

A multimodal prediction model combining serum neurotrophin profiles and qEEG parameters provides incremental improvement in prognostic accuracy for motor outcomes in acute ischemic stroke, though differences in discriminative performance between models did not reach statistical significance in this sample. This integrated approach may facilitate individualized rehabilitation planning and resource allocation in clinical practice.