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Predicting upper limb motor dysfunction after ischemic stroke: a functional near-infrared spectroscopy-based nomogram

Menghui Liu1, Chunxiao Wan1, Chunyan Wang1

  • 1Department of Rehabilitation Medicine, Tianjin Medical University General Hospital, Tianjin, China.

Frontiers in Neurology
|June 11, 2025
PubMed
Summary

This study identified five independent functional near-infrared spectroscopy (fNIRS) risk factors for upper limb motor recovery in ischemic stroke patients. A predictive model using fNIRS data aids clinical decision-making for stroke rehabilitation.

Keywords:
functional near-infrared spectroscopyischemic strokenomogrampredictive modelupper limb motor function

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Area of Science:

  • Neuroscience
  • Medical Imaging
  • Rehabilitation Medicine

Background:

  • Ischemic stroke frequently results in upper limb motor dysfunction.
  • Predicting motor functional recovery is crucial for effective stroke rehabilitation.
  • Functional near-infrared spectroscopy (fNIRS) offers a non-invasive method for assessing brain activity.

Purpose of the Study:

  • To identify independent risk factors for upper limb motor functional recovery 3 months post-ischemic stroke.
  • To develop a predictive model for upper limb motor dysfunction using fNIRS data.
  • To enhance clinical decision-making and treatment planning for stroke patients.

Main Methods:

  • 114 ischemic stroke patients were analyzed, split into training (n=80) and validation (n=34) groups.
  • LASSO and logistic regression analyses were used on fNIRS data to identify independent risk factors.
  • A nomogram was constructed to predict motor dysfunction, with model performance evaluated by ROC curve (AUC) and decision curve analysis (DCA).

Main Results:

  • Five independent fNIRS-derived risk factors were identified, including brain functional connectivity patterns.
  • The predictive model demonstrated strong discriminative ability with an AUC of 0.971 (training) and 0.804 (testing).
  • Decision curve analysis confirmed the model's good clinical utility in both cohorts.

Conclusions:

  • A novel predictive model based on fNIRS data was successfully developed for upper limb motor functional recovery after ischemic stroke.
  • The model effectively forecasts risk factors, aiding clinicians in personalized treatment strategies.
  • This pilot study provides a valuable tool for improving outcomes in stroke rehabilitation.