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Risk factors for post-stroke spasticity: a retrospective study.

Chuanxi Zhu1, Lingxu Li1, Long Qiu1,2

  • 1Department of Rehabilitation Medicine, Changchun University of Chinese Medicine, Changchun, Jilin, China.

Frontiers in Neurology
|January 6, 2025
PubMed
Summary

Post-stroke spasticity (PSS) is common and disabling. Key risk factors include basal ganglia lesions, lesion volume, and NIHSS scores, enabling early detection and treatment.

Keywords:
influence factorspost-stroke spasticityretrospective studyspasticitystroke

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Area of Science:

  • Neurology
  • Stroke Rehabilitation
  • Clinical Medicine

Background:

  • Post-stroke spasticity (PSS) is a frequent complication following stroke, contributing significantly to long-term disability.
  • Early detection and treatment are crucial for managing PSS and mitigating its functional impact.
  • Identifying risk factors for PSS can facilitate timely intervention and improve patient outcomes.

Purpose of the Study:

  • To identify independent risk factors for the development of post-stroke spasticity (PSS).
  • To develop a predictive model for PSS in stroke patients.
  • To aid in the early detection and management of PSS.

Main Methods:

  • Retrospective study analyzing 257 stroke patients admitted between June 2020 and November 2020.
  • Patients were categorized into spasticity (101 cases) and non-spasticity (156 cases) groups.
  • Multivariate logistic regression and ROC curve analysis were employed to identify risk factors and assess model fit.

Main Results:

  • Basal ganglia lesions (hemorrhage or infarction), lesion volume, and NIHSS scores were identified as independent risk factors for PSS (p < 0.05).
  • A predictive model for PSS was developed using these factors: Logit(P) = 1.595 * Basal ganglia + 0.084 * infarct volume + 0.208 * NIHSS scores - 2.092.
  • The risk prediction model demonstrated a high degree of fit, with an AUC of 0.786 (95% CI: 0.730-0.843).

Conclusions:

  • Basal ganglia lesion site, lesion volume, and NIHSS scores are significant independent risk factors for post-stroke spasticity.
  • The developed risk prediction model shows promise for identifying stroke patients at higher risk of developing spasticity.
  • These findings support the 'early detection, early treatment' consensus for PSS management.