Neurological research · 2026
Predictive value of neuroelectrophysiological parameters for respiratory failure in Guillain-Barré syndrome patients.
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Zeng Jing, Lin Chuxin, Ye Jiasheng, Feng Shuxing, Tang Zhiming, Liu Xingchen
Аннотация
OBJECTIVE: To evaluate the predictive value of parameters derived from nerve conduction studies (NCS) for respiratory failure in patients with Guillain-Barré syndrome (GBS).
METHODS: We conducted a retrospective analysis of 213 patients with GBS admitted between January 2020 and August 2023. Patients were categorized into respiratory failure (n = 92) and non-respiratory failure groups (n = 121). Demographic, clinical, and neuro-electrophysiological parameters were compared. Multivariate logistic regression analysis was performed to identify independent predictors of respiratory failure. The model's predictive performance was assessed using receiver operating characteristic (ROC) curve analysis.
RESULTS: Among 213 GBS patients (92 with respiratory failure, 121 without), multivariate logistic regression analysis identified two independent electrophysiological predictors of respiratory failure: slower peroneal motor conduction velocity (MCV, OR = 0.230, 95% CI: 0.063-0.838, p = .026) and slower tibial MCV (OR = 0.640, 95% CI: 0.539-0.760, p = .032). The predictive model demonstrated excellent discriminative ability with an AUC of 0.947 (95% CI: 0.921-0.973), sensitivity of 81.8%, and specificity of 95.7%. Patients with respiratory failure also had significantly higher Hughes functional scores (p < 0.001).
CONCLUSION: Motor conduction velocities of the peroneal and tibial nerves provide reliable and objective predictors for respiratory failure in GBS patients. Incorporating these markers into early risk assessment may facilitate prompt intervention and improve clinical outcomes.
METHODS: We conducted a retrospective analysis of 213 patients with GBS admitted between January 2020 and August 2023. Patients were categorized into respiratory failure (n = 92) and non-respiratory failure groups (n = 121). Demographic, clinical, and neuro-electrophysiological parameters were compared. Multivariate logistic regression analysis was performed to identify independent predictors of respiratory failure. The model's predictive performance was assessed using receiver operating characteristic (ROC) curve analysis.
RESULTS: Among 213 GBS patients (92 with respiratory failure, 121 without), multivariate logistic regression analysis identified two independent electrophysiological predictors of respiratory failure: slower peroneal motor conduction velocity (MCV, OR = 0.230, 95% CI: 0.063-0.838, p = .026) and slower tibial MCV (OR = 0.640, 95% CI: 0.539-0.760, p = .032). The predictive model demonstrated excellent discriminative ability with an AUC of 0.947 (95% CI: 0.921-0.973), sensitivity of 81.8%, and specificity of 95.7%. Patients with respiratory failure also had significantly higher Hughes functional scores (p < 0.001).
CONCLUSION: Motor conduction velocities of the peroneal and tibial nerves provide reliable and objective predictors for respiratory failure in GBS patients. Incorporating these markers into early risk assessment may facilitate prompt intervention and improve clinical outcomes.