Prediction Model for Early Subacute Phase Tracheostomy Decannulation in Patients with Stroke

Objective: This study aims to identify the factors influencing decannulation in patients with stroke who underwent tracheostomy during the early subacute phase. Methods: A retrospective analysis was conducted on 219 patients with stroke who underwent a tracheostomy at a tertiary hospital between January 2020 and December 2023. Among them, there were 155 males and 64 females. The age distribution ranged from 13 to 90 years old (average, 54.32 ± 14.96). There were 189 patients diagnosed with cerebral hemorrhage and 30 patients diagnosed with cerebral infarction. The patients were categorized into 2 groups: Those who achieved decannulation during the early subacute phase and those who did not. The decannulation group comprised 69 individuals, while the non-decannulation group comprised 150 individuals. Data collected included general patient demographics, stroke types, levels of consciousness, the presence of airway polyps, and outcomes of the modified Evan's blue dye test (MEBDT). Multivariate logistic regression analysis was employed to identify independent factors influencing early decannulation. The predictive value of these factors was further evaluated using the area under the curve (AUC) from the receiver operating characteristic (ROC) curve analysis. Results: Logistic regression analysis identified Glasgow Coma Scale scores, MEBDT results, and cough ability as independent factors influencing decannulation. ROC curve analysis demonstrated that a predictive model incorporating these 3 factors had a high predictive accuracy, with an AUC of 0.975 (P < .001, 95% CI 0.958-0.993). The model's cut-off value of 0.19 yielded a sensitivity of 95.6% and a specificity of 87.3%. Conclusion: The Glasgow Coma Scale score, MEBDT results, and cough ability are independent determinants of early decannulation is patients with stroke. The combined assessment of these factors offers strong predictive accuracy for early decannulation.