Clinical neurology and neurosurgery · 2026
A multimodal prognostic model for post-thrombectomy outcomes: Integrating vascular ultrasound parameters and clinical risk factors.
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Chen Xiaoqiong, Huang Qun, Li Ling, Lin Yufei, Wang Yuzhen, Chen Qiong, Lin Liqing
Аннотация
BACKGROUND: Mechanical thrombectomy (MT) has advanced the therapeutic approach for acute ischemic stroke-induced large vessel occlusion (AIS-LVO). However, many patients show unfavorable neurological effects despite successful reperfusion. Thus, identifying prognostic determinants associated with adverse effects after MT is crucial for the early detection of high-risk individuals.
METHODS: This retrospective cohort study included 176 AIS‑LVO patients who achieved successful recanalization (mTICI ≥2b) and underwent TCD monitoring within 72 h after MT. Patients were randomly divided into training and validation sets (7:3). Clinical variables and TCD parameters were collected, and least absolute shrinkage and selection operator (LASSO) regression was used for feature selection. The data were used to develop a prognostic prediction model, which was evaluated using receiver operating characteristic (ROC) curve analysis, calibration curve and decision curve analysis(DCA).
RESULTS: Three predictors were selected: peak systolic velocity ratio (PSV_ratio), smoke, and mean flow velocity of the affected middle cerebral artery (MFV_aMCA). The predictive model based on the aforementioned parameters demonstrated good performance in the ROC analysis, calibration curve and DCA.
CONCLUSION: In conclusion, PSV_ratio, smoke, and MFV_aMCA are independently predict 90-day outcomes in anterior circulation AIS-LVO patients treated with MT. The predictive model incorporating these factors provides a valuable tool for risk stratification.
METHODS: This retrospective cohort study included 176 AIS‑LVO patients who achieved successful recanalization (mTICI ≥2b) and underwent TCD monitoring within 72 h after MT. Patients were randomly divided into training and validation sets (7:3). Clinical variables and TCD parameters were collected, and least absolute shrinkage and selection operator (LASSO) regression was used for feature selection. The data were used to develop a prognostic prediction model, which was evaluated using receiver operating characteristic (ROC) curve analysis, calibration curve and decision curve analysis(DCA).
RESULTS: Three predictors were selected: peak systolic velocity ratio (PSV_ratio), smoke, and mean flow velocity of the affected middle cerebral artery (MFV_aMCA). The predictive model based on the aforementioned parameters demonstrated good performance in the ROC analysis, calibration curve and DCA.
CONCLUSION: In conclusion, PSV_ratio, smoke, and MFV_aMCA are independently predict 90-day outcomes in anterior circulation AIS-LVO patients treated with MT. The predictive model incorporating these factors provides a valuable tool for risk stratification.