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• Clinical Article •
The study of establishing functional outcome prediction model in acute stroke after mechanical thrombectomy
DING Shaohua  CHEN Yuchen  YIN Xindao  TIAN Weizhong  ZHANG Yi  DAI Hui 

Cite this article as: Ding SH, Chen YC, Yin XD, et al. The study of establishing functional outcome prediction model in acute stroke after mechanical thrombectomy[J]. Chin J Magn Reson Imaging, 2021, 12(8): 11-14, 21. DOI:10.12015/issn.1674-8034.2021.08.003.


[Abstract] Objective We established prediction model based on clinical factors, imaging factors and combining clinical and MRI factors to explore the optimal model for predicting the outcome in acute stroke after mechanical thrombectomy. Materials andMethods In this retrospective study, 71 acute stroke patients who received mechanical thrombectomy in our hospital were enrolled. All patients were within 24 h from onset and underwent MR examination before therapy. MRI data and clinical data were collected. The outcome was evaluated by mRS score at 3 months. Multivariate Logistic regression analysis was used to screen the independent predictors of outcome in acute stroke and to establish clinical predictive model, imaging predictive model and combining clinical and MRI predictive model. Receiver operating characteristic (ROC) was used to analyze their predictive effect on the outcome in acute stroke.Results Among 71 patients, 35 had good functional outcome and 36 had poor functional outcome. Multivariable Logistic analysis demonstrated that age (OR=1.071; 95% CI: 1.010—1.135; P=0.022) and NIHSS score on admission (OR=1.225; 95% CI: 1.099—1.366; P＜0.001) were independently associated with functional outcome in clinical model, and the AUC of clinical model was 0.810 with a sensitivity of 80.6% and a specificity of 71.4%. Hypoperfusion intensity ratio (HIR) (OR=4.037; 95% CI: 1.241—13.136; P=0.005) was independently associated with functional outcome in imaging model, and the AUC of imaging model was 0.862 with a sensitivity of 72.2% and a specificity of 94.3%. NIHSS score on admission (OR=1.157; 95% CI: 0.998—1.341; P=0.043) and HIR (OR=6.669; 95% CI: 4.817—15.051; P=0.009) were independently associated with functional outcome in clinical model, and the AUC of clinical model was 0.905 with a sensitivity of 94.4% and a specificity of 82.9%.Conclusions The prediction model of combining clinical and MRI is better than clinical model or imaging model alone, and can effectively improve predictive effect on outcome in acute stroke after mechanical thrombectomy.
[Keywords] stroke；diffusion weighted imaging；perfusion-weighted imaging；mechanical thrombectomy

DING Shaohua1   CHEN Yuchen2   YIN Xindao2   TIAN Weizhong3   ZHANG Yi3   DAI Hui1*  

1 Department of Radiology, the First Affiliated Hospital of Soochow University, Suzhou 215006, China

2 Department of Radiology, Nanjing First Hospital, Nanjing Medical University, Nanjing 210006, China

3 Department of Radiology, Taizhou People's Hospital, Taizhou 225300, China

Dai H, E-mail: huizi198208@126.com

Conflicts of interest   None.

ACKNOWLEDGMENTS This work was part of National Natural Science Foundation of China (No. 81971573).
Received  2021-01-17
Accepted  2021-03-18
DOI: 10.12015/issn.1674-8034.2021.08.003
Cite this article as: Ding SH, Chen YC, Yin XD, et al. The study of establishing functional outcome prediction model in acute stroke after mechanical thrombectomy[J]. Chin J Magn Reson Imaging, 2021, 12(8): 11-14, 21. DOI:10.12015/issn.1674-8034.2021.08.003.

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