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New insight in massive cerebral infarction predictions after anterior circulation occlusion.
Chen, Jingshu; Zou, Mingyu; Zhang, Nan; Qi, Shouliang; Yang, Benqiang; Zhang, Libo; Shi, Lin; Duan, Yang.
Afiliación
  • Chen J; Department of Radiology, Center for Neuroimaging, General Hospital of Northern Theater Command, 83 Wenhua Road, Shenhe District, Shenyang, 110016, Liaoning, China.
  • Zou M; Department of Radiology, General Hospital of Northern Theater Command, Shenyang, China.
  • Zhang N; Department of Radiology, General Hospital of Northern Theater Command, Shenyang, China.
  • Qi S; College of Medicine and Biological Information Engineering, Northeastern University, Shenyang, China.
  • Yang B; Department of Radiology, General Hospital of Northern Theater Command, Shenyang, China.
  • Zhang L; Department of Radiology, General Hospital of Northern Theater Command, Shenyang, China.
  • Shi L; Northern Theater Command Postgraduate Training Base of China Medical University General Hospital, Shenyang, China.
  • Duan Y; Department of Radiology, Center for Neuroimaging, General Hospital of Northern Theater Command, 83 Wenhua Road, Shenhe District, Shenyang, 110016, Liaoning, China. duanyang100@126.com.
Sci Rep ; 13(1): 23021, 2023 12 27.
Article en En | MEDLINE | ID: mdl-38155293
ABSTRACT
To predict massive cerebral infarction (MCI) occurrence after anterior circulation occlusion (ACO) by cASPECTS-CTA-CS (combined ASPECTS and CTA-CS). Of 185 cerebral infarction patients with the ACO, their collateral circulation scores from CT angiography (CTA) images in two groups (MCI and non-MCI) were evaluated using Alberta Stroke Program Early CT Score (ASPECTS) and CT angiography collateral score (CTA-CS) approaches. The cASPECTS-CTA-CS was validated internally using the bootstrap sampling method with 1000 bootstrap repetitions and compared to CTA-CS. Receiver-operating characteristic curve (ROC), clinical impact curve (CIC), and decision curve analysis (DCA) strategies were used to assess the clinical practicality and predictability of both approaches (cASPECTS-CTA-CS and CTA-CS). Using net reclassification improvement (NRI) and integrated discrimination improvement (IDI) analyses, discrimination levels of the cASPECTS-CTA-CS were compared with CTA-CS. Classification and regression tree (CART) analyses was conducted to identify the best predictive values and identify subgroup of MCI. The discrimination ability of collateral circulation evaluation score using the cASPECTS-CTA-CS [AUC 0.918, 95% confidence interval (CI) 0.869-0.967, P < 0.01; NRI 0.200, 95% CI -0.104 to 0.505, P = 0.197; and IDI 0.107, 95% CI 0.035-0.178, P = 0.004] was better than CTA-CS alone (AUC 0.885, 95% CI 0.833-0.937, P < 0.01). DCA indicated the net benefits of the cASPECTS-CTA-CS approach was higher than CTA-CS alone when the threshold probability range over 20%. CIC analyses showed that the number of high risks and true positives were in agreement when the threshold probability > 80%. Less than 23 of cASPECTS-CTA-CS by CART was important factor in determining MCI occurrence, and ASPECTS < 7 was followed factor. The cASPECTS-CTA-CS approach cumulatively predicted MCI after ACO.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Isquemia Encefálica / Accidente Cerebrovascular Límite: Humans Idioma: En Revista: Sci Rep Año: 2023 Tipo del documento: Article País de afiliación: China Pais de publicación: Reino Unido
Texto completo
Añadir a Mi BVS
Imprimir
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PubMed Links
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Isquemia Encefálica / Accidente Cerebrovascular Límite: Humans Idioma: En Revista: Sci Rep Año: 2023 Tipo del documento: Article País de afiliación: China Pais de publicación: Reino Unido