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Conference Paper: Clinical decision tool to predict functional outcome after successful endovascular recanalization in anterior-circulation large vessel

TitleClinical decision tool to predict functional outcome after successful endovascular recanalization in anterior-circulation large vessel
Authors
Issue Date22-Nov-2024
Abstract

Background: 

The treatment effect of intra-arterial thrombectomy (IAT) for intracranial large-vessel occlusion (LVO) can vary substantially between individuals with different background characteristics. A predictive tool that provides an evidence-based framework to forecast a patient’s functional outcome is valuable. 

Objective:

To develop and validate a clinical decision tool based on an Asian cohort of LVO-stroke patients 

Methods:

A consecutive series of patients treated with IAT at our institution were investigated. The inclusion criteria were : 1) Patients with anterior circulation LVO; 2) IAT performed between April 2017 to April 2023; 3) Successful recanalization defined by a modified treatment in cerebral infarction (mTICI) score of 2b to 3; and 4) clinical follow-up performed at 3 months after operation. 247 patients fulfilled the criteria. 

Clinical and radiological characteristics that are expected to interact with or predict functional outcome were included in a forward stepwise logistic regression model. Included patients were randomly divided into 2 groups, with 70% assigned as the derivation cohort, and the rest as the validation cohort. 


Results:

On univariate analysis based on the training set, the following predictors were associated with good 3-month mRS<=2: age, occlusion segment, admission NIHSS (The National Institutes of Health Stroke Scale), ASPECTS, rCS , and onset-to-perfusion time. On multivariate analysis, age, occlusion segment, admission NIHSS, ASPECTS, rCS and onset-to-perfusion time emerged as significant. The resultant binary predictive regression equation was validated using receiving operator characteristic (ROC) curve with area under curve being 0.807 (95% CI 0.735-0.879, p< 0.001).

Conclusions:

We have presented a precise predictive model for 3-month functional outcome in an Asian cohort of patients with anterior-circulation LVO-stroke post-IAT. This 5-variable simple clinical tool showed good discrimination and calibration in the validation set. 


Persistent Identifierhttp://hdl.handle.net/10722/351799

 

DC FieldValueLanguage
dc.contributor.authorSum, Hiu Fung Christopher-
dc.contributor.authorZhuang, Tin Fong James-
dc.contributor.authorCheng, King Fai Kevin-
dc.contributor.authorLui, Wai Man-
dc.contributor.authorTeo, Kay Cheong-
dc.contributor.authorHo, Grace-
dc.contributor.authorLau Hoi To-
dc.date.accessioned2024-11-29T00:35:15Z-
dc.date.available2024-11-29T00:35:15Z-
dc.date.issued2024-11-22-
dc.identifier.urihttp://hdl.handle.net/10722/351799-
dc.description.abstract<p>Background: </p><p>The treatment effect of intra-arterial thrombectomy (IAT) for intracranial large-vessel occlusion (LVO) can vary substantially between individuals with different background characteristics. A predictive tool that provides an evidence-based framework to forecast a patient’s functional outcome is valuable. </p><p>Objective:</p><p>To develop and validate a clinical decision tool based on an Asian cohort of LVO-stroke patients </p><p>Methods:</p><p>A consecutive series of patients treated with IAT at our institution were investigated. The inclusion criteria were : 1) Patients with anterior circulation LVO; 2) IAT performed between April 2017 to April 2023; 3) Successful recanalization defined by a modified treatment in cerebral infarction (mTICI) score of 2b to 3; and 4) clinical follow-up performed at 3 months after operation. 247 patients fulfilled the criteria. </p><p>Clinical and radiological characteristics that are expected to interact with or predict functional outcome were included in a forward stepwise logistic regression model. Included patients were randomly divided into 2 groups, with 70% assigned as the derivation cohort, and the rest as the validation cohort. </p><p><br></p><p>Results:</p><p>On univariate analysis based on the training set, the following predictors were associated with good 3-month mRS<=2: age, occlusion segment, admission NIHSS (The National Institutes of Health Stroke Scale), ASPECTS, rCS , and onset-to-perfusion time. On multivariate analysis, age, occlusion segment, admission NIHSS, ASPECTS, rCS and onset-to-perfusion time emerged as significant. The resultant binary predictive regression equation was validated using receiving operator characteristic (ROC) curve with area under curve being 0.807 (95% CI 0.735-0.879, p< 0.001).</p><p>Conclusions:</p><p>We have presented a precise predictive model for 3-month functional outcome in an Asian cohort of patients with anterior-circulation LVO-stroke post-IAT. This 5-variable simple clinical tool showed good discrimination and calibration in the validation set. </p>-
dc.languageeng-
dc.relation.ispartof31st Annual Scientific Meeting, The Hong Kong Neurosurgical Society, Hong Kong, 22-23 November 2024 (22/11/2024-23/11/2024, Hong Kong)-
dc.titleClinical decision tool to predict functional outcome after successful endovascular recanalization in anterior-circulation large vessel-
dc.typeConference_Paper-

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