Dataset Information

TAB-TICI Score: Successful Recanalization Score After Endovascular Thrombectomy in Acute Stroke

ABSTRACT: Background and Purpose: Successful reperfusion therapy is supposed to be comprehensive and validated beyond the grade of recanalization. This study aimed to develop a novel scoring system for defining the successful recanalization after endovascular thrombectomy. Methods: We analyzed the data of consecutive acute stroke patients who were eligible to undergo reperfusion therapy within 24 h of onset and who underwent mechanical thrombectomy using a nationwide multicenter stroke registry. A new score was produced using the predictors which were directly linked to the procedure to evaluate the performance of the thrombectomy procedure. Results: In total, 446 patients in the training population and 222 patients in the validation population were analyzed. From the potential components of the score, four items were selected: Emergency Room-to-puncture time (T), adjuvant devices used (A), procedural intracranial bleeding (B), and post-thrombectomy reperfusion status [Thrombolysis in Cerebral Infarction (TICI)]. Using these items, the TAB-TICI score was developed, which showed good performance in terms of discriminating early neurological aggravation [AUC 0.73, 95% confidence interval (CI) 0.67–0.78, P < 0.01] and favorable outcomes (AUC 0.69, 95% CI 0.64–0.75, P < 0.01) in the training population. The stability of the TAB-TICI score was confirmed by external validation and sensitivity analyses. The TAB-TICI score and its derived grade of successful recanalization were significantly associated with the volume of thrombectomy cases at each site and in each admission year. Conclusion: The TAB-TICI score is a valid and easy-to-use tool to more comprehensively define successful recanalization after endovascular thrombectomy in acute stroke patients with large vessel occlusion.

SUBMITTER: Seo W

PROVIDER: S-EPMC8551570 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:BackgroundTo evaluate the predictive value of radiomics features extracted from the thrombus on preoperative computed tomography images to identify successful recanalization after stent retrieve (SR) treatment in patients with acute ischemic stroke (AIS).MethodsTwo hundred fifty-six patients newly diagnosed AIS between March 2017 and September 2020 from two institutes, including the first affiliated hospital of Soochow university (institute I) and Northern Jiangsu People's hospital (institute II), were enrolled continuously and retrospectively. Patients with unsatisfactory image quality were excluded. The remaining patients of institute I were randomly divided into the training and internal validation cohorts at a ratio of 7 to 3, and patients of institute II were collected as the external validation cohort. After extraction and selection of the optimal radiomics features from training cohort, six machine learning (ML) classifiers including naïve Bayes (NB), random forest (RF), logistic regression (LR), linear support vector machine (L.SVM), radial SVM (R.SVM), and an artificial neural network (ANN) were developed to predict successful recanalization with SR treatment and compared. A combined model based on the optimal ML classifier was constructed using the optimal radiomics model and clinical-radiological risk variables. Finally, the performance of the model was selected based on the Matthews correlation coefficient (MCC) and the area under the receiver operating (AUC) and independently evaluated on the internal validation and external validation cohorts.ResultsWe automatically extracted 1,130 radiomics features from the voxel of interest (VOI) using PyRadiomics. The eight most relevant radiomics features were identified using Intraclass coefficient, single-factor logistic regression analysis, and least absolute shrinkage and selection operator algorithm in the training cohort. Among the six ML classifiers, the ANN classifier using thrombus radiomics features achieved the best prediction of early recanalization under SR with MCCs of 0.913, 0.693 and 0.505 in training, internal and external validation cohorts, respectively. Moreover, receiver operating characteristic curves showed that the combined model [AUC =0.860, 95% confidence interval (CI): 0.731-0.936; AUC =0.849, 95% CI: 0.759-0.831] was not significantly better than radiomics model based on the ANN classifier alone (AUC =0.873, 95% CI: 0.803-0.891; AUC =0.805, 95% CI: 0.864-0.971) (P>0.05, Delong test) in internal and external validation cohorts.ConclusionsA radiomics model based on the ANN classifier has the ability to predict successful recanalization after SR in patients with AIS, thus allowing a potentially better selection of mechanical thrombectomy treatment.

Project description:BackgroundHemorrhagic transformation (HT) of acute ischemic stroke (AIS) is associated with poor outcome. Previous studies only reported the association of mean ischemic severity or total infarct volume with HT after endovascular therapy (EVT). We aimed to investigate the predictive value of preoperative apparent diffusion coefficient (ADC) map for HT by combinated ischemic severity and corresponding volume in AIS after successful recanalization with EVT.MethodsWe retrospectively analyzed 119 consecutive cases of AIS with large vessel occlusion of anterior circulation within 24 hours after symptom onset and successful recanalization after EVT. All cases had baseline magnetic resonance imaging (MRI), follow-up computed tomography (CT), and magnetic resonance angiography (MRA) or computed tomography angiography (CTA). Volumes of ADC <0.6×10-3, 0.5×10-3, 0.4×10-3, and 0.3×10-3 mm2/s, baseline characteristics and outcomes of patients with and without HT identified by European Collaborative Acute Stroke Study (ECASS) were compared. The optimal ADC and volume threshold for predicting HT were analyzed using receiver operating characteristic (ROC) curve, and multivariate logistic regression analysis were performed with clinical characteristics and volumes of optimal ADC threshold to determine risk factors for HT.ResultsAmong 119 patients, 42 patients had HT on follow-up CT, including 24 hemorrhagic infarct (HI) cases and 18 parenchymal hematoma (PH) cases. The optimal volumes were 6.46 mL with ADC <0.4×10-3 mm2/s for predicting both HT and PH, with a larger area under curve (AUC) of 83.3% for HT than that for PH of 80%. In logistic regression analysis, intravenous tissue plasminogen activator (IV tPA) treatment, atrial fibrillation, and volume of ADC <0.4×10-3 mm2/s were identified as independent predictors for HT and volume of ADC <0.4×10-3 mm2/s had the highest odds ratio (OR) value.ConclusionsThe combination of ischemic severity and corresponding volume in ADC map may predict HT after thrombectomy. In addition to the total infarct volume, volume with severe ischemia should be taken into consideration in preoperative patient selection.

Project description:ImportanceIntravenous thrombolysis (IVT) followed by mechanical thrombectomy (MT) is recommended to treat acute ischemic stroke (AIS) with a large vessel occlusion (LVO). Most hospitals do not have on-site MT facilities, and most patients need to be transferred secondarily after IVT (drip and ship), which may have an effect on the neurologic outcome.ObjectiveTo compare the functional independence at 3 months between patients treated under the drip-and-ship paradigm and those treated on site (mothership).Design, setting, and participantsThis study used a prospectively gathered registry of patients with AIS to select patients admitted through the Saint-Antoine and Tenon (drip and ship) or the Fondation Rothschild (mothership) hospitals from January 1, 2013, through April 30, 2016. The study included patients older than 18 years treated with bridging therapy for AIS with LVO of the anterior circulation. Among the 159 patients who received MT at the mothership, 100 had been transferred after IVT from the drip-and-ship hospitals and 59 had received IVT on site.Main outcomes and measuresThe main outcome was 3-month functional independence (modified Rankin scale score ≤2). Both groups were compared using a multivariate linear model, including variables that were significantly different in the 2 groups.ResultsDuring the study period, 497 patients were hospitalized at the drip-and-ship and mothership hospitals for an AIS eligible to reperfusion therapy; 11 patients had a basilar artery occlusion and were excluded, leaving 100 patients in the drip-and-ship group (mean age, 73 years; age range, 60-81 years; 57 men [57.0%]) and 59 in the mothership group (mean age, 70 years; age range, 58-82 years; 29 men [49.2%]). The proportion of patients with a favorable neurologic outcome at 3 months was similar in both groups (drip and ship, 61 [61.0%]; mothership, 30 [50.8%]; P = .26), even after adjusting the analysis for the baseline National Institutes of Health Stroke Scale score, diffusion-weighted imaging Alberta Stroke Program Early Computed Tomography Score, and general anesthesia (P = .82). Patients had less severe conditions in the drip-and-ship group (median baseline National Institutes of Health Stroke Scale score, 15 vs 17 [P = .03]; median diffusion-weighted imaging Alberta Stroke Program Early Computed Tomography Score, 7.5 vs 7 [P = .05]). Process times were longer in the drip-and-ship group (onset-to-needle time, 150 vs 135 minutes; onset-to-puncture time, 248 vs 189 minutes; and onset-to-recanalization time, 297 vs 240 minutes; P < .001). Both groups were similar in terms of substantial recanalization (Thrombolysis in Cerebral Ischemia scores 2B to 3; drip and ship, 84 [84.0%]; mothership, 47 [79.7%]; P = .49) and symptomatic hemorrhagic transformation (drip and ship, 2 [2.0%]; mothership, 2 [3.4%]; P = .63).Conclusions and relevanceThis study found that patients treated under the drip-and-ship paradigm also benefit from bridging therapy, with no statistically significant difference compared with those treated directly in a comprehensive stroke center.

Dataset Information

TAB-TICI Score: Successful Recanalization Score After Endovascular Thrombectomy in Acute Stroke

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets