DRAGON Score Research Articles

Validation of Prognostic Scales for Functional Outcome in Ischemic Stroke Patients Treated with Intravenous Thrombolysis in a Rural Setting

Introduction: Early prediction of functional outcome after rtPA helps clinicians in prognostic conversations with stroke patients and their families. Three prognostic tools have been developed in this regard: DRAGON, MRI-DRAGON, and S-TPI scales. These tools, all performing with comparable accuracy, have been internally and externally validated in tertiary care centers. However, their performance in rural areas remains uncertain. This study addresses this gap in the literature by evaluating the effectiveness of those prognostic tools in stroke patients treated in a rural area of the Midwest. Methods: We conducted a retrospective study of stroke patients treated with thrombolytics at Southern Illinois Healthcare Stroke Network from July 2017 to June 2024. Data on demographics, clinical presentations, laboratory values, neuroimaging, and stroke metrics were collected. Modified Rankin Scale (mRS) at 1 month, classified into good (mRS ≤2) and poor (mRS ≥5) outcomes were noted. DRAGON and MRI-DRAGON scores were calculated. S-TPI model was built. Area under the receiver operating characteristic curve (AUC) with its 95% confidence interval was calculated for each prognostic model. Results: A total of 279 patients were included in this study. Of those, 43% (n = 119) were male. Median age (interquartile range [IQR]) was 69 (57–80) years. NIHSS at presentation (IQR) was 7 (4–13). 12% of the cohort (n = 34) had posterior circulation stroke. At 1 month, 66% of patients (n = 185) had mRS ≤2, whereas 14% of patients (n = 39) had mRS ≥5. MRI-DRAGON showed the highest accuracy in predicting both good (AUC = 0.86, 95% CI: 0.81–0.90) and poor outcomes (AUC = 0.84, 95% CI: 0.76–0.91). DRAGON also demonstrated high accuracy for good (AUC = 0.85, 95% CI: 0.80–0.89) and poor (AUC = 0.82, 95% CI: 0.75–0.90) outcomes. Conversely, in our population, the S-TPI model had the lowest accuracy for good (AUC = 0.56, 95% CI: 0.49–0.63) and poor (AUC = 0.68, 95% CI: 0.61–0.76) outcomes. Conclusion: Among the available grading scores, MRI-DRAGON score can be considered the more accurate short-term prognostic tool for stroke patients treated with rtPA in the rural setting.

External validation of the iScore, ASTRAL score, DRAGON score, and THRIVE score and development of a nomogram to predict outcome in patients with large vessel occlusion-acute ischemic stroke

ObjectiveThis study aimed to validate the iScore, ASTRAL score, DRAGON score, and THRIVE score for assessing large vessel occlusion–acute ischemic stroke (AIS-LVO) and establish a predictive model for AIS-LVO patients that has better performance to guide clinical practice. MethodsWe retrospectively included 439 patients with AIS-LVO and collected baseline data from all of them. External validation of the iScore, ASTRAL score, DRAGON score, and THRIVE score was performed. All variables were compared between groups via univariate analysis, and the results are expressed as ORs and 95 % CIs. Independent variables with P < 0.25 were included in the multivariate logistic analysis, and statistically significant differences (P < 0.05) were identified as risk factors for prognosis in AIS-LVO patients. Receiver operating characteristic (ROC) curve analysis and decision curve analysis (DCA) were used to evaluate the predictive value of our model. ResultsOur external validation resulted in an iScore under the curve (AUC) of 0.8475, an ASTRAL AUC of 0.8324, a DRAGON AUC of 0.8196, and a THRIVE AUC of 0.8039. In our research, multivariate Cox regression revealed 8 independent predictors. We used a nomogram to visualize the results of the data analysis. The AUC for the training cohort was 0.8855 (95 % CI, 0.8487-0.9222), and that in the validation cohort was 0.8992 (95 % CI, 0.8496-0. 9488). ConclusionsIn this study, we verified that the above scores have excellent efficacy in predicting the prognosis of AIS-LVO patients. The nomogram we developed was able to predict the prognosis of AIS-LVO more accurately and may contribute to personalized clinical decision-making and treatment for future clinical work.

Heterogeneous treatment effects of Cerebrolysin as an early add-on to reperfusion therapy: post hoc analysis of the CEREHETIS trial.

Background: There has been intensive research into enhancing the effects of reperfusion therapy to mitigate hemorrhagic transformation (HT) in stroke patients. Using neuroprotective agents alongside intravenous thrombolysis (IVT) appears a promising approach. Cerebrolysin is one of the candidates since it consists of neuropeptides mimicking the action of neurotrophic factors on brain protection and repair. Objectives: We looked at treatment effects of Cerebrolysin as an early add-on to IVT in stroke patients with varying HT risk. Methods: It was post hoc analysis of the CEREHETIS trial (ISRCTN87656744). Patients with middle cerebral artery infarction (n = 238) were selected from the intention-to-treat population. To stratify participants according to their HT risk, the DRAGON, SEDAN and HTI scores were computed for each eligible subject using on-admission data. The study endpoints were any and symptomatic HT, and functional outcome measured with the modified Rankin Scale (mRS) on day 90. Favorable functional outcome (FFO) was defined as an mRS ≤2. The performance of each stratification tool was estimated with regression approaches. Heterogeneous treatment effect analysis was conducted using techniques of meta-analysis and the matching-smoothing method. Results: The HTI score outperformed other tools in terms of HT risk stratification. Heterogeneity of Cerebrolysin treatment effects was moderate (I2, 35.8%-56.7%; H2, 1.56-2.31) and mild (I2, 10.9%; H2, 1.12) for symptomatic and any HT, respectively. A significant positive impact of Cerebrolysin on HT and functional outcome was observed in the moderate (HTI = 1) and high (HTI ≥2) HT risk patients, but it was neutral in those with the low (HTI = 0) risk. In particular, there was a steady decline in the rate of symptomatic (HTI = 0 vs. HTI = 4: by 4.3%, p = 0.077 vs. 21.1%, p < 0.001) and any HT (HTI = 0 vs. HTI = 4: by 1.2%, p = 0.737 vs. 32.7%, p < 0.001). Likewise, an mRS score reduction (HTI = 0 vs. HTI = 4: by 1.8%, p = 0.903 vs. 126%, p < 0.001) with a reciprocal increase of the fraction of FFO patients (HTI = 0 vs. HTI = 4: by 1.2% p = 0.757 vs. 35.5%, p < 0.001) was found. Conclusion: Clinically meaningful heterogeneity of Cerebrolysin treatment effects on HT and functional outcome was established in stroke patients. The beneficial effects were significant in those whose estimated on-admission HT risk was either moderate or high.

Supra-Blan2 t score as a multisystem-based risk score to predict poor 3-month outcome in acute ischemic stroke patients with intravenous thrombolysis.

To develop and validate a novel weighted score integrating multisystem laboratory and clinical variables to predict poor 3-month outcome (mRS score of 3-6) in acute ischemic stroke (AIS) patients with intravenous thrombolysis (IVT) therapy. We retrospectively analyzed data from Trial of Revascularization Treatment for Acute Ischemic Stroke study. The Supra-Blan2 t score was derived using the data on age, the National Institutes of Health Stroke Scale score, history of atrial fibrillation, blood sugar level, neutrophil count, direct bilirubin level, platelet-lymphocyte ratio, and TnI level in the derivation cohort of 433 patients, and validated in a cohort of 525 patients. Furthermore, we compared the performance of the Supra-Blan2 t score with DRAGON, TURN, and SPAN-100 scores. The discrimination capacity in the derivation and validation cohorts was good for poor 3-month outcome (the area under the curve was 0.821 and 0.843, respectively). The cumulative incidence of poor 3-month outcome significantly increased across risk categories in the derivation (low-risk, 9.2%; medium-risk, 17.4%; and high-risk, 58.8%) and validation cohorts (12.7%, 36.5%, and 73.6%, respectively). The performance of the Supra-Blan2 t score was similar to or superior to DRAGON, TURN, and SPAN-100 scores. The Supra-Blan2 t score, based on easily available multisystem laboratory and clinical variables, reliably predicted poor 3-month functional outcome in AIS patients treated with IVT therapy featuring good calibration and discrimination.

How to Train Your Dragon by John Powell

Reviewed by: How to Train Your Dragon by John Powell Denise E. Finnegan-Hill John Powell. How to Train Your Dragon. Los Angeles: Omni Music Publishing, 2020. [xvi, 384 p. ISBN 9781734507928 (paperback), $85] Rarely does one find a published copy of a film’s score, particularly from a film as recent as 2010. The film How to Train Your Dragon received critical acclaim when it was first released with many reviewers acknowledging the role of the score in the film’s success. The score by composer John Powell, received its own recognition with an Oscar nomination for Best Score and winning Film Score of the Year from the IFMCA Awards. The score is written for full orchestra with a variety of folk and non-Western instruments. The published score is great for anyone studying film music, presenting a unique opportunity to dive deep into a newer score without having to rely on one’s ear and assist in widening the base of film music research. The lack of scholarly research on Powell, limited to only a composition dissertation chapter by Jennifer Dirkes (“Synchretic Analysis and Storyboard Scores: The Musical Rhythm of Filmic Elements,” [PhD diss., University of California-Los Angeles, 2017]) and my own Master’s thesis (“Thematic Development in John Powell’s Score for How to Train Your Dragon (2010),” [MM thesis, University of Nebraska-Lincoln, 2020]) leaves much room for exploration of Powell and the How to Train Your Dragon franchise. The How to Train Your Dragon score is unique to Omni Music Publishing’s collection as both the only score by Powell and the only score for an animated film, helping to diversify the emerging “canon” brought about by the limited publication of film scores. The published score will allow more scholars to explore Powell’s thematic technique and other aspects of his composition style that have not yet been researched. The thematically driven nature of the score that is in many ways more akin to the classic scores of John Williams, than other scores of the same year such as Oscar nominees The Social Network (Trent Reznor and Atticus Ross) and Inception (Hans Zimmer) is possibly why Omni chose this score for publication alongside well-known composers like James Horner, Bernard Herrmann, and Elmer Bernstein. The publication was successful enough that Omni is set to publish the score for the second How to Train Your Dragon film in fall of 2021. Apart from Batman and Batman Returns (Danny Elfman) this is the only other series of scores Omni has published to date. Pending the success of the second score, I’m sure they will consider releasing the score for the third film as well, giving scholars the opportunity to study the entire franchise more easily. The publication is a beautiful edition, clearly laid out for ease of study. Abridged film credits and a relatively short introductory “analysis” of some [End Page 466] main themes and where they appear in the score are included. The film credits page mentions only those involved in the music production apart from the directors and main voice actors. This page is helpful to see everyone involved in the music production besides Powell, including a long list of orchestrators and arrangers, reminding us that although Powell will get credit for every choice made in the film’s music, it is not likely that he made every small decision, an important thing to note when writing about film music. Unfortunately, there is no indication of which orchestrator or arranger worked on which parts of the score. One may assume the names are listed by amount of contribution since they are not in alphabetical order, but there is no confirmation of this idea. At the bottom of the same page are the “book credits” showing that Powell and others from his production company, 5 Cat Studios, were involved in creating this publication. Timothy Rodier from Omni Music Publishing is also listed and credited with the layout and design of the book, but unfortunately there is no indication of how much input Powell had in the publication’s production and could possibly be listed as a courtesy or simply because the publisher went through...

Different Scores Predict the Value of Hemorrhagic Transformation after Intravenous Thrombolysis in Patients with Acute Ischemic Stroke.

Objective To evaluate the value of the Alberta stroke project early CT score (ASPECTS), DRAGON score, SEDAN score, and HAT score in predicting hemorrhagic transformation (HT) after intravenous thrombolysis in patients with acute ischemic stroke (AIS). Methods The clinical data of 248 AIS patients treated with intravenous thrombolysis in our hospital from December 2017 to December 2019 were analyzed. According to the prognosis, all patients were divided into the non-HT group (n = 200) and the HT group (n = 48). Univariate analysis and multivariate logistic regression models were used to analyze clinical data to determine the influencing factors of HT after intravenous thrombolysis in AIS patients. The receiver operating characteristic curve was used to evaluate the ASPECTS, DRAGON, SEDAN, and HAT scores to the value of predicting HT after intravenous thrombolysis in AIS patients. Results The lower the ASPECTS score and the higher the DRAGON, SEDAN, and HAT scores, the higher the incidence of HT after intravenous thrombolysis in AIS patients (P < 0.05). The results of multivariate logistic regression analysis showed that the patient's age, atrial fibrillation, baseline NIHSS score, early signs of infarction on admission with head CT, time from onset to thrombolytic therapy, and thrombolytic drugs were all independent factors affecting intravenous thrombolysis in AIS patients (P < 0.05). The area under the curve (AUC) of the predictive value of ASPECTS for HT is 0.895 (95% CI 0.813–0.977). When the optimal cutoff value is 0.607, the sensitivity is 100% and the specificity is 60.7%. The AUC of the predictive value of DRAGON for HT is 0.877 (95% CI 0.790–0.964). When the optimal cutoff value is 0.665, the sensitivity is 84.4% and the specificity is 82.1%. The AUC of the predictive value of SEDAN for HT is 0.764 (95% CI 0.638–0.890). When the optimal cutoff value is 0.474, the sensitivity is 78.6% and the specificity is 68.8%. The AUC of the predictive value of HAT for HT is 0.777 (95% CI 0.651–0.903). When the optimal cutoff value is 0.509, the sensitivity is 68.8% and the specificity is 82.1%. Conclusion The lower the ASPECTS score and the higher the DRAGON, SEDAN, and HAT scores, the higher the incidence of HT in AIS patients. The patient's age, atrial fibrillation, baseline NIHSS score, early signs of infarction on admission with head CT, time from onset to thrombolytic therapy, and thrombolytic drugs are all independent factors affecting HT in AIS patients. The scores of ASPECTS, DRAGON, SEDAN and HAT have certain value in predicting HT after intravenous thrombolysis in AIS patients, and the predicted value of ASPECTS score is the best.

Using a Multiclass Machine Learning Model to Predict the Outcome of Acute Ischemic Stroke Requiring Reperfusion Therapy.

Prediction of functional outcome in ischemic stroke patients is useful for clinical decisions. Previous studies mostly elaborate on the prediction of favorable outcomes. Miserable outcomes, which are usually defined as modified Rankin Scale (mRS) 5–6, should be considered as well before further invasive intervention. By using a machine learning algorithm, we aimed to develop a multiclass classification model for outcome prediction in acute ischemic stroke patients requiring reperfusion therapy. This was a retrospective study performed at a stroke medical center in Taiwan. Patients with acute ischemic stroke who visited between January 2016 and December 2019 and who were candidates for reperfusion therapy were included. Clinical outcomes were classified as favorable outcome, intermediate outcome, and miserable outcome. We developed four different multiclass machine learning models (Logistic Regression, Supportive Vector Machine, Random Forest, and Extreme Gradient Boosting) to predict clinical outcomes and compared their performance to the DRAGON score. A sample of 590 patients was included in this study. Of them, 180 (30.5%) had favorable outcomes and 152 (25.8%) had miserable outcomes. All selected machine learning models outperformed the DRAGON score on accuracy of outcome prediction (Logistic Regression: 0.70, Supportive Vector Machine: 0.67, Random Forest: 0.69, and Extreme Gradient Boosting: 0.67, vs. DRAGON: 0.51, p < 0.001). Among all selected models, Logistic Regression also had a better performance than the DRAGON score on positive predictive value, sensitivity, and specificity. Compared with the DRAGON score, the multiclass machine learning approach showed better performance on the prediction of the 3-month functional outcome of acute ischemic stroke patients requiring reperfusion therapy.

Abstract TP13: External Validation of Stroke Prognostication Scales - A Retrospective Cohort Study

Introduction: In recent years, many scoring models have been proposed to predict clinical outcomes after acute ischemic stroke. Aim of our study was to perform a comparative analysis of these scoring systems to assess predictive reliability. Method: This retrospective single center study included 166 community-based patients presenting with an acute ischemic stroke between 2015 and 2018 who had undergone mechanical thrombectomy with or without IV r-tPA administration prior to the procedure. Patients with unknown 90 day Modified Ranking Scale (mRS) were excluded from the study. We included SPAN-100, THRIVE, HIAT2, iScore , TPI, DRAGON, ASTRAL and HAT predictive models to our study. To predict MRS at 90 days, we first dichotomize mRS into two groups: scores of 0 and 1 and scores 2 and above. We then used logistic regression to find the association between a stroke score and the probability of having a 90-day mRS of 2 or above. Separate univariate logistic regressions were fit for each stroke score. We assessed the ability of each stroke score to predict 90-day mRS using the area-under-the-curve (AUC) of the receiver operating characteristic curve (ROC - plot of sensitivity against 1-specificity). AUC values range from 0.5 to 1 with values above 0.7 showing good discriminatory ability. Results: SPAN-100, HIAT2, iScore, and ASTRAL scores have similar predictive ability with AUC values over 0.7 (Table 1). The ASTRAL score had the highest predictive ability with a score above 31.5 indicating a high likelihood of a 90-day MRS ≥ 2 (Table 1). The TPI, DRAGON, and HAT scores all had AUCs below 0.65 indicating poor predictive performance in our data. Conclusion: The SPAN-100, HIAT2, iScore, and ASTRAL scores reliably predicts 90-day mRS of 2 or greater in patients with acute ischemic stroke.

Symptomatic Intracerebral Hemorrhage after Intravenous Thrombolysis: Predictive Factors and Validation of Prediction Models

Objective: Thrombolytic therapy with intravenous alteplase (IV-rtPA) has a known risk of symptomatic intracerebral hemorrhage (sICH). We aim to identify factors with a significant association with the development of sICH post-IV-rtPA. We also aim to perform an external validation of sICH predicting scores in our patient population. Material and Methods: We performed a retrospective chart review of patients who received IV-rtPA at our tertiary care hospital. We excluded patients who underwent mechanical thrombectomy. We analyzed various factors recorded at presentation such as presenting mean arterial pressure (MAP), blood glucose, National Institutes of Health Stroke Scale (NIHSS) score, verify Aspirin, verify Plavix, age, sex, platelet count, international normalized ratio, prothrombin time, partial thromboplastin time, hemoglobin A1c, low-density lipoprotein, onset to treatment time, weight, sex, and early infarct signs on computed tomography (CT) head and compared them between sICH and non-sICH groups. For validation of sICH scores, we used documented variables to calculate the following scores for each patient: stroke prognostication using age and NIH stroke scale-100 (SPAN-100), DRAGON, CUCCHIARA, hemorrhage after thrombolysis (HAT), SEDAN, totaled health risks in vascular events, and safe implementation of thrombolysis in stroke-symptomatic intracerebral hemorrhage. Results: sICH rate in our cohort of 89 patients was 5.62% according to the European-Australasian Cooperative Acute Stroke Study-II (ECASS-II) criteria and 7.86% according to the National Institute of Neurological Disorders and Stroke (NINDS) criteria. In the multivariate regression analysis, MAP (95% CI, .001-.01; P .002), blood glucose greater than or equal to 185 mg/dL (95% CI, .12-.45; P .001) and presence of early infarct signs (95% CI, .06-.25; P .002) had a significant association with the development of sICH with the ECASS-II definition of sICH post-IV-rtPA, whereas, only MAP (95% CI, 1.01-1.18; P .025) and verify Aspirin less than 500 (95% CI, .01-.80; P .032) had a significant association with the development of sICH with the NINDS definition of sICH post-IV-rtPA. Our study found that HAT (95% CI, .58-.96; P .044) and DRAGON (95% CI, .61-.96; P .012) scores had the highest area under the curve (AUC) with respect to ECASS-II and NINDS criteria of sICH, respectively. Conclusions: We found that presenting MAP, presence of early infarct signs on CT Head and blood glucose greater than or equal to 185 mg/dL upon a patient's presentation have a significant association with sICH post-IV-rtPA when the ECASS-II definition was used, while presenting MAP and verify Aspirin less than 500 upon a patient's presentation have a significant association with sICH post-IV-rtPA when the NINDS definition was used. Our study found that HAT and DRAGON scores had the highest AUC, and they were the most valid in predicting the development of sICH in our independent cohort. Patients with these risk factors should receive more intensive neurological monitoring.

Effect of glycated hemoglobin index and mean arterial pressure on acute ischemic stroke prognosis after intravenous thrombolysis with recombinant tissue plasminogen activator.

To determine whether glycated hemoglobin and mean arterial pressure (MAP) during thrombolysis are prognostic factors of intravenous thrombolysis with recombinant tissue plasminogen activator (rt-PA) for acute ischemic stroke (AIS).A total of 125 AIS patients, who received rt-PA intravenous thrombolysis in our hospital, were included into the present study, and divided into good prognosis group and poor prognosis group. Univariate and multivariate logistic regression analyses were used to determine the prognostic factors of AIS treated by rt-PA thrombolysis, Spearman correlation analysis was used to analyze the correlation of the accumulated cigarette consumption in the smoking subgroup and glycated hemoglobin in the diabetic subgroup with the prognosis after intravenous thrombolysis and the symptomatic intracranial hemorrhage (sICH).Univariate analysis revealed that the interval from onset to thrombolysis, baseline National Institutes of Health Stroke Scale (NIHSS) score, MAP during thrombolysis and DRAGON score were prognostic factors. Multivariate logistic regression analysis revealed that baseline NIHSS score and MAP during thrombolysis were independent prognostic factors for rt-PA thrombolysis. Furthermore, the glycated hemoglobin index was positively correlated with the incidence of sICH.The NIHSS score before thrombolysis and MAP during thrombolysis were independent factors for the prognosis of AIS treated by thrombolysis. The higher the glycated hemoglobin index of diabetic patients, the more likely they are to develop sICH, the glycated hemoglobin index was negatively correlated with the prognosis after intravenous thrombolysis. The accumulated cigarette consumption was negatively correlated with the prognosis after intravenous thrombolysis.

Successful thrombolysis in cerebrovascular disease: a case report

The most important risk factor for presenting a cerebrovascular disease (CVA) is age. Stroke is also the most frequent cause of disability acquired in adulthood. According to the World Health Organization, it is estimated that by the year 2050, almost half of the population over 65 could suffer or have suffered a CVA. Due to the high incidence and negative impact of this disease, we present a clinical case of successful thrombolysis in a patient with ischemic stroke and hypertensive crisis in the emergency department. We emphasize the adequate evaluation with the different existing clinical, radiological and predictive scales (NIHSS, Dragon Score, ASPECT, HAT score), as well as the inclusion and exclusion criteria, which are indispensable to administer an intravenous reperfusión therapy. Conclusions: In Mexico, the cases reported with successful thrombolysis are only 5%. In this successful case, the proper performance in the emergency service impacted positively on the prognosis of the patient, since the timely diagnosis and administration of rTPA avoided important sequelae and provided a better quality of Life, which is decreased in up to 70% of patients suffering from a CVA (according to studies conducted in the USA).

THRIVE-c score predicts clinical outcomes in Chinese patients after thrombolysis.

ObjectivesTotal Health Risks in Vascular Events‐calculation score (THRIVE‐c) is an easy use and patient‐specific outcome predictive score by computing the logistic equation with patients’ continuous variables. We validated its performance in Chinese ischemic stroke patients receiving intravenous thrombolysis (IVT) therapy.Materials and MethodsWe used data from the Thrombolysis Implementation and Monitor of Acute Ischemic Stroke in China (TIMS‐China) registry to validate the THRIVE‐c score in patients receiving IVT therapy. We evaluated the score performance using area under the receiver operating characteristic curve (AUC). Receiver operator characteristic curve (ROC) was used to compare THRIVE‐c score performance with other scores in predicting clinical outcome and symptomatic intracranial hemorrhage (SICH). Calibration was assessed by Pearson correlation coefficient and Hosmer–Lemeshow test.ResultsAmong the 1,128 patients receiving IVT therapy included in this study, AUC of the THRIVE‐c score for 3‐month SICH, poor functional outcome, and mortality rate was 0.70 (95% CI: 0.63–0.76), 0.75 (95% CI: 0.73–0.78) and 0.81 (95% CI: 0.77–0.85), respectively. The increased THRIVE‐c score was associated with higher risk of developing SICH, poor functional outcome, or mortality in patients with acute ischemic stroke at 3 months after thrombolysis. The performance of the THRIVE‐c score was similar to or superior to other predictive scores (THRIVE score, SEDAN score, DRAGON score, HIAT2 score).ConclusionsThe THRIVE‐c score reliably predicts the risks of 3‐month SICH, poor functional outcome, and mortality after IVT therapy in Chinese patients with ischemic stroke.

DRAGON score predicts functional outcomes in acute ischemic stroke patients receiving both intravenous tissue plasminogen activator and endovascular therapy

Background:The DRAGON score, which includes clinical and computed tomographic (CT) scan parameters, predicts functional outcomes in ischemic stroke patients treated with intravenous tissue plasminogen activator (IV tPA). We assessed the utility of the DRAGON score in predicting functional outcome in stroke patients receiving both IV tPA and endovascular therapy.Methods:A retrospective chart review of patients treated at our institution from February 2009 to October 2015 was conducted. All patients with computed tomography angiography (CTA) proven large vessel occlusions (LVO) who underwent intravenous thrombolysis and endovascular therapy were included. Baseline DRAGON scores and modified Rankin Score (mRS) at the time of hospital discharge was calculated. Good outcome was defined as mRS ≤3.Results:Fifty-eight patients with LVO of the anterior circulation were studied. The mean DRAGON score of patients on admission was 5.3 (range, 3–8). All patients received IV tPA and endovascular therapy. Multivariate analysis demonstrated that DRAGON scores ≥7 was associated with higher mRS (P < 0.006) and higher mortality (P < 0.0001) compared with DRAGON scores ≤6. Patients with DRAGON scores of 7 and 8 on admission had a mortality rate of 3.8% and 40%, respectively.Conclusions:The DRAGON score can help predict better functional outcomes in ischemic stroke patients receiving both IV tPA and endovascular therapy. This data supports the use of the DRAGON score in selecting patients who could potentially benefit from more invasive therapies such as endovascular treatment. Larger prospective studies are warranted to further validate these results.

External Validation of the ASTRAL and DRAGON Scores for Prediction of Functional Outcome in Stroke: Cooray C, Mazya M, Bottai M, et al. Stroke. 2016;47:1493-1499

External Validation of the ASTRAL and DRAGON Scores for Prediction of Functional Outcome in Stroke: Cooray C, Mazya M, Bottai M, et al. Stroke. 2016;47:1493-1499

ASTRAL, DRAGON and SEDAN scores predict stroke outcome more accurately than physicians.

ASTRAL, SEDAN and DRAGON scores are three well-validated scores for stroke outcome prediction. Whether these scores predict stroke outcome more accurately compared with physicians interested in stroke was investigated. Physicians interested in stroke were invited to an online anonymous survey to provide outcome estimates in randomly allocated structured scenarios of recent real-life stroke patients. Their estimates were compared to scores' predictions in the same scenarios. An estimate was considered accurate if it was within 95% confidence intervals of actual outcome. In all, 244 participants from 32 different countries responded assessing 720 real scenarios and 2636 outcomes. The majority of physicians' estimates were inaccurate (1422/2636, 53.9%). 400 (56.8%) of physicians' estimates about the percentage probability of 3-month modified Rankin score (mRS) > 2 were accurate compared with 609 (86.5%) of ASTRAL score estimates (P < 0.0001). 394 (61.2%) of physicians' estimates about the percentage probability of post-thrombolysis symptomatic intracranial haemorrhage were accurate compared with 583 (90.5%) of SEDAN score estimates (P < 0.0001). 160 (24.8%) of physicians' estimates about post-thrombolysis 3-month percentage probability of mRS 0-2 were accurate compared with 240 (37.3%) DRAGON score estimates (P < 0.0001). 260 (40.4%) of physicians' estimates about the percentage probability of post-thrombolysis mRS 5-6 were accurate compared with 518 (80.4%) DRAGON score estimates (P < 0.0001). ASTRAL, DRAGON and SEDAN scores predict outcome of acute ischaemic stroke patients with higher accuracy compared to physicians interested in stroke.

External Validation of the ASTRAL and DRAGON Scores for Prediction of Functional Outcome in Stroke.

ASTRAL (Acute Stroke Registry and Analysis of Lausanne) and DRAGON (includes dense middle cerebral artery sign, prestroke modified Rankin Scale score, age, glucose, onset to treatment, National Institutes of Health Stroke Scale score) are 2 recently developed scores for predicting functional outcome after acute stroke in unselected acute ischemic stroke patients and in patients treated with intravenous thrombolysis, respectively. We aimed to perform external validation of these scores to assess their predictive performance in the large multicentre Safe Implementation of Thrombolysis in Stroke-International Stroke Thrombolysis Register. We calculated the ASTRAL and DRAGON scores in 36 131 and 33 716 patients, respectively, registered in Safe Implementation of Thrombolysis in Stroke-International Stroke Thrombolysis Register between 2003 and 2013. The proportion of patients with 3-month modified Rankin Scale scores of 3 to 6 was observed for each score point and compared with the predicted proportion according to the risk scores. Calibration was assessed using calibration plots, and predictive performance was assessed using area under the curve of the receiver operating characteristic. Multivariate logistic regression coefficients for the variables in the 2 scores were compared with the original derivation cohorts. The ASTRAL showed an area under the curve of 0.790 (95% confidence interval, 0.786-0.795) and the DRAGON an area under the curve of 0.774 (95% confidence interval, 0.769-0.779). All ASTRAL parameters except range of visual fields and all DRAGON parameters were significantly associated with functional outcome in multivariate analysis. The ASTRAL and DRAGON scores show an acceptable predictive performance. ASTRAL does not require imaging-data and therefore may have an advantage for the use in prehospital patient assessment. Prospective studies of both scores evaluating the impact of their use on patient outcomes after intravenous thrombolysis and endovascular therapy are needed.

The DRAGON Score Predicts Functional Outcomes in Acute Ischemic Stroke Patients Receiving both Intravenous Tissue Plasminogen Activator (IVtPA) and Endovascular Therapy (I6.013)

The DRAGON Score Predicts Functional Outcomes in Acute Ischemic Stroke Patients Receiving both Intravenous Tissue Plasminogen Activator (IVtPA) and Endovascular Therapy (I6.013)

The DRAGON Score Predicts Functional Outcomes in Acute Ischemic Stroke Patients Receiving both Intravenous Tissue Plasminogen Activator (IVtPA) and Endovascular Therapy (P1.185)

The DRAGON Score Predicts Functional Outcomes in Acute Ischemic Stroke Patients Receiving both Intravenous Tissue Plasminogen Activator (IVtPA) and Endovascular Therapy (P1.185)

Predicting Prognosis of Mechanical Thrombectomy in Acute Ischemic Stroke Patients Using Modified DRAGON Score

Background: The DRAGON score is reportedly useful for predicting the outcome of intravenous thrombolysis. This study tested whether the modified DRAGON (mDRAGON) score, in which the onset-to-treatment time is extended, can predict the long-term outcome of transient ischemic stroke (AIS) patients who are candidates for mechanical thrombectomy (MT). Methods: We assessed 40 AIS patients who were treated by MT alone or in combination with intravenous tissue plasminogen activator. The mDRAGON score is based on the following findings: hyperdense cerebral artery sign/early infarct signs on computed tomography (both=2, either=1, none=0), prestroke modified Rankin scale (mRS) score (>1=1), age (≥80 years=2, 65-79 years=1, <65 years=0), glucose level (>144 mg/dL=1), onset-to-treatment time (>230 minutes=1), and baseline National Institutes of Health Stroke Scale score (>15=3, 10-15=2, 5-9=1, 0-4=0). Receiver operating characteristics (ROC) curve analysis was used to compare the performance of the mDRAGON score with the performances of other stroke prediction scores. Results: Among 40 AIS patients treated with MT, the proportions with a good outcome (mRS score=0-2) in the groups with mDRAGON scores of 2 or 3, 4 or 5, 6 or 7, and 8-10 were 75%, 20%, 0%, and 0%, respectively, while the corresponding proportions with a poor outcome (mRS score=3-6) were 25%, 80%, 100%, and 100%. For the prediction of a good outcome at 3 months (mRS score=0-2), the area under the ROC curve of the mDRAGON scores was 0.87 (0.76-0.90). Conclusions: The mDRAGON score can be used to reliably predict the clinical outcome of AIS patients following endovascular treatment. Key Words: Stroke, Endovascular procedures, Prognosis

Validation of the DRAGON Score in a Chinese Population to Predict Functional Outcome of Intravenous Thrombolysis–Treated Stroke Patients

The DRAGON score predicts functional outcome of ischemic stroke patients treated with intravenous thrombolysis. Our aim was to evaluate its utility in a Chinese stroke population. Patients with acute ischemic stroke treated with intravenous thrombolysis were prospectively registered in the Thrombolysis Implementation and Monitor of acute ischemic Stroke in China. We excluded patients with basilar artery occlusion and missing data, leaving 970 eligible patients. We calculated the DRAGON score, and the clinical outcome was measured by the modified Rankin Scale at 3 months. Model discrimination was quantified by calculating the C statistic. Calibration was assessed using Pearson correlation coefficient. The C statistic was .73 (.70-.76) for good outcome and .75 (.70-.79) for miserable outcome. Proportions of patients with good outcome were 94%, 83%, 70%, and 0% for 0 to 1, 2, 3, and 8 to 10 score points, respectively. Proportions of patients with miserable outcome were 0%, 3%, 9%, and 50% for 0 to 1, 2, 3, and 8 to 10 points, respectively. There was high correlation between predicted and observed probability of 3-month favorable and miserable outcome in the external validation cohort (Pearson correlation coefficient, .98 and .98, respectively, both P < .0001). The DRAGON score showed good performance to predict functional outcome after tissue-type plasminogen activator treatment in the Chinese population. This study demonstrated the accuracy and usability of the DRAGON score in the Chinese population in daily practice.