The Prognostic Value of the iScore, the PLAN Score, and the ASTRAL Score in Acute Ischemic Stroke

Wang, Weiying; Sang, Wenwen; Jin, Dong-Yan; Yan, Sha; Yuan, Hong; Zhang, Huan; Yang, Xu

doi:10.1016/j.jstrokecerebrovasdis.2017.01.013

Cited by 14 publications

(7 citation statements)

References 16 publications

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“…The ASTRAL scale has been subsequently externally validated by seven studies, with six assessing predictive value based on AUROC estimates (42–48). Within these, ASTRAL was found to have fair to good discriminatory power, with the exception of one study, involving a Brazilian cohort (AUROC 0.67) (44).…”

Section: Resultsmentioning

confidence: 99%

“…The scale has been further externally validated in 15 studies (48, 54, 79–91). The iScore has been applied not only to predict mortality, but also poor functional outcome, institutionalization, clinical response, hemorrhagic transformations following thrombolytic therapy, and healthcare costs.…”

Section: Resultsmentioning

confidence: 99%

“…The scale's performance was not assessed in an independent dataset. External validation was however conducted in two subsequent studies (48, 73). The scale was applied for prediction of good functional outcome, poor outcome, and mortality.…”

Section: Resultsmentioning

confidence: 99%

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Thinking About the Future: A Review of Prognostic Scales Used in Acute Stroke

2019

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Background: There are many prognostic scales that aim to predict functional outcome following acute stroke. Despite considerable research interest, these scales have had limited impact in routine clinical practice. This may be due to perceived problems with internal validity (quality of research), as well as external validity (generalizability of results). We set out to collate information on exemplar stroke prognosis scales, giving particular attention to the scale content, derivation, and validation. Methods: We performed a focused literature search, designed to return high profile scales that use baseline clinical data to predict mortality or disability. We described prognostic utility and collated information on the content, development and validation of the tools. We critically appraised chosen scales based on the CHecklist for critical Appraisal and data extraction for systematic Reviews of prediction Modeling Studies (CHARMS). Results: We chose 10 primary scales that met our inclusion criteria, six of which had revised/modified versions. Most primary scales used 5 input variables (range: 4–13), with substantial overlap in the variables included. All scales included age, eight included a measure of stroke severity, while five scales incorporated pre-stroke level of function (often using modified Rankin Scale), comorbidities and classification of stroke type. Through our critical appraisal, we found issues relating to excluding patients with missing data from derivation studies, and basing the selection of model variable on significance in univariable analysis (in both cases noted for six studies). We identified separate external validation studies for all primary scales but one, with a total of 60 validation studies. Conclusions: Most acute stroke prognosis scales use similar variables to predict long-term outcomes and most have reasonable prognostic accuracy. While not all published scales followed best practice in development, most have been subsequently validated. Lack of clinical uptake may relate more to practical application of scales rather than validity. Impact studies are now necessary to investigate clinical usefulness of existing scales.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

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Thinking About the Future: A Review of Prognostic Scales Used in Acute Stroke

2019

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“…Symptomatic haemorrhagic transformation (sHT) within 24 hours of stroke onset was diagnosed in 20 (29.4%) patients, of whom one underwent IVT alone, nine underwent IVT plus MT, and 10 underwent MT alone. The ASTRAL score was significantly higher in patients who developed sHT compared to non-sHT patients [36 (34)(35)(36)(37)(38) vs. 24 (17)(18)(19)(20)(21)(22)(23)(24)(25)(26)(27)(28)(29)(30)(31)(32); p < 0.001, Figure 1A]. In ROC analysis with respect to sHT, the area under the curve (AUC) was 0.877 (95% CI, 0.789-0.965; SE, 0.045; Figure 1B).…”

Section: Resultsmentioning

confidence: 99%

Does ASTRAL score at hospital admission predict symptomatic haemorrhagic transformation in acute ischaemic stroke after revascularisation? A pilot single-centre study

Świtońska

Słomka

Piekuś-Słomka

et al. 2022

Neurol Neurochir Pol.

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Introduction.Accurately predicting outcomes after acute ischaemic stroke (AIS) is a major clinical goal. The aim of this pilot study was to evaluate the prognostic validity and accuracy of the Acute Stroke Registry and Analysis of Lausanne (ASTRAL) score in predicting symptomatic haemorrhagic transformation (sHT) in patients with AIS who have undergone revascularisation. Material and methods.Consecutive patients hospitalised for AIS who underwent treatment with intravenous thrombolysis (IVT) and/or mechanical thrombectomy (MT) were identified, and their ASTRAL scores at hospital admission were estimated. The study endpoint was sHT within 24 hours of stroke onset. The predictive performance of the ASTRAL score was investigated through logistic regression analysis and discrimination and calibration tests.Results. Sixty-eight AIS patients, with a median age of 69 (58-79) years, were included. sHT occurred in 20 (29.4%) of the 68 patients. The ASTRAL score was significantly higher in patients who developed sHT compared to non-sHT patients [36 (34-38) versus 24 (17-32); p<0.001]. The ASTRAL score was an independent predictor of sHT, and showed good discriminative power (area under the curve 0.88; 95% confidence interval, 0.789-0.965). Conclusions and clinical implications.ASTRAL score is an independent predictor of sHT and shows high predictive accuracy in patients with AIS. Future studies are warranted to confirm these results.

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“…These tools have the advantage of being simple and readily available with few variables; therefore, they can make a quick prediction with only the findings within a short time after hospitalization [9]. In previous studies, external validation results for short-term functional outcome prediction of these tools have shown an area under the receiver operating characteristic curve (AUC) range of approximately 0.8, indicating that these tools were effective [10][11][12].…”

Section: Introductionmentioning

confidence: 99%

Machine Learning-Based Three-Month Outcome Prediction in Acute Ischemic Stroke: A Single Cerebrovascular-Specialty Hospital Study in South Korea

et al. 2021

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Background: Functional outcomes after acute ischemic stroke are of great concern to patients and their families, as well as physicians and surgeons who make the clinical decisions. We developed machine learning (ML)-based functional outcome prediction models in acute ischemic stroke. Methods: This retrospective study used a prospective cohort database. A total of 1066 patients with acute ischemic stroke between January 2019 and March 2021 were included. Variables such as demographic factors, stroke-related factors, laboratory findings, and comorbidities were utilized at the time of admission. Five ML algorithms were applied to predict a favorable functional outcome (modified Rankin Scale 0 or 1) at 3 months after stroke onset. Results: Regularized logistic regression showed the best performance with an area under the receiver operating characteristic curve (AUC) of 0.86. Support vector machines represented the second-highest AUC of 0.85 with the highest F1-score of 0.86, and finally, all ML models applied achieved an AUC > 0.8. The National Institute of Health Stroke Scale at admission and age were consistently the top two important variables for generalized logistic regression, random forest, and extreme gradient boosting models. Conclusions: ML-based functional outcome prediction models for acute ischemic stroke were validated and proven to be readily applicable and useful.

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The Prognostic Value of the iScore, the PLAN Score, and the ASTRAL Score in Acute Ischemic Stroke

Cited by 14 publications

References 16 publications

Thinking About the Future: A Review of Prognostic Scales Used in Acute Stroke

Thinking About the Future: A Review of Prognostic Scales Used in Acute Stroke

Does ASTRAL score at hospital admission predict symptomatic haemorrhagic transformation in acute ischaemic stroke after revascularisation? A pilot single-centre study

Machine Learning-Based Three-Month Outcome Prediction in Acute Ischemic Stroke: A Single Cerebrovascular-Specialty Hospital Study in South Korea

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