Severity: Warning
Message: file_get_contents(https://...@gmail.com&api_key=61f08fa0b96a73de8c900d749fcb997acc09&a=1): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests
Filename: helpers/my_audit_helper.php
Line Number: 197
Backtrace:
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 197
Function: file_get_contents
File: /var/www/html/application/helpers/my_audit_helper.php
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Function: simplexml_load_file_from_url
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3165
Function: getPubMedXML
File: /var/www/html/application/controllers/Detail.php
Line: 597
Function: pubMedSearch_Global
File: /var/www/html/application/controllers/Detail.php
Line: 511
Function: pubMedGetRelatedKeyword
File: /var/www/html/index.php
Line: 317
Function: require_once
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Objective: This 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.
Methods: We 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.
Results: Our 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).
Conclusions: In 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.
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http://dx.doi.org/10.1016/j.jstrokecerebrovasdis.2024.107919 | DOI Listing |