Blood glucose level affects prognosis of patients who received intravenous thrombolysis after acute ischemic stroke? A meta-analysis

Wang, Yue; Jiang, Guannan; Zhang, Jie; Wang, Jingfeng; You, Wanchun; Zhu, Juehua

doi:10.3389/fendo.2023.1120779

Cited by 6 publications

(3 citation statements)

References 38 publications

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“…The third factor that enhances the model's predictive accuracy is the RBS level obtained at the presentation. This study corroborates previous research by demonstrating a correlation between higher RBS levels at admission and an unfavorable prognosis [46]. In this study, the mean RBS was 9.3 ± 4.6 mmol/L, and the average RBS of patients with an unfavorable mRS at 90 days was significantly higher than that of the favorable group (9.9 vs. 8.7, with a p-value below 0.05).…”

Section: Discussionsupporting

confidence: 91%

Predicting 90-Day Prognosis in Ischemic Stroke Patients Post Thrombolysis Using Machine Learning

Abujaber,

Albalkhi,

Imam

et al. 2023

JPM

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(1) Objective: This study aimed to construct a machine learning model for predicting the prognosis of ischemic stroke patients who underwent thrombolysis, assessed through the modified Rankin Scale (mRS) score 90 days after discharge. (2) Methods: Data were sourced from Qatar’s stroke registry covering January 2014 to June 2022. A total of 723 patients with ischemic stroke who had received thrombolysis were included. Clinical variables were examined, encompassing demographics, stroke severity indices, comorbidities, laboratory results, admission vital signs, and hospital-acquired complications. The predictive capabilities of five distinct machine learning models were rigorously evaluated using a comprehensive set of metrics. The SHAP analysis was deployed to uncover the most influential predictors. (3) Results: The Support Vector Machine (SVM) model emerged as the standout performer, achieving an area under the curve (AUC) of 0.72. Key determinants of patient outcomes included stroke severity at admission; admission systolic and diastolic blood pressure; baseline comorbidities, notably hypertension (HTN) and coronary artery disease (CAD); stroke subtype, particularly strokes of undetermined origin (SUO); and hospital-acquired urinary tract infections (UTIs). (4) Conclusions: Machine learning can improve early prognosis prediction in ischemic stroke, especially after thrombolysis. The SVM model is a promising tool for empowering clinicians to create individualized treatment plans. Despite limitations, this study contributes to our knowledge and encourages future research to integrate more comprehensive data. Ultimately, it offers a pathway to improve personalized stroke care and enhance the quality of life for stroke survivors.

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Section: Discussionsupporting

confidence: 91%

Predicting 90-Day Prognosis in Ischemic Stroke Patients Post Thrombolysis Using Machine Learning

Abujaber,

Albalkhi,

Imam

et al. 2023

JPM

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“…Interestingly, patients with initially elevated blood glucose levels had poorer usual activity scores. This finding correlates with the results of a recent meta-analysis, showing that acute stroke patients with elevated blood glucose levels who received systemic thrombolytic therapy had a worse outcome as measured by mRS at 90 days and a higher rate of symptomatic intracerebral haemorrhage [ 49 ]. Possible mechanisms for such detrimental effects of hyperglycaemia have been discussed and include exacerbation of pathophysiological mechanisms such as thrombo-inflammation known to negatively impact infarct evolution final outcome [ 9 , 11 , 40 , 41 ].…”

Section: Discussionsupporting

confidence: 88%

Functional long-term outcome following endovascular thrombectomy in patients with acute ischemic stroke

Rogalewski,

Klein,

Friedrich

et al. 2024

Neurol. Res. Pract.

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Endovascular thrombectomy (EVT) is the most effective treatment for acute ischemic stroke caused by large vessel occlusion (LVO). Yet, long-term outcome (LTO) and health-related quality of life (HRQoL) in these patients have rarely been addressed, as opposed to modified Rankin scale (mRS) recordings. We analysed demographic data, treatment and neuroimaging parameters in 694 consecutive stroke patients in a maximum care hospital. In 138 of these patients with respect on receipt of written informed consent, LTO and HRQoL were collected over a period of 48 months after EVT using a standardised telephone survey (median 2.1 years after EVT). Age < 70 years (OR 4.82), lower NIHSS on admission (OR 1.11), NIHSS ≤ 10 after 24 h (OR 11.23) and complete recanalisation (mTICI3) (OR 7.79) were identified as independent predictors of favourable LTO. Occurrence of an infection requiring treatment within the first 72 h was recognised as a negative predictor for good long-term outcome (OR 0.22). Patients with mRS > 2 according to the telephone survey more often had complaints regarding mobility, self‐care, and usual activity domains of the HRQoL. Our results underline a sustainable positive effect of effective EVT on the quality of life in LVO stroke. Additionally, predictive parameters of outcome were identified, that may support clinical decision making in LVO stroke.

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“…16 Epidemiological studies have demonstrated that an extended period of elevated hyperglycemia is associated with magnified infarct dimensions, heightened susceptibility to reperfusion complications, deterioration of stroke-related lesions, and potentially elevated mortality rates. 17 Currently, the precise mechanism underlying the aggravation of brain damage due to glucose fluctuations remains incompletely elucidated. However, several potential rationales exist for this phenomenon.…”

Section: Discussionmentioning

confidence: 99%

Effect of admission serum glucose on the clinical prognosis of patients with acute ischemic stroke receiving alteplase intravenous thrombolysis

Huang,

2023

Int J Immunopathol Pharmacol

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Objective: To investigate the effect of admission serum glucose on the clinical prognosis of patients with acute ischemic stroke receiving intravenous alteplase thrombolysis. Methods: Patients with acute ischemic stroke who received intravenous alteplase thrombolysis between January 2016 and December 2017 were enrolled. The clinical prognosis was assessed using the modified Rankin Scale (mRs) at 90 days after onset. Univariate and multivariate logistic regression analyses were conducted to investigate whether admission serum glucose was an independent factor in the 90-day prognosis. The predictive value of admission serum glucose for a 90-day poor prognosis was evaluated using receiver operating characteristic (ROC) curves. All patients were divided into two groups based on admission serum glucose levels: high admission serum glucose (above the cut-off value) and low admission serum glucose (below the cut-off value). The 90-day prognosis of patients with different admission serum glucose was analyzed. Results: A total of 138 patients were enrolled, including 79 males (57.24%), with a mean age of (68 ± 12) years and a median baseline National Institutes of Health Stroke Scale (NIHSS) score of 9 (6 to 13.75). There were 74 cases (53.62%) in the good prognosis group and 64 cases (46.37%) in the poor prognosis group. The results of the univariate analysis indicated that admission serum glucose in the good prognosis group was significantly lower than that in the poor prognosis group [(7.45 ± 2.31) versus (8.80 ± 3.65), p < .05]. Logistic regression analysis revealed that the admission serum glucose level was an independent risk factor for clinical prognosis at 90 days after onset (OR = 1.24, 95% CI:1.01–1.52). ROC curve analysis showed that the cutoff value of admission serum glucose for predicting poor prognosis 90 days after intravenous thrombolytic therapy with alteplase was 6.77 mmol/l AUC (area under curve) 0.623, 95%CI: 0.53–0.72, sensitivity 68.80%, specificity 52.70%. When compared with the admission serum glucose ≥6.77 mmol/l group (83 cases), the 90-day mRS scores in the admission serum glucose <6.77 mmol/l group (55 cases) were lower [3 (1 to 5) scores versus 1 (0 to 3) scores, Z = 2.89, p < .05]. Conclusions: In patients with acute ischemic stroke receiving intravenous alteplase thrombolytic therapy, a higher admission serum glucose level is an independent predictor of adverse neurological outcomes at 90 days postoperatively.

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Blood glucose level affects prognosis of patients who received intravenous thrombolysis after acute ischemic stroke? A meta-analysis

Cited by 6 publications

References 38 publications

Predicting 90-Day Prognosis in Ischemic Stroke Patients Post Thrombolysis Using Machine Learning

Predicting 90-Day Prognosis in Ischemic Stroke Patients Post Thrombolysis Using Machine Learning

Functional long-term outcome following endovascular thrombectomy in patients with acute ischemic stroke

Effect of admission serum glucose on the clinical prognosis of patients with acute ischemic stroke receiving alteplase intravenous thrombolysis

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