Serum Albumin, Body Mass Index, and Preceding Xa and P2Y12 Inhibitors Predict Prognosis of Recurrent Ischemic Stroke

Kiboshi, Ryusei; Satoh, Sousuke; Mikami, Kasumi; Kitajima, Maiko; Urushizaka, Mayumi; Metoki, Norifumi; Osanai, Tomohiro

doi:10.1016/j.jstrokecerebrovasdis.2021.105681

Cited by 4 publications

(3 citation statements)

References 20 publications

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“…Previous studies have confirmed the independent predictive value of serum albumin levels in patients with first acute ischaemic stroke for predicting in-hospital mortality and stroke severity. Despite the results of some studies showing that for 25% of stroke patients, serum albumin does not contribute to the improvement of clinical outcome, it still has a role as a predictor of rehabilitation outcome in both first and recurrent strokes [27] . In addition, serum albumin level reflects the overall nutritional status of the patient to a certain extent, which is also important for the recovery of motor function after stroke.…”

Section: Discussionmentioning

confidence: 91%

Integrating Multimodal Information and Advanced Machine Learning Algorithms for Function Assessment and Rehabilitation Prediction in Patients after Cerebral Hemorrhage

Liu,

He,

Wang

et al. 2024

Preprint

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Background The recovery process for patients post-cerebral hemorrhage is influenced by various factors. Crucially, multimodal information, including results from rehabilitation function assessments, imaging examinations, and laboratory tests, is essential for evaluating motor function and predicting the rehabilitation outcome in these patients. Methods A retrospective analysis was conducted, utilizing data from 315 and 424 patients with post-cerebral hemorrhage. The training set comprised rehabilitation function assessment results, imaging examination data, and laboratory test results, used to establish models for evaluating motor function and predicting rehabilitation outcomes. Clinical characteristics of patients underwent single-factor and multi-factor logistic regression analyses, exploring influencing factors during the recovery process after cerebral hemorrhage. Head CT scans of patients underwent pre-processing, extracting radiomic features for predicting motor function when combined with functional assessment results. Moreover, a GBDT gradient boosting tree model was constructed based on patients' multimodal clinical information and compared with other machine learning models to evaluate rehabilitation outcomes. Separate models for predicting motor function and evaluating rehabilitation were established for patients with cerebral hemorrhage using selected radiomic and clinical features, and the performance of each model was individually assessed. Results Following extensive training and validation with a substantial patient records dataset, the receiver operating characteristic (ROC) analysis reveals the excellent performance of the motor function prediction model we developed for patients post-cerebral hemorrhage. In both five-fold and ten-fold cross-validation, the gradient boosting decision tree (GBDT) algorithm demonstrates superior performance in the post-cerebral hemorrhage rehabilitation assessment compared to other machine learning algorithms. Multifactor analysis indicates that, in predicting motor function after cerebral hemorrhage, factors such as albumin, neutrophil count and percentage, triglycerides, coagulation time, and urea are significant. In rehabilitation assessment, meaningful factors include the age of onset, admission modified Barthel Index (mBI) score, and the initiation of rehabilitation. Conclusion Our study integrates multimodal information and advanced machine learning algorithms, providing a solution for assessing function and predicting rehabilitation in patients after cerebral hemorrhage. The established models hold the potential to provide decision support for clinicians in clinical practice, promoting the realization of personalized rehabilitation treatment.

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Section: Discussionmentioning

confidence: 91%

Integrating Multimodal Information and Advanced Machine Learning Algorithms for Function Assessment and Rehabilitation Prediction in Patients after Cerebral Hemorrhage

Liu,

He,

Wang

et al. 2024

Preprint

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“…In addition, ALB can also play an anti-coagulant role by inhibiting platelet aggregation and increasing the production of anti-aggregation prostaglandin D2, which can play a role in the treatment of IS. [ 46 ] NST capsule can inhibit the expression of pro-inflammatory factor TNF, which suggest that NST capsule may alleviate brain injury of IS by regulating lipid and atherosclerosis, fluid shear stress and atherosclerotic pathways. [ 47 ] According to literature reports, TP53 factor can play a role in regulating glycolysis and apoptosis of cytokines by transferring glucose metabolism to pentose phosphate metabolic pathway, which can reduce oxidative stress response of brain nerves and play a protective role in injured ischemic neurons.…”

Section: Discussionmentioning

confidence: 99%

Multi-target mechanism of Naoshuantong capsule for treatment of Ischemic stroke based on network pharmacology and molecular docking

Yang,

Yan,

et al. 2023

Medicine

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Background: Naoshuantong capsule (NST capsule) is a classic Chinese patent medicine, which can treat ischemic stroke (IS) and has good clinical efficacy. However, its pharmacological mechanism remains to be further explored in the treatment of IS. Methods: The bio-active components and potential targets of NST Capsules were obtained by ETCM and TCMSP databases. In addition, the related targets of IS were collected by Genecard, OMIM, DrugBank, TTD and DisGeNET databases. NST-IS common target was obtained by Venn platform. PPI network of NST-IS common target and the composition - target network diagram of NST Capsule were constructed by Cytoscape3.8.1. Finally, AutoDock was used for molecular docking. Results: 265 targets were predicted from 32 active compounds in NST Capsule, 109 common targets were identified between NST Capsule and IS. The top 10 key targets of PPI network were ALB, TNF, TP53, VEGFA, CASP3, MYC, etc. Enrichment analysis showed that NST capsules treated IS mainly through lipid and atherosclerosis, fluid shear stress and atherosclerosis signaling pathways. Conclusion: Through the methods of network pharmacology and molecular docking, this study clarified that NST capsules play a role in the treatment of IS, which is multi-target, multi-channel and multi-component regulation. This study further explored the pharmacological mechanism of NST capsule in the treatment of IS, which can provide some references for the subsequent research in the pharmacological mechanism of NST capsule.

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“…Serum albumin is an indicator of the nutritional status. Recent studies have shown that decreased serum albumin levels were independently associated with poor prognosis in ischemic stroke 21,22 . The role of albumin as a neuroprotectant has been assessed in the ALIAS (albumin in acute stroke) trial.…”

Section: Discussionmentioning

confidence: 99%

The Hemoglobin, Albumin, Lymphocytes and Platelets (HALP) Predicts Long-term Survival in Posterior Circulation Ischemic Stroke

Wei

Xie

et al. 2021

Preprint

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The survival of posterior circulation ischemic stroke (PCIS) patients is worse. The hemoglobin, albumin, lymphocyte, and platelet (HALP) score is a novel combined index reflecting nutritional and inflammation status. We aimed to evaluate the impact of the HALP score on the prognosis of PCIS. The Kaplan-Meier method with log-rank test was used to draw the survival curves. Cox proportional hazard regression model were performed to determine the independent prognostic factors. The predictive power was evaluated by assessing the area under the receiver operating characteristic (ROC) curve. A total of 238 PCIS patients were retrospectively enrolled, and the median follow-up time was 4.3 years. Based on the Kaplan–Meier curve analysis, it was noticed that a low HALP value was significantly associated with a worse overall survival (P < 0.001). Multivariate Cox analysis showed that age, National Institutes of Health Stroke Scale (NIHSS), and HALP score were independent risk factors for overall survival (HR 1.059, 1.26 and 0.354). Furthermore, the combination of the HALP and NIHSS score improved the prediction performance (AUC 0.888) and appeared to has the ability to accurately identify high-risk patients with poor prognosis.

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Serum Albumin, Body Mass Index, and Preceding Xa and P2Y12 Inhibitors Predict Prognosis of Recurrent Ischemic Stroke

Cited by 4 publications

References 20 publications

Integrating Multimodal Information and Advanced Machine Learning Algorithms for Function Assessment and Rehabilitation Prediction in Patients after Cerebral Hemorrhage

Integrating Multimodal Information and Advanced Machine Learning Algorithms for Function Assessment and Rehabilitation Prediction in Patients after Cerebral Hemorrhage

Multi-target mechanism of Naoshuantong capsule for treatment of Ischemic stroke based on network pharmacology and molecular docking

The Hemoglobin, Albumin, Lymphocytes and Platelets (HALP) Predicts Long-term Survival in Posterior Circulation Ischemic Stroke

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