ArticleHeliyon2024
Beyond diagnosis: Leveraging routine blood and urine biomarkers to predict severity and functional outcome in acute ischemic stroke.
Article in Heliyon, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
10 citing papers in PubMed, 1 synthesis or guideline pooled it, 7 citations in OpenAlex.
- Predictive performance of machine learning models in acute ischemic stroke: a systematic review and meta-analysis.Frontiers in neurologyPooled it
- Article
- Predicting post-stroke functional outcome using explainable machine learning and integrated data.Scientific reports · 2026Article
- mHealth-Enabled Stroke Screening for Pediatric Sickle Cell Disease in Low-Resource Settings: Systematic Literature Review of Critical Barriers, Emerging Technologies, and AI-Driven Solutions.JMIR pediatrics and parenting · 2026Review
- Molecular Mechanisms of the Microbiota-Gut-Brain Axis in the Onset and Progression of Stroke.International journal of molecular sciences · 2025Review
- Machine Learning in Myasthenia Gravis: A Systematic Review of Prognostic Models and AI-Assisted Clinical Assessments.Diagnostics (Basel, Switzerland) · 2025Review
- Personalized Predictions of Therapeutic Hypothermia Outcomes in Cardiac Arrest Patients with Shockable Rhythms Using Explainable Machine Learning.Diagnostics (Basel, Switzerland) · 2025Article
- Impact of hemoglobin levels on acute ischemic stroke severity.Frontiers in neurology · 2025Article
- Article
- Identification of Urine Metabolic Markers of Stroke Risk Using Untargeted Nuclear Magnetic Resonance Analysis.International journal of molecular sciences · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: The initial severity of acute ischemic stroke (AIS) is a crucial predictor of the disease outcome. In this study, blood and urine biomarkers from patients with AIS were measured to estimate stroke severity and predict long-term stroke outcomes. Methods: The medical records of patients with AIS between October 2016 and May 2020 were retrospectively analyzed. The relationships of blood and urine biomarkers with stroke severity at admission were evaluated in patients with AIS. Predictive models for initial stroke severity and long-term prognosis were then developed using a panel of identified biomarkers. Results: A total of 2229 patients were enrolled. Univariate analysis revealed 12 biomarkers associated with the National Institutes of Health Stroke Scale scores at admission. The area under the curve values for predicting initial stroke severity and long-term prognosis on the basis of these biomarkers were 0.7465, 0.7470, and 0.8061, respectively. Among multiple tested machine-learning, eXtreme gradient boosting exhibited the highest effectiveness in predicting 90-day modified Rankin Scale scores. SHapley Additive exPlanations revealed fasting glucose, albumin, hemoglobin, prothrombin time, and urine-specific gravity to be the top five most crucial biomarkers. Conclusion: These findings demonstrate that clinically available blood and urine biomarkers can effectively estimate initial stroke severity and predict long-term prognosis in patients with AIS. Our results provide a scientific basis for developing tailored clinical treatment and management strategies for AIS, through incorporating liquid biomarkers into stroke risk assessment and patient care protocols for patients with AIS.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.