ArticleJournal of the American Heart Association2024
Inflammation-Derived and Clinical Indicator-Based Predictive Model for Ischemic Stroke Recovery.
Article in Journal of the American Heart Association, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
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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
5 citing papers in PubMed.
- Collateral Circulation andJournal of the American Heart Association · 2025Trial
- Microglial Mitochondrial Dysfunction: The Storm Center of Post-Stroke Neuroinflammation.CNS neuroscience & therapeutics · 2026Review
- Multi-dimensional MRI representation and privileged learning approaches to functional outcome prediction for ischemic stroke patients.NPJ digital medicine · 2026Article
- Verification of the predictive value of EV-associated biomarkers MMP9 and CEACAM1 in rehabilitation of ischemic stroke.Extracellular vesicles and circulating nucleic acids · 2026Article
- Association of systemic immune-inflammation index with severity in acute ischemic stroke patients: a cross-sectional study.Frontiers in neurology · 2025Article
Corrections and comments
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Authors and funding
15 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundNeuroinflammatory responses are closely associated with poststroke prognosis severity. This study aimed to develop a predictive model, combining inflammation-derived markers and clinical indicators, for distinguishing functional outcomes in patients with subacute ischemic stroke. METHODS AND
resultsBased on activities of daily living assessments, ischemic stroke participants were categorized into groups with little effective (LE) recovery and obvious effective (OE) recovery. Initial biocandidates were identified by overlapping differentially expressed proteins from proteomics of clinical serum samples (5 LE, 5 OE, and 6 healthy controls) and differentially expressed genes from an RNA sequence of the ischemic cortex in middle cerebral artery occlusion mice (n=3). Multidimensional validations were conducted in ischemia-reperfusion models and a clinical cohort (15 LE, 11 OE, and 18 healthy controls). Models of robust biocandidates combined with clinical indicators were developed with machine learning in the training data set and prediction in another test data set (15 LE and 11 OE). We identified 194 differentially expressed proteins (LE versus healthy controls) and 174 differentially expressed proteins (OE versus healthy controls) in human serum, and 5121 differentially expressed genes (day 3) and 5906 differentially expressed genes (day 7) in middle cerebral artery occlusion mice cortex. Inflammation-derived biomarkers TIMP1 (tissue inhibitor metalloproteinase-1) and galactosidase-binding protein LGLAS3 (galectin-3) exhibited robust increases under ischemic injury in mice and humans. TIMP1 and LGALS3 coupled with clinical indicators (hemoglobin, low-density lipoprotein cholesterol, and uric acid) were developed into a combined model for differentiating functional outcome with high accuracy (area under the curve, 0.8).
conclusionsThe combined model is a valuable tool for evaluating prognostic outcomes, and the predictive factors can facilitate development of better treatment strategies.
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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 Socratic graph.