ArticleNeurotherapeutics : the journal of the American Society for Experimental NeuroTherapeutics2019
High-Throughput Profiling of Circulating Antibody Signatures for Stroke Diagnosis Using Small Volumes of Whole Blood.
Article in Neurotherapeutics : the journal of the American Society for Experimental NeuroTherapeutics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 2 of them syntheses that pooled it.
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.
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Who cites it
8 citing papers in PubMed, 2 syntheses or guidelines pooled it, 8 citations in OpenAlex.
- Systematic review and meta-analysis of stroke blood biomarker data highlights need for more translational research methods.Nature communications · 2026Pooled it
- Multi-Level Biomarkers for Early Diagnosis of Ischaemic Stroke: A Systematic Review and Meta-Analysis.International journal of molecular sciences · 2023Pooled it
- Next-Generation Stroke Biomarkers: Bridging the Gap Between Innovation and Translation.Journal of clinical medicine · 2026Review
- Proteomic analysis of whole blood to investigate the therapeutic effects of nervonic acid on cerebral ischemia-reperfusion injury in rats.Frontiers in cell and developmental biology · 2025Article
- Proteomic advance of ischemic stroke: preclinical, clinical, and intervention.Metabolic brain disease · 2023Review
- Use of deep artificial neural networks to identify stroke during triage via subtle changes in circulating cell counts.BMC neurology · 2022Article
- Stroke Proteomics: From Discovery to Diagnostic and Therapeutic Applications.Circulation research · 2022Review
- Large-scale informatic analysis to algorithmically identify blood biomarkers of neurological damage.Proceedings of the National Academy of Sciences of the United States of America · 2020Article
Corrections and comments
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Authors and funding
5 authors at 3 institutions in 1 country.
Funding
Abstract
Accurate stroke recognition during triage can streamline care and afford patients earlier access to life-saving interventions. However, the tools currently available to clinicians for prehospital and early in-hospital identification of stroke are limited. The peripheral immune system is intricately involved in stroke pathology and thus may be targetable for the development of immunodiagnostics. In this preliminary study, we sought to determine whether the circulating antibody pool is altered early in stroke, and whether such alterations could be leveraged for diagnosis. One hundred microliters of peripheral whole blood was sampled from 19 ischemic stroke patients, 17 hemorrhagic stroke patients, and 20 stroke mimics in the acute phase of care. A custom-fabricated high-density peptide array comprising 125,000 unique probes was used to assess the binding characteristics of blood-borne antibodies, and a random forest-based approach was used to select a parsimonious set of probes with an optimal ability to discriminate between groups. The coordinate antibody binding intensities of the top 17 probes identified in our analysis displayed an ability to differentiate the total pool of stroke patients from stroke mimics with 92% sensitivity and 90% specificity, as well as detect hemorrhage with 88% sensitivity and 87% specificity, as determined using a same-set cross-validation. These preliminary findings suggest that stroke-associated alterations in the circulating antibody pool may have clinical utility for diagnosis during triage, and that such a possibility warrants further investigation.
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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 OpenQuestion graph.