{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Pan J"],"funding":["Natural science of foundation of Zhejiang province"],"pagination":["1620"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC11675862"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["15(12)"],"pubmed_abstract":["Ischemic stroke is a serious cerebrovascular disease, highlighting the urgent need for reliable biomarkers for early diagnosis. Recent reports suggest that long non-coding RNAs (lncRNAs) can be potential biomarkers for ischemic stroke. Therefore, our study seeks to investigate the potential diagnostic value of lncRNAs for ischemic stroke by analyzing existing research. A comprehensive literature search was conducted across the PubMed, ScienceDirect, Wiley Online Library, and Web of Science databases for articles published up to July 10, 2024. Statistical analyses were performed using Stata 17.0 software to calculate pooled sensitivity, specificity, positive likelihood ratio (PLR), diagnostic odds ratio (DOR), negative likelihood ratio (NLR), and area under the curve (AUC). Heterogeneity wa"],"journal":["Genes"],"pubmed_title":["Long Non-Coding RNAs as Diagnostic Biomarkers for Ischemic Stroke: A Systematic Review and Meta-Analysis."],"pmcid":["PMC11675862"],"funding_grant_id":["LZ20H090002"],"pubmed_authors":["Pan J","Fan W","Gu C","Xi Y","Wang P","Wang Y"],"additional_accession":[]},"is_claimable":false,"name":"Long Non-Coding RNAs as Diagnostic Biomarkers for Ischemic Stroke: A Systematic Review and Meta-Analysis.","description":"Ischemic stroke is a serious cerebrovascular disease, highlighting the urgent need for reliable biomarkers for early diagnosis. Recent reports suggest that long non-coding RNAs (lncRNAs) can be potential biomarkers for ischemic stroke. Therefore, our study seeks to investigate the potential diagnostic value of lncRNAs for ischemic stroke by analyzing existing research. A comprehensive literature search was conducted across the PubMed, ScienceDirect, Wiley Online Library, and Web of Science databases for articles published up to July 10, 2024. Statistical analyses were performed using Stata 17.0 software to calculate pooled sensitivity, specificity, positive likelihood ratio (PLR), diagnostic odds ratio (DOR), negative likelihood ratio (NLR), and area under the curve (AUC). Heterogeneity wa","dates":{"release":"2024-01-01T00:00:00Z","publication":"2024 Dec","modification":"2026-04-19T03:26:33.058Z","creation":"2025-04-19T21:29:32.1Z"},"accession":"S-EPMC11675862","cross_references":{"pubmed":["39766887"],"doi":["10.3390/genes15121620"]}}