Department of Neurology, All India Institute of Medical Sciences, New Delhi, India.
Neurovascular Research Laboratory, Vall d'Hebron Institute of Research, Universitat Autònoma de Barcelona, Barcelona, Spain.
Int J Stroke. 2020 Oct;15(7):704-721. doi: 10.1177/1747493020946157. Epub 2020 Aug 3.
Correct diagnosis of stroke and its subtypes is pivotal in early stages for optimum treatment.
The aim of this systematic review and meta-analysis is to summarize the published evidence on the potential of blood biomarkers in the diagnosis and differentiation of stroke subtypes.
A literature search was conducted for papers published until 20 April 2020 in PubMed, EMBASE, Cochrane Library, TRIP, and Google Scholar databases to search for eligible studies investigating the role of blood biomarkers in diagnosing stroke. Quality assessment was done using modified Quality Assessment of Diagnostic Accuracy Studies questionnaire. Pooled standardized mean difference and 95% confidence intervals were calculated. Presence of heterogeneity among the included studies was investigated using the Cochran's statistic and metric tests. If was < 50% then a fixed-effect model was applied else a random-effect model was applied. Risk of bias was assessed using funnel plots and between-study heterogeneity was assessed using meta-regression and sensitivity analyses. Entire statistical analysis was conducted in STATA version 13.0.
A total of 40 studies including patients with 5001 ischemic strokes, 756 intracerebral hemorrhage, 554 stroke mimics, and 1774 healthy control subjects analyzing 25 biomarkers (within 24 h after symptoms onset/after the event) were included in our meta-analysis; 67.5% of studies had moderate evidence of quality. Brain natriuretic peptide, matrix metalloproteinase-9, and D-dimer significantly differentiated ischemic stroke from intracerebral hemorrhage, stroke mimics, and health control subjects ( < 0.05). Glial fibrillary acidic protein successfully differentiated ischemic stroke from intracerebral hemorrhage (standardized mean difference -1.04; 95% confidence interval -1.46 to -0.63) within 6 h. No studies were found to conduct a meta-analysis of blood biomarkers differentiating transient ischemic attack from healthy controls and stroke mimics.
This meta-analysis highlights the potential of brain natriuretic peptide, matrix metalloproteinase-9, D-dimer, and glial fibrillary acidic protein as diagnostic biomarkers for stroke within 24 h. Results of our meta-analysis might serve as a platform for conducting further targeted proteomics studies and phase-III clinical trials. CRD42019139659.
正确诊断中风及其亚型对于早期的最佳治疗至关重要。
本系统评价和荟萃分析旨在总结已发表的关于血液生物标志物在诊断和区分中风亚型方面的潜在作用的证据。
对截至 2020 年 4 月 20 日在 PubMed、EMBASE、Cochrane 图书馆、TRIP 和 Google Scholar 数据库中发表的论文进行文献检索,以寻找评估血液生物标志物在诊断中风中作用的合格研究。使用改良的诊断准确性研究质量评估问卷进行质量评估。计算汇总标准化均数差和 95%置信区间。使用 Cochran's 统计量和 I 2 度量检验研究之间的异质性。如果 I 2 < 50%,则应用固定效应模型,否则应用随机效应模型。使用漏斗图评估偏倚风险,使用 meta 回归和敏感性分析评估研究间异质性。整个统计分析均在 STATA 版本 13.0 中进行。
共有 40 项研究纳入了 5001 例缺血性中风患者、756 例颅内出血患者、554 例中风模拟患者和 1774 例健康对照者,分析了 25 种生物标志物(症状发作后 24 小时内/发病后);67.5%的研究具有中等质量证据。脑利钠肽、基质金属蛋白酶-9 和 D-二聚体显著区分了缺血性中风与颅内出血、中风模拟和健康对照组(<0.05)。胶质纤维酸性蛋白在 6 小时内成功区分了缺血性中风与颅内出血(标准化均数差 -1.04;95%置信区间 -1.46 至 -0.63)。未发现研究对短暂性脑缺血发作与健康对照和中风模拟进行血液生物标志物的荟萃分析。
本荟萃分析强调了脑利钠肽、基质金属蛋白酶-9、D-二聚体和胶质纤维酸性蛋白在 24 小时内作为中风诊断生物标志物的潜力。我们的荟萃分析结果可能为进一步开展靶向蛋白质组学研究和 III 期临床试验提供平台。CRD42019139659。