A Systematic Review and Meta-Analysis Assessing the Accuracy of Blood Biomarkers for the Diagnosis of Ischemic Stroke in Adult and Elderly Populations

Abstract

This study aims to elucidate the methodology and compare the accuracy of different blood biomarkers for diagnosing ischemic stroke (IS). We reviewed 29 articles retrieved from PubMed, MEDLINE, Web of Science, and CINAHL Plus with Full Text. Among these, 23 articles involving 3,494 participants were suitable for meta-analysis. The pooled area under the curve (AUC) of all studies for meta-analysis was 0.89. The pooled sensitivity and specificity were 0.76 (0.74-0.78) and 0.84 (0.83-0.86), respectively. Blood biomarkers from noninpatient settings demonstrated better diagnostic performance than those in inpatient settings (AUC 0.91 vs 0.88). Smaller sample sizes (<100) showed better performance than larger ones (≥100; AUC 0.92 vs 0.86). Blood biomarkers from acute IS (AIS) patients showed higher diagnostic values than those from IS and other stroke types (AUC 0.91 vs 0.87). The diagnostic performance of multiple blood biomarkers was superior to that of a single biomarker (AUC 0.91 vs 0.88). The diagnostic value of blood biomarkers from Caucasians was higher than that from Asians and Africans (AUC 0.90 vs 0.89, 0.75). Blood biomarkers from those with comorbidities (AUC 0.92) showed a better diagnostic performance than those not reporting comorbidities (AUC 0.84). All the subgroups analyzed, including setting, sample size, target IS population, blood biomarker profiling, ethnicity, and comorbidities could lead to heterogeneity. Blood biomarkers have demonstrated sufficient diagnostic accuracy for diagnosing IS and hold promise for integration into routine clinical practice. However, further research is recommended to refine the optimal model for utilizing blood biomarkers in IS diagnosis.

Keywords: blood biomarker; diagnostic test; ischemic stroke; meta-analysis.

Figure 1.

PRISMA flow chart.

Figure 2.

Risk of bias summary using the QUADAS-2. Zhang et al. 2020_a refers to L. J. Zhang et al., 2020, Zhang et al. 2020_b refer to H. T. Zhang et al., 2020.

Figure 3.

SROC for all studies. AUC, 0.89. SROC, summary receiver operating characteristic; AUC, area under the curve.

Figure 4.

Forest plots of sensitivity and specificity of blood biomarkers for diagnosis of IS. The pooled sensitivity is 0.76 (0.74–0.78); the pooled specificity is 0.84 (0.83–0.86).

Figure 5.

Univariable meta-regression and subgroup analyses for the heterogeneity.

Figure 6.

Deek's funnel plot to estimate publication bias.

Figure 7.

Fagan nomogram to evaluate the clinical utility of blood biomarkers for diagnosis of IS.