Revealing the diagnostic value of cerebrospinal fluid presepsin (sCD14) as a new biomarker for postneurosurgical and nosocomial central nervous system infections: A systematic review and meta-analysis of diagnostic test accuracy studies.

BACKGROUND

Central nervous system (CNS) infections represent life-threatening conditions. Emerging evidence suggests cerebrospinal fluid (CSF) presepsin (sCD14) as a promising biomarker for these infections. However, its diagnostic accuracy remains controversial. This study aimed to systematically evaluate the reliability of CSF presepsin in diagnosing CNS infections through a comprehensive meta-analysis.

METHODS

A systematic search of PubMed, Scopus, and Web of Science databases was conducted up to November 2024. Five prospective studies involving 384 participants were included. CSF presepsin levels were compared between infected and non-infected patients. Pooled sensitivity, specificity, diagnostic odds ratio (DOR), positive predictive value (PPV), and negative predictive value (NPV) were calculated using a random-effects model. Publication bias and clinical utility were assessed through Deek's funnel plot and Fagan's nomogram, respectively.

RESULTS

Infected patients exhibited significantly higher CSF presepsin levels (mean difference: 760.16 pg/mL; 95 % confidence interval (CI): 426.26-1094.05, p < 0.01). Pooled sensitivity and specificity were 87 % (95 % CI: 82-91 %) and 67 % (95 % CI: 60-74 %), respectively, with a DOR of 13.04 (95 % CI: 7.51-22.64). The pooled PPV and NPV were 79 % (95 % CI: 73-84 %) and 79 % (95 % CI: 71-85 %), respectively. The area under the curve of the summary receiver operating characteristic curve was 86 %, emphasizing high diagnostic accuracy. No statistically significant publication bias was detected (P = 0.12).

CONCLUSION

CSF presepsin demonstrated potential as a diagnostic biomarker for CNS infections, demonstrating high sensitivity and moderate specificity. Further large-scale studies are needed to refine its clinical applicability and establish standardized thresholds.