The accuracy of presepsin (sCD14-ST) for the diagnosis of sepsis in adults: a meta-analysis

Xin Zhang, Dan Liu, You-Ning Liu, Rui Wang, Li-Xin Xie, Xin Zhang, Dan Liu, You-Ning Liu, Rui Wang, Li-Xin Xie

Abstract

Introduction: The early diagnosis of sepsis remains a challenge. Recently, soluble cluster of differentiation 14 subtype (sCD14-ST), also known as presepsin, has been identified as a potential biomarker of sepsis. We performed a meta-analysis to assess the diagnostic accuracy of presepsin for sepsis in patients with systemic inflammation.

Methods: We systematically searched the PubMed, Embase, Web of Knowledge and Cochrane databases. Studies were included if they assessed the diagnostic accuracy of presepsin for sepsis in adult patients with systemic inflammatory response syndrome (SIRS). Furthermore, a 2 × 2 contingency table was constructed based on these results. Two authors independently judged the studies and extracted the data. The diagnostic accuracy of presepsin in sepsis was calculated using a bivariate meta-analysis model. The Q-test and I (2) index were used to test the heterogeneity.

Results: Eight studies involving a total of 1,815 patients were included in the present study. The pooled sensitivity, specificity, diagnostic odds ratio, positive likelihood ratio and negative likelihood ratio were 0.86 (95% CI: 0.79-0.91), 0.78 (95% CI: 0.68-0.85), 22 (95% CI: 10-48), 3.8 (95% CI: 2.6-5.7), and 0.18 (95% CI: 0.11-0.28), respectively. The area under the summary receiver operator characteristic curve was 0.89 (95% CI: 0.86-0.92). Meta-regression analysis revealed that consecutive patient selection, sample size and setting significantly accounted for the heterogeneity of sensitivity.

Conclusions: Our findings suggest that presepsin exhibits very good diagnostic accuracy (AUC=0.89) for the diagnosis for sepsis. Nevertheless, an overall assessment of all the clinical indexes for sepsis diagnosis and continual re-evaluation of presepsin during the course of the disease are needed.

Figures

Fig. 1
Fig. 1
Flow chart of study selection
Fig. 2
Fig. 2
Proportion of Quality Assessment of Diagnostic Accuracy Studies (QUADAS) tool criteria fulfilled by the included studies
Fig. 3
Fig. 3
Deek’s funnel plot asymmetry test for publication bias. No publication bias was detected (p = 0.31)
Fig. 4
Fig. 4
Forrest plot of the sensitivity and specificity of presepsin for the diagnosis of sepsis
Fig. 5
Fig. 5
Positive and negative likelihood ratios. The positive likelihood ratio and negative likelihood ratio were 3.8 (95 % CI: 2.6, 5.7), 0.18 (95 % CI: 0.11, 0.28), respectively LUQ left upper quadrant, RUQ right upper quadrant, LLQ left lower quadrant, RLQ right lower quadrant, LRP likelihood ratio positive, LRN likelihood ratio negative
Fig. 6
Fig. 6
Summary receiver operating characteristic graph of included studies. SEN sensitivity, SPE specificity
Fig. 7
Fig. 7
Fagan’s nomogram for calculation of post-test probabilities. Fagan’s nomogram for presepsin illustrates post-test probability with fixed pre-test probability of 20 % for sepsis. LR likelihood ratio, pos positive, neg negative
Fig. 8
Fig. 8
Univariate meta-regression and subgroup analysis

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