Clinica chimica acta; international journal of clinical chemistry · 2023
Presepsin in the diagnosis of sepsis.
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Paraskevas Themistoklis, Chourpiliadi Charikleia, Demiri Silvia, Micahilides Christos, Karanikolas Evangelos, Lagadinou Maria, Velissaris Dimitrios
Аннотация
OBJECTIVES: Sepsis is a life-threatening condition characterized by organ dysfunction. It occurs due to the host's dysregulated response to an infection. Clinicians use inflammatory biomarkers to evaluate patients at risk of sepsis in various settings.
METHODS: We included studies focusing on the diagnostic accuracy of presepsin in patients under suspicion of sepsis. The bivariate model of Reitsma was used for the quantitative synthesis, and summary estimates were calculated. The Zhou-Dendukuri approach was followed to assess heterogeneity. Subgroup analyses were performed based on settings and diagnostic criteria.
RESULTS: The summary sensitivity for diagnosing sepsis was 0.805 (95 % CI: 0.759-0.844), while the false positive rate (FPR) was 0.174 (95 % CI: 0.124-0.239). The area under the curve (AUC) for the summary receiver operating characteristic (SROC) curve was 0.875, with a slightly lower partial AUC of 0.833. The analysis using the Zhou-Dendukuri approach revealed low heterogeneity (I2 = 15.9 %). Subgroup analyses showed no significant differences in SROC curves and summary estimates between the ED and ICU settings, although the ED subgroup exhibited higher heterogeneity (I2 = 52.7 % vs. 20.2 %). The comparison between the diagnostic criteria, Sepsis 1 and Sepsis 3, demonstrated similar summary estimates and SROC curves. The examination of the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) tool revealed a high risk of bias regarding the participants and their applicability. Also, there was an increased risk of bias in all the studies concerning the index test.
CONCLUSION: Based on our research, presepsin is a promising biomarker for triage and early diagnosis of sepsis.
METHODS: We included studies focusing on the diagnostic accuracy of presepsin in patients under suspicion of sepsis. The bivariate model of Reitsma was used for the quantitative synthesis, and summary estimates were calculated. The Zhou-Dendukuri approach was followed to assess heterogeneity. Subgroup analyses were performed based on settings and diagnostic criteria.
RESULTS: The summary sensitivity for diagnosing sepsis was 0.805 (95 % CI: 0.759-0.844), while the false positive rate (FPR) was 0.174 (95 % CI: 0.124-0.239). The area under the curve (AUC) for the summary receiver operating characteristic (SROC) curve was 0.875, with a slightly lower partial AUC of 0.833. The analysis using the Zhou-Dendukuri approach revealed low heterogeneity (I2 = 15.9 %). Subgroup analyses showed no significant differences in SROC curves and summary estimates between the ED and ICU settings, although the ED subgroup exhibited higher heterogeneity (I2 = 52.7 % vs. 20.2 %). The comparison between the diagnostic criteria, Sepsis 1 and Sepsis 3, demonstrated similar summary estimates and SROC curves. The examination of the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) tool revealed a high risk of bias regarding the participants and their applicability. Also, there was an increased risk of bias in all the studies concerning the index test.
CONCLUSION: Based on our research, presepsin is a promising biomarker for triage and early diagnosis of sepsis.