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Erschienen in: Inflammation Research 9/2023

05.09.2023 | Original Research Paper

The value of plasma presepsin as a diagnostic and prognostic biomarker for sepsis in Southern China

verfasst von: Juehui Wu, Xiaoxia Zhan, Songzi Wang, Xuanren Liao, Laisheng Li, Jinmei Luo

Erschienen in: Inflammation Research | Ausgabe 9/2023

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Abstract

Background

Presepsin is a soluble CD14 subtype that has been considered as a novel marker for patients with sepsis. This study explored the clinical value of presepsin for sepsis in Southern China, and further established models for diagnosis and prognosis of sepsis through using machine learning (ML), by combining presepsin and other laboratory parameters.

Methods

269 subjects (105 infected patients, 164 sepsis and septic shock) and 198 healthy controls were enrolled. Laboratory parameters (hematological parameters, coagulation parameters, liver function indices, renal function indices, and inflammatory markers) were collected. Plasma presepsin was tested by chemiluminescence enzyme immunoassay. ML of DxAI™ Research platform was used to establish diagnostic and prognostic models. Sensitivity, specificity, and other performance indicators were used to evaluate the performance of each model.

Results

The level of presepsin was obviously increased in sepsis and sepsis shock, compared with that of infected and healthy group (all P < 0.0001). Presepsin concentration was positively correlated with positive blood culture and 30-day mortality in sepsis and septic shock patients. Through ROC curve analysis, Hb, UREA, APTT, CRP, PCT, and presepsin were incorporated into machine learning to construct diagnosis models. Ada Boost model had the best diagnostic efficiency (AUC: 0.94 (95% CI 0.919–0.968) in the training set and AUC: 0.86 (95% CI 0.813–0.900) in validation set). Furthermore, AST, APTT, UREA, PCT, and presepsin were included in the prognosis ML models, and the Bernoulli NB model had greater predictive ability for 30-day mortality risk of sepsis (AUC: 0.706), which was higher than that of PCT (AUC: 0.617) and presepsin (AUC: 0.634) alone.

Conclusion

Machine-learning model based on presepsin and routinely laboratory parameters showed good performance of diagnostic and prognostic ability for sepsis patients.
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Metadaten
Titel
The value of plasma presepsin as a diagnostic and prognostic biomarker for sepsis in Southern China
verfasst von
Juehui Wu
Xiaoxia Zhan
Songzi Wang
Xuanren Liao
Laisheng Li
Jinmei Luo
Publikationsdatum
05.09.2023
Verlag
Springer International Publishing
Erschienen in
Inflammation Research / Ausgabe 9/2023
Print ISSN: 1023-3830
Elektronische ISSN: 1420-908X
DOI
https://doi.org/10.1007/s00011-023-01787-z

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