TITLE:
A New Prediction System of Sepsis: A Retrospective, Clinical Study
AUTHORS:
Enhe Liu, Zhinan Zheng, Qiuye Kou
KEYWORDS:
Sepsis, Biomarkers, Prediction System
JOURNAL NAME:
Modern Research in Inflammation,
Vol.5 No.4,
November
4,
2016
ABSTRACT: Objective: Analyzing 6 biomarkers, such as procalcitonin
(PCT), C-reactive protein (CRP), fibrinogen (Fib), lactate concentration (Lac),
D-dimer (D-d), neutrophil ratio (NEUT%) to figure out several sensitive
indicators and establish a new prediction system of sepsis, which could achieve
a higher sensitivity and specificity to predict sepsis. Methods: We collected 113 SIRS patients in ICU. According to
their prognosis, all the patients were divided into two groups named sepsis and
non-sepsis group according to the diagnostic criteria of sepsis. We recorded
the general information and detected the plasma levels of the 6 biomarkers. Results: The plasma levels of NEUT% and Fib between the two
groups had no significant difference. PCT had the highest prediction accuracy of
sepsis compared with other biomarkers. A predictive model was established, in
which Lac, PCT, CRP were enrolled. The final prediction model was: logit(P) = 0.314 + 0.105 × Lac(mmol/l) + 0.099 × PCT(ng/mL) + 0.012 × CRP(mg/L).
The area under the curve of the prediction model was 0.893, which was higher
than every single biomarker involved in this study. Conclusion: The three serum
biomarkers of Lac, PCT, CRP are used to establish a prediction model of sepsis: logit(P) = 0.314 + 0.105 × Lac(mmol/l) + 0.099 × PCT(ng/mL) + 0.012 × CRP(mg/L),
which can better predict the occurrence of sepsis compared with other
biomarkers.