Prediction of Postoperative Sepsis Based on Changes in Presepsin Levels of Critically Ill Patients with Acute Kidney Injury after Abdominal Surgery

Abstract

Presepsin (PSP) is a viable biomarker for the detection of bacterial infection, but it lacks accuracy when acute kidney injury (AKI) develops. Herein, we evaluated the diagnostic and prognostic value of PSP in predicting postoperative sepsis after abdominal surgery respective to the degree of AKI. A total of 311 patients who underwent abdominal surgery and were admitted to a surgical intensive care unit were enrolled and classified into non-AKI, mild-AKI (stage 1, stage 2 and stage 3 without renal replacement therapy (RRT)) and severe-AKI (stage 3 with RRT) group, according to the Kidney Disease Improving Global Outcomes criteria. In each group, PSP and other biomarkers were statistically analyzed between non-sepsis and postoperative sepsis at the admission (T0), 24 h (T1), 48 h (T2) and 72 h (T3) after surgery. In non-AKI and mild-AKI group, PSP levels were significantly higher in postoperative sepsis than non-sepsis group, whereas no difference was detected in the severe-AKI group. Cutoff values of PSP in the mild-AKI group for the prediction of postoperative sepsis were 544 pg/mL (AUC: 0.757, p < 0.001) at T0 and 458.5 pg/mL (AUC: 0.743, p < 0.001) at T1, significantly higher than in non-AKI group. In multivariate analysis, predictors of postoperative sepsis in the mild-AKI group were PSP at T2 (odds ratio (OR): 1.002, p = 0.044) and PSP at T3 (OR: 1.001, p = 0.049). PSP can be useful for predicting newly developed sepsis in patients with transient AKI after abdominal surgery with modified cutoff values.

Indirect Method for Estimation of Reference Intervals of Inflammatory Markers

“…The RI for PSEP estimated with our RII method was 0-411 pg/mL, which is higher than previous results with a mean value ranging from 21.8 to 382 pg/mL [33] or that of the institutional RI. This difference might have been caused by the inclusion of higher values rather than lower values from non-diseased populations, which would have shifted the cut-off value toward the higher side.…”

“…Defining a healthy or non-diseased state was unnecessary in this statistical process. Decomposition of the mixture distribution was performed using LPA, which applies an expectation maximization algorithm [ 25 , 33 ]. LPA assumes unobserved population heterogeneity, which suits the purpose of finding mixed populations using continuous variables.…”

Presepsin Predicts Severity and Secondary Bacterial Infection in COVID-19 by Bioinformatics Analysis

“…Compared with other biomarkers such as PCT, the plasma presepsin concentration increases earlier, which can significantly distinguish sepsis from nonsepsis [ 14 ]. In addition, this early timing feature also endows presepsin the superior diagnostic ability, which can be used for early diagnosis of postoperative sepsis [ 25 ].…”

Presepsin as a Diagnostic and Prognostic Biomarker in Sepsis

“…Patients with higher Presepsin as a Diagnostic and Prognostic Biomarker in Sepsis DOI: http://dx.doi.org/10.5772/intechopen.107955 presepsin levels had a more severe intra-abdominal infection, higher risks of complications, and failure of fistula closure compared with patients with low presepsin admission values group. Current evidence suggests that presepsin could be also a useful predictive marker for newly developing sepsis after abdominal surgery [149]. Prospective study by Bamba et al [150] revealed that presepsin could also be a useful biomarker of sepsis secondary to fungal infections.…”