Serum C-reactive protein concentrations in early abdominal and pulmonary sepsis

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

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.

C-reactive protein and procalcitonin use in adults in low- and middle-income countries: a narrative review

Objectives

C-reactive protein (CRP) and procalcitonin (PCT) are widely used biomarkers in high-income countries. However, evidence for their use in low- and middle-income countries (LMICs) is scant. Because many factors, including rates of endemic disease, comorbidities and genetics, may influence biomarkers' behaviour, we aimed to review available evidence generated in LMICs.

Methods

We searched the PubMed database for relevant studies within the last 20 years that originated in regions of interest (Africa, Latin America, Middle East, South Asia or South East Asia), and full-text articles involving diagnosis, prognostication and evaluation of therapeutic response with CRP and/or PCT in adults (n = 88) were reviewed and categorized in 12 predefined focus areas.

Results

Overall, results were highly heterogeneous, at times conflicting, and often lacking clinically useful cut-off values. However, most studies demonstrated higher levels of CRP/PCT in patients with bacterial versus other infections. HIV and TB patients had consistently higher levels of CRP/PCT versus controls. In addition, higher CRP/PCT levels at baseline and follow-up in HIV, TB, sepsis and respiratory tract infections were associated with poorer prognosis.

Conclusions

Evidence generated from LMIC cohorts suggests that CRP and PCT may have potential to become effective clinical guiding tools particularly in respiratory tract infections, sepsis and HIV/TB. However, more studies are needed to define potential scenarios for use and cost-effectiveness. Consensus across stakeholders regarding target conditions, laboratory standards and cut-off values would support the quality and applicability of future evidence.

suPAR in the assessment of post intensive care unit prognosis: a pilot study

OBJECTIVE

To determine the performance of soluble urokinase-type plasminogen activator receptor upon intensive care unit discharge to predict post intensive care unit mortality.

METHODS

A prospective observational cohort study was conducted during a 24-month period in an 8-bed polyvalent intensive care unit. APACHE II, SOFA, C-reactive protein, white cell count and soluble urokinase-type plasminogen activator receptor on the day of intensive care unit discharge were collected from patients who survived intensive care unit admission.

RESULTS

Two hundred and two patients were included in this study, 29 patients (18.6%) of whom died after intensive care unit discharge. Nonsurvivors were older and more seriously ill upon intensive care unit admission with higher severity scores, and nonsurvivors required extended use of vasopressors than did survivors. The area under the receiver operating characteristics curves of SOFA, APACHE II, C-reactive protein, white cell count, and soluble urokinase-type plasminogen activator receptor at intensive care unit discharge as prognostic markers of hospital death were 0.78 (95%CI 0.70 - 0.86); 0.70 (95%CI 0.61 - 0.79); 0.54 (95%CI 0.42 - 0.65); 0.48 (95%CI 0.36 - 0.58); and 0.68 (95%CI 0.58 - 0.78), respectively. SOFA was independently associated with a higher risk of in-hospital mortality (OR 1.673; 95%CI 1.252 - 2.234), 28-day mortality (OR 1.861; 95%CI 1.856 - 2.555) and 90-day mortality (OR 1.584; 95%CI 1.241 - 2.022).

CONCLUSION

At intensive care unit discharge, soluble urokinase-type plasminogen activator receptor is a poor predictor of post intensive care unit prognosis.

Biomarkers for Sepsis: What Is and What Might Be?

Every year numerous individuals develop the morbid condition of sepsis. Therefore, novel biomarkers that might better inform clinicians treating such patients are sorely needed. Difficulty in identifying such markers is in part due to the complex heterogeneity of sepsis, resulting from the broad and vague definition of this state/condition based on numerous possible clinical signs and symptoms as well as an incomplete understanding of the underlying pathobiology of this complex condition. This review considers some of the attempts that have been made so far, looking at both the pro- and anti-inflammatory response to sepsis, as well as genomic analysis, as sources of potential biomarkers. Irrespective, for functional biomarker(s) of sepsis to successfully translate from the laboratory to a clinical setting, the biomarker must be target specific and sensitive as well as easy to implement/interpret, and be cost effective, such that they can be utilized routinely in patient diagnosis and treatment.