Prognostic Value of Procalcitonin in Adult Patients with Sepsis: A Systematic Review and Meta-Analysis

<div><p>Procalcitonin (PCT) has been widely investigated for its prognostic value in septic patients. However, studies have produced conflicting results. The purpose of the present meta-analysis is to explore the diagnostic accuracy of a single PCT concentration and PCT non-clearance in predicting all-cause sepsis mortality. We searched PubMed, Embase, Web of Knowledge and the Cochrane Library. Articles written in English were included. A 2 × 2 contingency table was constructed based on all-cause mortality and PCT level or PCT non-clearance in septic patients. Two authors independently evaluated study eligibility and extracted data. The diagnostic value of PCT in predicting prognosis was determined using a bivariate meta-analysis model. We used the Q-test and <i>I</i>² index to test heterogeneity. Twenty-three studies with 3,994 patients were included. An elevated PCT level was associated with a higher risk of death. The pooled relative risk (RR) was 2.60 (95% confidence interval (CI), 2.05–3.30) using a random-effects model (<i>I</i>² = 63.5%). The overall area under the summary receiver operator characteristic (SROC) curve was 0.77 (95% CI, 0.73–0.80), with a sensitivity and specificity of 0.76 (95% CI, 0.67–0.82) and 0.64 (95% CI, 0.52–0.74), respectively. There was significant evidence of heterogeneity for the PCT testing time (<i>P</i> = 0.020). Initial PCT values were of limited prognostic value in patients with sepsis. PCT non-clearance was a prognostic factor of death in patients with sepsis. The pooled RR was 3.05 (95% CI, 2.35–3.95) using a fixed-effects model (<i>I</i>² = 37.9%). The overall area under the SROC curve was 0.79 (95% CI, 0.75–0.83), with a sensitivity and specificity of 0.72 (95% CI, 0.58–0.82) and 0.77 (95% CI, 0.55–0.90), respectively. Elevated PCT concentrations and PCT non-clearance are strongly associated with all-cause mortality in septic patients. Further studies are needed to define the optimal cut-off point and the optimal definition of PCT non-clearance for accurate risk assessment.</p></div

Forest plot of procalcitonin concentration to predict mortality in sepsis.

<p>The overall pooled RR was 2.60 (95% CI, 2.05–3.30).</p

Characteristics of studies associating PCT level with mortality.

<p>PCT = procalcitonin; ICU = intensive care unit; SICU = surgical intensive care unit; MICU = medical intensive care unit; ED = emergency department; HW = hospital ward; PR = prospective recruitment; CR = consecutive recruitment; RR = retrospective recruitment; RCT = random control trial; MPR = multiple-center prospective recruitment; MRCT = multiple-center random control trial; SEN = sensitivity; SPE = specificity; CI = confidence interval.</p><p>Characteristics of studies associating PCT level with mortality.</p

Forest plot of procalcitonin non-clearance to predict mortality in sepsis.

<p>The overall pooled RR was 3.05 (95% CI, 2.35–3.95).</p

Characteristics of studies associating PCT non-clearance with mortality.

<p>PCT = procalcitonin; ICU = intensive care unit; SICU = surgical intensive care unit; ED = emergency department; HW = hospital ward; PR = prospective recruitment; CR = consecutive recruitment; RR = retrospective recruitment; RCT = random control trial; MPR = multiple-center prospective recruitment; MRCT = multiple-center random control trial; SEN = sensitivity; SPE = specificity; CI = confidence interval.</p><p>Characteristics of studies associating PCT non-clearance with mortality.</p

Deek’s funnel plot asymmetry test for publication bias

<p>(A. For single procalcitonin concentration; B. For procalcitonin non-clearance). Potential publication bias exists (P<0.05).</p

Flowchart of study selection.

<p>Flowchart of study selection.</p

Subgroup analysis.

<p>PCT = procalcitonin; ICU = intensive care unit; ED = emergency department; SEN = sensitivity; SPE = specificity; DOR = diagnostic odds ratio; PLR = positive likelihood ratio; NLR = negative likelihood ratio; AUC = area under the curve; CI = confidence interval.</p><p>Subgroup analysis.</p

Identification of Novel Biomarkers for Sepsis Prognosis via Urinary Proteomic Analysis Using iTRAQ Labeling and 2D-LC-MS/MS

<div><h3>Objectives</h3><p>Sepsis is the major cause of death for critically ill patients. Recent progress in proteomics permits a thorough characterization of the mechanisms associated with critical illness. The purpose of this study was to screen potential biomarkers for early prognostic assessment of patients with sepsis.</p> <h3>Methods</h3><p>For the discovery stage, 30 sepsis patients with different prognoses were selected. Urinary proteins were identified using isobaric tags for relative and absolute quantitation (iTRAQ) coupled with LC-MS/MS. Mass spec instrument analysis were performed with Mascot software and the International Protein Index (IPI); bioinformatic analyses were used by the algorithm of set and the Gene Ontology (GO) Database. For the verification stage, the study involved another 54 sepsis-hospitalized patients, with equal numbers of patients in survivor and non-survivor groups based on 28-day survival. Differentially expressed proteins were verified by Western Blot.</p> <h3>Results</h3><p>A total of 232 unique proteins were identified. Proteins that were differentially expressed were further analyzed based on the pathophysiology of sepsis and biomathematics. For sepsis prognosis, five proteins were significantly up-regulated: selenium binding protein-1, heparan sulfate proteoglycan-2, alpha-1-B glycoprotein, haptoglobin, and lipocalin; two proteins were significantly down-regulated: lysosome-associated membrane proteins-1 and dipeptidyl peptidase-4. Based on gene ontology clustering, these proteins were associated with the biological processes of lipid homeostasis, cartilage development, iron ion transport, and certain metabolic processes. Urinary LAMP-1 was down-regulated, consistent with the Western Blot validation.</p> <h3>Conclusion</h3><p>This study provides the proteomic analysis of urine to identify prognostic biomarkers of sepsis. The seven identified proteins provide insight into the mechanism of sepsis. Low urinary LAMP-1 levels may be useful for early prognostic assessment of sepsis.</p> <h3>Trial Registration</h3><p>ClinicalTrial.gov <a href="http://www.clinicaltrials.gov/ct2/show/NCT01493492">NCT01493492</a></p> </div

Dynamic Changes in Amino Acid Concentration Profiles in Patients with Sepsis

<div><p>Objectives</p><p>The goal of this work was to explore the dynamic concentration profiles of 42 amino acids and the significance of these profiles in relation to sepsis, with the aim of providing guidance for clinical therapies.</p><p>Methods</p><p>Thirty-five critically ill patients with sepsis were included. These patients were further divided into sepsis (12 cases) and severe sepsis (23 cases) groups or survivor (20 cases) and non-survivor (15 cases) groups. Serum samples from the patients were collected on days 1, 3, 5, 7, 10, and 14 following intensive care unit (ICU) admission, and the serum concentrations of 42 amino acids were measured.</p><p>Results</p><p>The metabolic spectrum of the amino acids changed dramatically in patients with sepsis. As the disease progressed further or with poor prognosis, the levels of the different amino acids gradually increased, decreased, or fluctuated over time. The concentrations of sulfur-containing amino acids (SAAs), especially taurine, decreased significantly as the severity of sepsis worsened or with poor prognosis of the patient. The serum concentrations of SAAs, especially taurine, exhibited weak negative correlations with the Sequential Organ Failure Assessment (SOFA) (r=-0.319) and Acute Physiology and Chronic Health Evaluation (APACHE) II (r=-0.325) scores. The areas under the receiver operating characteristic curves of cystine, taurine, and SAA levels and the SOFA and APACHE II scores, which denoted disease prognosis, were 0.623, 0.674, 0.678, 0.86, and 0.857, respectively.</p><p>Conclusions</p><p>Critically ill patients with disorders of amino acid metabolism, especially of SAAs such as cystine and taurine, may provide an indicator of the need for the nutritional support of sepsis in the clinic.</p><p>Trial Registration</p><p>ClinicalTrial.gov identifier <a href="https://clinicaltrials.gov/ct2/show/NCT01818830" target="_blank">NCT01818830</a>.</p></div