The Cold-Inducible RNA-Binding Protein (CIRP) Level in Peripheral Blood Predicts Sepsis Outcome

<div><p>Objectives</p><p>Sepsis is a lethal and complex clinical syndrome caused by infection or suspected infection. Cold-inducible RNA-binding protein (CIRP) is a widely distributed cold-shock protein that plays a proinflammatory role in sepsis and that may induce organ damage. However, clinical studies regarding the use of CIRP for the prognostic evaluation of sepsis are lacking. The purpose of this research was to investigate the prognostic significance of peripheral blood concentrations of CIRP in sepsis. Sepsis was assessed using several common measures, including the Acute Physiology and Chronic Health Evaluation II (APACHE II) score; the Sepsis-related Organ Failure Assessment (SOFA) score; the lactate, serum creatinine, and procalcitonin (PCT) levels; the white blood cell (WBC) count; and the neutrophil ratio (N%).</p><p>Design</p><p>Sixty-nine adult patients with sepsis were enrolled in this study. According to the mortality data from the hospital, 38 patients were survivors, and 31 were nonsurvivors. The plasma levels of the biomarkers were measured and the APACHE II and SOFA scores were calculated within 24 hours of patient enrollment into our study. The CIRP level was measured via ELISA.</p><p>Results</p><p>The plasma level of CIRP was significantly higher in the nonsurvivors than in the survivors (median (IQR) 4.99 (2.37–30.17) ng/mL and 1.68 (1.41–13.90) ng/mL, respectively; <i>p</i> = 0.013). The correlations of the CIRP level with the APACHE II score (r = 0.248, <i>p</i> = 0.040, n = 69), the SOFA score (r = 0.323, <i>p</i> = 0.007, n = 69), the serum creatinine level (r = 0.316, <i>p</i> = 0.008, n = 69), and the PCT level (r = 0.282, <i>p</i> = 0.019, n = 69) were significant. Receiver operator characteristic (ROC) curve analysis showed that the area under the ROC curve (AUC) for the CIRP level was 0.674 (<i>p</i> = 0.013). According to Cox proportional hazards models, the CIRP level independently predicts sepsis mortality. When the CIRP level in the peripheral blood increased by 10 ng/mL, the mortality risk increased by 1.05-fold (<i>p</i> = 0.012). Thus, the CIRP level reflects the degree of renal injury but does not predict the severity of sepsis or organ damage.</p><p>Conclusion</p><p>An elevated plasma concentration of CIRP was significantly associated with poor prognosis among patients with sepsis. Therefore, CIRP is a potential predictor of sepsis prognosis.</p></div

The ROC curves for the biomarkers and the severity scores.

<p>The areas under the ROC curve (AUCs) for the CIRP level, the APACHE II score, the SOFA score, the lactate level, the serum creatinine level, the PCT level, the WBC count, and the N% are shown.</p

Correlations between the CIRP level and the levels of other biomarkers.

<p>The correlations of the plasma CIRP level with the APACHE II score; the SOFA score; the serum lactate, creatinine, and procalcitonin (PCT) levels; the white blood cell (WBC) count; and the neutrophil ratio (N%) were determined in the 69 patients with sepsis (Spearman rank analysis). <i>r</i> represents Spearman’s correlation coefficient, and a <i>p-</i>value < 0.05 was considered to be statistically significant.</p

Areas under the receiver operating characteristic curves for certain biomarker levels and the severity scores in the prediction of sepsis severity and organ failure in patients with sepsis.

<p>*<i>p-</i>value ≦ 0.05</p><p>**<i>p-</i>value ≦ 0.01</p><p>Areas under the receiver operating characteristic curves for certain biomarker levels and the severity scores in the prediction of sepsis severity and organ failure in patients with sepsis.</p

Baseline demographics, clinical characteristics, and comorbidities of 69 patients with sepsis.

<p>APACHE II = Acute Physiology and Chronic Health Evaluation II, SOFA = Sepsis-related Organ Failure Assessment.</p><p>The <i>p</i>-values for age were calculated using the t-test, and those for the APACHE II scores and SOFA score were calculated using the Mann-Whitney <i>U</i> test. Fisher’s exact tests were applied for the categorical variables. A <i>p</i>-value < 0.05 was considered to be statistically significant.</p><p>IQR = inter-quartile range, SD = standard deviation.</p><p>^a<i>p</i> = 0.000433.</p><p>Baseline demographics, clinical characteristics, and comorbidities of 69 patients with sepsis.</p

Mortality prediction based on the plasma levels of the biomarkers and on the severity scores according to ROC curve analysis.

<p>The optimal cutoff values for each plasma biomarker level and the severity scores are presented. A <i>p</i>-value < 0.05 was considered to be statistically significant.</p><p>CIRP = cold-inducible RNA-binding protein, APACHE II = Acute Physiology and Chronic Health Evaluation II, SOFA = Sequential Organ Failure Assessment score, PCT = procalcitonin, WBC = white blood cell, N% = neutrophil ratio.</p><p>ROC = receiver operating characteristic, AUC = area under the ROC curve, CI = confidence interval.</p><p>^b<i>p</i> = 0.000437.</p><p>Mortality prediction based on the plasma levels of the biomarkers and on the severity scores according to ROC curve analysis.</p

Comparison of the plasma biomarker levels between the survivors and nonsurvivors of sepsis.

<p>CIRP = cold-inducible RNA-binding protein, WBC = white blood cell, N% = neutrophil ratio, PCT = procalcitonin.</p><p>The <i>p-</i>values for these biomarkers were obtained using the Mann-Whitney <i>U</i> test. A <i>p</i>-value < 0.05 was considered to be statistically significant.</p><p>IQR = inter-quartile range, SD = standard deviation.</p><p>Comparison of the plasma biomarker levels between the survivors and nonsurvivors of sepsis.</p

Cox proportional hazards models for mortality prediction according to the biomarker levels and the severity scores.

<p>CIRP = cold-inducible RNA-binding protein, APACHE II = Acute Physiology and Chronic Health Evaluation II, SOFA = Sepsis-related Organ Failure Assessment, PCT = procalcitonin, WBC = white blood cell, N% = neutrophil ratio.</p><p>CIRP0.1 = CIRP level/10.</p><p>HR = hazard ratio.</p><p>A <i>p</i>-value < 0.05 was considered to be statistically significant.</p><p>^c = 0.998–1.002</p><p>Cox proportional hazards models for mortality prediction according to the biomarker levels and the severity scores.</p

Table_1_Application of oXiris-continuous hemofiltration adsorption in patients with sepsis and septic shock: A single-centre experience in China.DOCX

oXiris is a new, high-adsorption membrane filter in continuous hemofiltration adsorption to reduce the inflammatory response in sepsis. The investigators retrospectively reviewed patients with sepsis/septic shock who underwent at least one oXiris-treatment from November 2020 to March 2022. The demographic data, baseline levels before treatment, clinical datas, prognosis, and the occurrence of adverse events during treatment were recorded. 90 patients were enrolled in this study. The hemodynamic indices, sequential organ failure assessment score, lactate, inflammatory biomarkers levels were significantly improved at 12 h and 24 h after treatment. Procalcitonin and interleukin-6 reduction post-treatment of oXiris were most pronounced in infection from skin and soft tissue, urinary and abdominal cavity. Logistic regression analysis showed that pre-treatment sequential organ failure assessment score (p = 0.034), percentage decrease in sequential organ failure assessment score (p = 0.004), and age (p = 0.011) were independent risk factors for intensive care unit mortality. In conclusion, oXiris-continuous hemofiltration adsorption may improve hemodynamic indicators, reduce the use of vasoactive drugs, reduce lactate level and infection indicators. Of note, oXiris improve organ function in sepsis, which may result to higher survival rate.</p

Susceptibility analysis of PRRSV receptor transgenic cell lines.

<p>(A) Quantitative RT-PCR (qPCR) analysis of pCD163, pCD169, and sCD151 mRNA expression in transgenic BHK-21 cells: the respective expressions of the target genes were calculated and normalized to GAPDH using the 2^-Δct method. (B) qPCR analysis of pCD163, pCD169, and sCD151 mRNA expression in transgenic BHK-21 cells at the 5^th,15^th, and 25^th passage. Cells were collected and total RNA was extracted, reverse transcribed, and quantitated by qPCR. (C) Immunofluorescence assay (IFA) analysis of PRRSV N protein expression in transgenic BHK-21 cells infected with PRRSV. Transgenic cells were infected with PRRSV CH-1a or JXwn06 (MOI = 1), and expression of the N protein was examined at 36 hpi using the monoclonal antibody SDOW17 and a secondary antibody conjugated to Alexa Fluor 594. Bar = 200 μm. (D) qPCR analysis of viral ORF7 RNA expression in BHK-21 transgenic cells at 12 hpi and 24 hpi. The four transgenic BHK-21 cells were infected with PRRSV CH-1a or JXwn06 (MOI = 0.5) and viral ORF7 in the cells was analyzed by qPCR at 12 hpi and 24 hpi. (E) The supernatant containing PRRSV RNA was analyzed based on absolute quantitative RT-PCR at the indicated time points. Transgenic cells were infected with PRRSV CH-1a or JXwn06 (MOI = 0.5), and the supernatant was collected and used for RNA extraction and absolute qPCR of the virions at 12 hpi and 24 hpi. The data were representative of the results of three independent experiments (mean ± SD). Statistical significances were analyzed using Student’s t-test. *, P<0.05; **, P<0.01; ***, P<0.001; NS, not significant.</p