ABSTRACT
Background: The direct method for reference interval (RI) estimating is limited due to the requirement of resources, difficulties in defining a non-diseased population, or ethical problems in obtaining samples. We estimated the RI for inflammatory biomarkers using an indirect method (RII). Methods: C-reactive protein (CRP), erythrocyte sedimentation rate (ESR) and presepsin (PSEP) data of patients visiting a single hospital were retrieved from April 2009 to April 2021. Right-skewed data were transformed using the Box-Cox transformation method. A mixed population of non-diseased and diseased distributions was assumed, followed by latent profile analysis for the two classes. The intersection point of the distribution curve was estimated as the RI. The influence of measurement size was evaluated as the ratio of abnormal values and adjustment (n×bandwidth) of the distribution curve. Results: The RIs estimated by the proposed RII method (existing method) were as follows: CRP, 0-4.1 (0-4.7) mg/L; ESR, 0-10.2 (0-15) mm/hr and PSEP, 0-411 (0-300) pg/mL. Measurement sizes ≥2,500 showed stable results. An abnormal-to-normal value ratio of 0.5 showed the most accurate result for CRP. Adjustment values ≤5 or >5 were applicable for a measurement size <25,000 or ≥25,000, respectively. Conclusions: The proposed RII method could provide additional information for RI verification or estimation with some limitations.
Subject(s)
C-Reactive Protein , Peptide Fragments , Biomarkers , Blood Sedimentation , Humans , Lipopolysaccharide Receptors , Reference ValuesABSTRACT
BACKGROUND: Analytical evaluation of newly developed presepsin by a Sysmex HISCL-5000 (Sysmex, Japan) automated immune analyzer was performed. METHODS: For evaluation, sepsis patient samples were collected before treatment in an emergency department. Precision, linearity, limit of blank/limit of detection, method comparisons, and reference intervals were evaluated. Method comparisons were performed using a PATHFAST immune analyzer (LSI Medience Corporation, Japan). RESULTS: Precision using a 20x2x2 protocol for low (306 pg/mL) and high (1031 pg/mL) levels resulted in within-laboratory standard deviation (95% confidence interval [CI]) and coefficient of variation (CV) %, which were as follows: 15.3 (13.1-18.7), 5.5% and 47.7, (40.5-58.1), 6.4%, respectively. Linearity using patient samples and calibrators were measured from 201 to 16,177 and 188 to 30,000 pg/mL, respectively. The regression equation was y = -23.2 + 1.008x (SE = 162.4) for low levels and y = 779.9 + 1.006x (SE = 668) for high levels. Method comparison by Passing-Bablock analysis was as follows: y = -209.77 + 1.047x (Syx = 335.3). The correlation coefficient (95% CI) was 0.869 (0.772-0.927) with statistical significance (p < 0.001). Reference intervals from 120 normal healthy subjects showed that 300 pg/mL was the cut off. Presepsin tended to show a higher value at higher ages and in males. Presepsin showed correlation with some parameters, and the correlation coefficient (p value) were as follows: hematocrit, 0.198 (0.03); eGFR (CKD-EPI), -0.240 (0.0129); MDRD-eGFR, -0.194 (0.048), respectively. CONCLUSION: Presepsin measurement by HISCL-5000 showed reliable performance. Further clinical studies are required for the diagnosis and prognosis of sepsis.