Sarkar Rajarshi
Drs. Tribedi & Roy Diagnostic Laboratory, Kolkata, India.
EJIFCC. 2024 Aug 8;35(2):120-131. eCollection 2024 Aug.
Though paraproteinaemic interferences is a well-known phenomenon in clinical chemistry, a large-scale evaluation study involving multiple paraproteinaemic specimens on multiple platforms including multiple measurands with an aim to provide a predictive analysis, is singularly lacking. The present study aims to fill this gap in research.
This cross-sectional non-interventional observational study involved thirteen paraproteinaemic subjects, determined their gamma globulin characterization and measured their total bilirubin, direct bilirubin, HDL-cholesterol, calcium, inorganic phosphate, iron and unsaturated iron binding capacity (UIBC) levels on a dry chemistry platform (Vitros 350) as the established method and two wet chemistry platforms (AU5800 and Cobas 6000) as the evaluation methods. Data thus generated was analyzed for any significant variation and tested if such variation increased with decreasing albumin/ globulin ratio.
Significant variation between dry chemistry and wet chemistry measurements were obtained for direct bilirubin, HDL and iron on AU5800 with p-values of 0.0009, <0.0001 and 0.0466 respectively. Similarly, discrepant results were obtained on Cobas 6000 for direct bilirubin and iron, with p-values of <0.0001 and 0.0002 respectively. Additionally, UIBC measurements on AU5800 varied significantly with increasing amounts of paraprotein present in the specimen (p-value = 0.0207).
This study emphasizes on predictive analyses to show that paraprotein interferences are fairly common on wet chemistry platforms. Evolving algorithms for monitoring of reaction curves can minimize release of erroneous results due to such interferences.
尽管副蛋白血症干扰在临床化学中是一个广为人知的现象,但目前缺乏一项大规模评估研究,该研究涉及多个平台上的多个副蛋白血症样本,包括多个被测量物,旨在提供预测分析。本研究旨在填补这一研究空白。
这项横断面非干预性观察研究涉及13名副蛋白血症患者,确定了他们的γ球蛋白特征,并在干式化学平台(Vitros 350)作为既定方法以及两个湿式化学平台(AU5800和Cobas 6000)作为评估方法上测量了他们的总胆红素、直接胆红素、高密度脂蛋白胆固醇、钙、无机磷、铁和不饱和铁结合能力(UIBC)水平。对由此产生的数据进行分析,以确定是否存在显著差异,并测试这种差异是否随着白蛋白/球蛋白比率的降低而增加。
在AU5800上,直接胆红素、高密度脂蛋白和铁的干式化学测量与湿式化学测量之间存在显著差异,p值分别为0.0009、<0.0001和0.0466。同样,在Cobas 6000上,直接胆红素和铁的测量结果也存在差异,p值分别为<0.0001和0.0002。此外,AU5800上的UIBC测量结果随样本中副蛋白含量的增加而有显著变化(p值 = 0.0207)。
本研究强调预测分析,以表明副蛋白干扰在湿式化学平台上相当常见。不断发展的反应曲线监测算法可以最大限度地减少由于此类干扰而产生的错误结果。