Biochemia medicaPub Date : 2024-06-15DOI: 10.11613/BM.2024.020504
Slavica Dodig, Ivana Čepelak
{"title":"Antiphospholipid antibodies in patients with antiphospholipid syndrome.","authors":"Slavica Dodig, Ivana Čepelak","doi":"10.11613/BM.2024.020504","DOIUrl":"10.11613/BM.2024.020504","url":null,"abstract":"<p><p>Antiphospholipid syndrome (APS) is a rare systemic autoimmune disease characterized by recurrent pregnancy morbidity or thrombosis in combination with the persistent presence of antiphospholipid antibodies (aPLs) in plasma/serum. Antiphospholipid antibodies are a heterogeneous, overlapping group of autoantibodies, of which anti-β2-glycoprotein I (aβ2GPI), anticardiolipin (aCL) antibodies and antibodies that prolong plasma clotting time in tests <i>in vitro</i> known as lupus anticoagulant (LAC) are included in the laboratory criteria for the diagnosis of APS. The presence of LAC antibodies in plasma is indirectly determined by measuring the length of coagulation in two tests - activated partial thromboplastin time (aPTT) and diluted Russell's viper venom time (dRVVT). The concentration of aβ2GPI and aCL (immunglobulin G (IgG) and immunoglobulin M (IgM) isotypes) in serum is directly determined by solid-phase immunoassays, either by enzyme-linked immunosorbent assay (ELISA), fluoroimmunoassay (FIA), immunochemiluminescence (CLIA) or multiplex flow immunoassay (MFIA). For patient safety, it is extremely important to control all three phases of laboratory testing, <i>i.e.</i> preanalytical, analytical and postanalytical phase. Specialists in laboratory medicine must be aware of interferences in all three phases of laboratory testing, in order to minimize these interferences. The aim of this review was to show the current pathophysiological aspects of APS, the importance of determining aPLs-a in plasma/serum, with an emphasis on possible interferences that should be taken into account when interpreting laboratory findings.</p>","PeriodicalId":94370,"journal":{"name":"Biochemia medica","volume":"34 2","pages":"020504"},"PeriodicalIF":0.0,"publicationDate":"2024-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11177653/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141332868","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Biochemia medicaPub Date : 2024-06-15DOI: 10.11613/BM.2024.020501
Mustapha Zendjabil
{"title":"Preanalytical, analytical and postanalytical considerations in circulating microRNAs measurement.","authors":"Mustapha Zendjabil","doi":"10.11613/BM.2024.020501","DOIUrl":"10.11613/BM.2024.020501","url":null,"abstract":"<p><p>Microribonucleic acids (miRNAs) have emerged as a new category of biomarkers for many human diseases like cancer, cardiovascular and neurodegenerative disorders. MicroRNAs can be detected in various body fluids including blood, urine and cerebrospinal fluid. However, the literature contains conflicting results for circulating miRNAs, which is the main barrier to using miRNAs as non-invasive biomarkers. This variability in results is largely due to differences between studies in sample processing methodology, miRNA quantification and result normalization. The purpose of this review is to describe the various preanalytical, analytical and postanalytical factors that can impact miRNA detection accuracy and to propose recommendations for the standardization of circulating miRNAs measurement.</p>","PeriodicalId":94370,"journal":{"name":"Biochemia medica","volume":"34 2","pages":"020501"},"PeriodicalIF":0.0,"publicationDate":"2024-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11177657/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141332874","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Biochemia medicaPub Date : 2024-06-15DOI: 10.11613/BM.2024.020803
Vanja Radišić Biljak, Višnja Jureša, Valentina Vidranski, Ivana Vuga, Franciska Tomić, Fran Smaić, Martina Horvat, Branka Krešić, Brankica Šimac, Ivana Lapić
{"title":"The band count imprecision - a Croatian multicentric pilot study.","authors":"Vanja Radišić Biljak, Višnja Jureša, Valentina Vidranski, Ivana Vuga, Franciska Tomić, Fran Smaić, Martina Horvat, Branka Krešić, Brankica Šimac, Ivana Lapić","doi":"10.11613/BM.2024.020803","DOIUrl":"10.11613/BM.2024.020803","url":null,"abstract":"<p><strong>Introduction: </strong>Due to high inter-observer variability the 2015 International Council for Standardization in Haematology (ICSH) recommendations state to count band neutrophils as segmented neutrophils in the white blood cell (WBC) differential. However, the inclusion of bands as a separate cell entity within the WBC differential is still widely used in hematology laboratories in Croatia. The aim of this multicentric study was to assess the degree of inter-observer variability in enumerating band neutrophils within the WBC differential among Croatian laboratories.</p><p><strong>Materials and methods: </strong>Seven large Croatian hospital laboratories from different parts of the country participated in the study. In each of 7 participating laboratories, one blood smear, that was flagged by the analyzer as possibly having bands, was evaluated by all personnel participating in the analysis of hematology samples. Between-observer manual smear reproducibility was expressed as coefficient of variation (CV) and calculated using the following formula: CV (%) = (standard deviation (SD)/mean value) x 100%.</p><p><strong>Results: </strong>The CVs (%) and relative band neutrophil counts in participating laboratories were as follows: 15.4% (16-24), 19.2% (16-32), 19.5% (17-40), 21.1% (17-44), 35.0% (8-26), 51.9% (3-29), and remarkably high 62.4% (12-59). For segmented neutrophils CVs were lower, ranging from 7.4% to 32.2%. The CVs did not correlate with the number of staff members in each hospital (P = 0.293).</p><p><strong>Conclusions: </strong>This study revealed very high variability in enumerating band neutrophil count in the blood smear differential among all participants, thus prompting a need for action on a national level.</p>","PeriodicalId":94370,"journal":{"name":"Biochemia medica","volume":"34 2","pages":"020803"},"PeriodicalIF":0.0,"publicationDate":"2024-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11177652/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141332876","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Biochemia medicaPub Date : 2024-06-15DOI: 10.11613/BM.2024.020708
Borna Rapčan, Maja Hanić, Branimir Plavša, Jelena Šimunović, Jerko Štambuk, Frano Vučković, Irena Trbojević-Akmačić, Mislav Novokmet, Gordan Lauc, Genadij Razdorov
{"title":"Automated high throughput IgG N-glycosylation sample preparation method development on the Tecan Freedom EVO platform.","authors":"Borna Rapčan, Maja Hanić, Branimir Plavša, Jelena Šimunović, Jerko Štambuk, Frano Vučković, Irena Trbojević-Akmačić, Mislav Novokmet, Gordan Lauc, Genadij Razdorov","doi":"10.11613/BM.2024.020708","DOIUrl":"10.11613/BM.2024.020708","url":null,"abstract":"<p><strong>Introduction: </strong>Glycomics, focusing on the role of glycans in biological processes, particularly their influence on the folding, stability and receptor interactions of glycoconjugates like antibodies, is vital for our understanding of biology. Changes in immunoglobulin G (IgG) N-glycosylation have been associated with various physiological and pathophysiological conditions. Nevertheless, time-consuming manual sample preparation is one of the limitations in the glycomics diagnostic implementation. The study aimed to develop an automated method for sample preparation on the Tecan Freedom Evo 200 platform and compare its efficiency and precision with the manual counterpart.</p><p><strong>Materials and methods: </strong>The initial method development included 32 pooled blood plasma technical replicates. An additional 24 pooled samples were used in the method comparison along with 78 random duplicates of plasma samples collected from 10,001 Dalmatians biobank to compare the manual and automated methods.</p><p><strong>Results: </strong>The development resulted in a new automated method. For the automated method, glycan peaks comprising 91% of the total sample glycan showed a variation of less than 5% while 92% of the total sample showed a variation of less than 5% for the manual method. The results of the Passing-Bablok regression indicated no differences between the automated and manual methods for 12 glycan peaks (GPs). However, for 8 GPs systematic difference was present, while both systematic and proportional differences were present for four GPs.</p><p><strong>Conclusions: </strong>The developed automated sample preparation method for IgG glycan analysis reduced exposure to hazardous chemicals and offered a simplified workflow. Despite slight differences between the methods, the new automated method showed high precision and proved to be highly comparable to its manual counterpart.</p>","PeriodicalId":94370,"journal":{"name":"Biochemia medica","volume":"34 2","pages":"020708"},"PeriodicalIF":0.0,"publicationDate":"2024-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11177659/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141332869","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Biochemia medicaPub Date : 2024-06-15DOI: 10.11613/BM.2024.021002
Tomáš Šálek, David Stejskal
{"title":"Pseudonormokalemia case report - What does it mean to have normal blood potassium?","authors":"Tomáš Šálek, David Stejskal","doi":"10.11613/BM.2024.021002","DOIUrl":"10.11613/BM.2024.021002","url":null,"abstract":"<p><p>This case report describes a case of pseudonormokalemia, true hypokalemia. Often, only laboratory values outside the normal range gain attention and false normal results are at risk of not being noticed. However, a disease state may be masked by another pathological process. Here, a 50-year old male was admitted to the Department of Internal Medicine due to sepsis from a dental infection. Initially, serum potassium measurement revealed a normal value of 4 mmol/L (reference interval 3.8-5.1 mmol/L). Thrombocyte number was above 500x10<sup>9</sup>/L. Due to our policy to recommend a repeated measurement of potassium in whole blood or heparin plasma if a patient has thrombocytosis, pseudonormokalemia was identified because the heparin plasma potassium value was only 2.9 mmol/L (reference interval 3.5-4.8 mmol/L). The physiological difference between serum and plasma concentration is no more than 0.3 mmol/L. In this case, potassium concentration were falsely elevated in the serum sample, probably caused by the high number of platelets releasing potassium during clotting. Interpretative comments in patients with thrombocytosis over 500x10<sup>9</sup>/L recommending plasma potassium measurement are helpful. The best way to eliminate pseudohyperkalemia and pseudonormokalemia phenomena caused by thrombocytosis is to completely change towards heparin plasma as the standard material.</p>","PeriodicalId":94370,"journal":{"name":"Biochemia medica","volume":"34 2","pages":"021002"},"PeriodicalIF":0.0,"publicationDate":"2024-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11177651/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141332875","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Biochemia medicaPub Date : 2024-06-15DOI: 10.11613/BM.2024.020707
Xucai Dong, Xi Meng, Bin Li, Dongmei Wen, Xianfei Zeng
{"title":"Comparative study on the quality control effectiveness of AI-PBRTQC and traditional PBRTQC model in identifying quality risks.","authors":"Xucai Dong, Xi Meng, Bin Li, Dongmei Wen, Xianfei Zeng","doi":"10.11613/BM.2024.020707","DOIUrl":"10.11613/BM.2024.020707","url":null,"abstract":"<p><strong>Introduction: </strong>We compared the quality control efficiency of artificial intelligence-patient-based real-time quality control (AI-PBRTQC) and traditional PBRTQC in laboratories to create favorable conditions for the broader application of PBRTQC in clinical laboratories.</p><p><strong>Materials and methods: </strong>In the present study, the data of patients with total thyroxine (TT4), anti-Müllerian hormone (AMH), alanine aminotransferase (ALT), total cholesterol (TC), urea, and albumin (ALB) over five months were categorized into two groups: AI-PBRTQC group and traditional PBRTQC group. The Box-Cox transformation method estimated truncation ranges in the conventional PBRTQC group. In contrast, in the AI-PBRTQC group, the PBRTQC software platform intelligently selected the truncation ranges. We developed various validation models by incorporating different weighting factors, denoted as λ. Error detection, false positive rate, false negative rate, average number of the patient sample until error detection, and area under the curve were employed to evaluate the optimal PBRTQC model in this study. This study provides evidence of the effectiveness of AI-PBRTQC in identifying quality risks by analyzing quality risk cases.</p><p><strong>Results: </strong>The optimal parameter setting scheme for PBRTQC is TT4 (78-186), λ = 0.03; AMH (0.02-2.96), λ = 0.02; ALT (10-25), λ = 0.02; TC (2.84-5.87), λ = 0.02; urea (3.5-6.6), λ = 0.02; ALB (43-52), λ = 0.05.</p><p><strong>Conclusions: </strong>The AI-PBRTQC group was more efficient in identifying quality risks than the conventional PBRTQC. AI-PBRTQC can also effectively identify quality risks in a small number of samples. AI-PBRTQC can be used to determine quality risks in both biochemistry and immunology analytes. AI-PBRTQC identifies quality risks such as reagent calibration, onboard time, and brand changes.</p>","PeriodicalId":94370,"journal":{"name":"Biochemia medica","volume":"34 2","pages":"020707"},"PeriodicalIF":0.0,"publicationDate":"2024-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11177656/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141332870","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Biochemia medicaPub Date : 2024-06-15DOI: 10.11613/BM.2024.020706
Juan José Perales-Afán, Diego Aparicio-Pelaz, Sheila López-Triguero, Elena Llorente, Juan José Puente-Lanzarote, Marta Fabre
{"title":"Direct and indirect reference intervals of 25-hydroxyvitamin D: it is not a real vitamin D deficiency pandemic.","authors":"Juan José Perales-Afán, Diego Aparicio-Pelaz, Sheila López-Triguero, Elena Llorente, Juan José Puente-Lanzarote, Marta Fabre","doi":"10.11613/BM.2024.020706","DOIUrl":"10.11613/BM.2024.020706","url":null,"abstract":"<p><strong>Introduction: </strong>Many studies report vitamin D (25-OH-D) deficiency, although there is no consensus among scientific societies on cut-offs and reference intervals (RI). The aim of this study is to establish and compare RI for serum 25-OH-D by direct and indirect methods.</p><p><strong>Materials and methods: </strong>Two studies were performed in Zaragoza (Spain). A retrospective study (N = 7222) between January 2017 and April 2019 was used for RI calculation by indirect method and a prospective study (N = 312) with healthy volunteers recruited in August 2019 and February 2020 for direct method. Seasonal differences were investigated. Measurements were performed on Cobas C8000 (Roche-Diagnostics, Basel, Switzerland) using electrochemiluminescence immunoassay technology.</p><p><strong>Results: </strong>Reference intervals (2.5-97.5 percentile and corresponding 95% confidence intervals, CIs) were as follows: by indirect method 5.6 ng/mL (5.4 to 5.8) - 57.2 ng/mL (55.2 to 59.8), in winter 5.4 ng/mL (5.2 to 5.7) - 55.7 ng/mL (53.6 to 58.4), while in summer 5.9 ng/mL (5.4 to 6.2) - 59.9 ng/mL (56.3 to 62.9). By direct method 9.0 ng/mL (5.7 to 9.5) - 41.4 ng/mL (37.6 to 48.0), in winter 7.4 ng/mL (3.9 to 8.6) - 34.6 ng/mL (30.6 to 51.5), while in summer 13.3 ng/mL (10.1 to 14.1) - 44.1 ng/mL (38.9 to 66.0). In both methods, RIs were higher in summer. A significant difference was observed in 25-OH-D median values between the two methods (P < 0.001).</p><p><strong>Conclusions: </strong>Reference interval calculation according to the studied area may be a useful tool to adapt the deficiency cut-offs for 25-OH-D. Our data support 25-OH-D values over 12.0 ng/mL for healthy population as sufficient, therefore current recommendations should be updated. In addition, differences in seasonality should be taken into account.</p>","PeriodicalId":94370,"journal":{"name":"Biochemia medica","volume":"34 2","pages":"020706"},"PeriodicalIF":0.0,"publicationDate":"2024-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11177660/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141332871","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Biochemia medicaPub Date : 2024-06-15DOI: 10.11613/BM.2024.020709
Bernardica Valent Morić, Ivan Šamija, Lavinia La Grasta Sabolić, Adriana Unić, Marijana Miler
{"title":"Is the urinary neutrophil gelatinase-associated lipocalin concentration in children and adolescents with type 1 diabetes mellitus different from that in healthy children?","authors":"Bernardica Valent Morić, Ivan Šamija, Lavinia La Grasta Sabolić, Adriana Unić, Marijana Miler","doi":"10.11613/BM.2024.020709","DOIUrl":"10.11613/BM.2024.020709","url":null,"abstract":"<p><strong>Introduction: </strong>Diabetic kidney disease (DKD) is one of the major microvascular complications of type 1 diabetes mellitus (T1DM). Some studies suggest that changes of renal tubular components emerge before the glomerular lesions thus introducing the concept of diabetic tubulopathy with urinary neutrophil gelatinase-associated lipocalin (uNGAL) as a potential marker of DKD. This concept was not confirmed in all studies.</p><p><strong>Materials and methods: </strong>In 198 T1DM patients with median age 15 years and diabetes duration over one year, an albumin/creatinine ratio (ACR) was determined and uNGAL measured in spot urine sample. Urine samples for ACR and uNGAL were also collected in the control group of 100 healthy children of similar age.</p><p><strong>Results: </strong>There was no significant difference in uNGAL concentration or uNGAL/creatinine between T1DM children and healthy subjects (6.9 (2.8-20.1) ng/mL <i>vs</i> 7.9 (2.9-21.0) ng/mL, P = 0.969 and 6.8 (2.2-18.4) ng/mg <i>vs</i> 6.5 (1.9-13.4) ng/mg, P = 0.448, respectively) or between T1DM subjects with albuminuria A2 and albuminuria A1 (P = 0.573 and 0.595, respectively). Among T1DM patients 168 (85%) had normal uNGAL concentrations, while in 30 (15%) patients uNGAL was above the defined cut-off value of 30.9 ng/mL. There was no difference in BMI, HbA1c and diabetes duration between patients with elevated uNGAL compared to those with normal uNGAL.</p><p><strong>Conclusions: </strong>We found no significant difference in uNGAL concentration or uNGAL/creatinine between T1DM children and healthy subjects or between albuminuria A2 and albuminuria A1 T1DM subjects. Therefore, uNGAL should not be recommended as a single marker for detecting diabetic kidney disease in children and adolescents.</p>","PeriodicalId":94370,"journal":{"name":"Biochemia medica","volume":"34 2","pages":"020709"},"PeriodicalIF":0.0,"publicationDate":"2024-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11177655/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141332938","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Biochemia medicaPub Date : 2024-06-15DOI: 10.11613/BM.2024.020502
Katarzyna Maćkowiak, Magdalena Jankowiak, Karolina Szewczyk-Golec, Iga Hołyńska-Iwan
{"title":"Hairy cell leukemia - etiopathogenesis, diagnosis and modern therapeutic approach.","authors":"Katarzyna Maćkowiak, Magdalena Jankowiak, Karolina Szewczyk-Golec, Iga Hołyńska-Iwan","doi":"10.11613/BM.2024.020502","DOIUrl":"10.11613/BM.2024.020502","url":null,"abstract":"<p><p>Hairy cell leukemia (HCL) represents 2% of all leukemia cases, with men aged above 55 years being the most affected. The most common symptoms of this type of leukemia include splenomegaly, monocytopenia, and neutropenia. In the basic blood count examination, leukopenia with monocytopenia and granulocytopenia, as well as aplastic anemia and/or thrombocytopenia occur. The mutation of β-rapidly accelerated fibrosarcoma (<i>BRAF</i>) proto-oncogene, which can be found in nearly 100% of patients, is an important feature of HCL. Immunophenotypic analysis of the HCL cells reveals high expression of B-lineage antigens, including CD19, CD20, and CD22. Additionally, CD11c, CD25, CD103, and CD123 belong to specific markers of HCL. Lactate dehydrogenase activity and β-2-microglobulin concentration are also important in the patient's assessment. The differential diagnosis between HCL, hairy cell leukemia variant (HCL-V) and splenic marginal zone lymphoma (SMZL) is of first importance. Currently, the main treatment for HCL involves the use of purine analogues, excluding pregnant women, individuals with severe infections, and those with relapsing HCL.</p>","PeriodicalId":94370,"journal":{"name":"Biochemia medica","volume":"34 2","pages":"020502"},"PeriodicalIF":0.0,"publicationDate":"2024-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11177658/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141332873","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Effects of reverse osmosis membrane replacement of pure water system on clinical chemistry and immunoassay in clinical laboratory.","authors":"Shaocong Liang, Huaxian Wu, Jiayi Zhao, Xuanjie Guo, Yongjie Qiang, Xin Zhao, Meng Lan, Chongquan Zhao, Dongxin Zhang","doi":"10.11613/BM.2024.010705","DOIUrl":"10.11613/BM.2024.010705","url":null,"abstract":"<p><strong>Introduction: </strong>Reverse osmosis (RO) membrane, key component of water-purifying equipment, is often stored in protection fluid containing substances such as glycerol, which may contaminate the water at replacement. This study aims to explore the effects of RO membrane replacement on clinical chemistry and immunoassay, particularly triglyceride (TG), providing reference for managing test interference caused by RO membrane replacement.</p><p><strong>Materials and methods: </strong>The RO membrane of water-purifying equipment A, which provided water to C16000 biochemistry analyzer (Abbott Laboratories, Abbott Park, USA) and E801 electrochemiluminescence analyzer (Roche, Basel, Switzerland), was replaced. Water resistivity was recorded, and quality control (QC) tests were performed on C16000 and E801. Moreover, TG was measured in 29 of selected serum samples on C16000 at 0.5h and 10.5h after RO membrane replacement and on reference biochemistry analyzer BS2000M (Mindray Biomedical Electronics Co., Shenzhen, China), which was connected to water-purifying equipment B without RO membrane replacement. Finally, blank, calibrator 1 and calibrator 2 of TG reagent were measured on C16000 before and at 0.5h, 2.5h and 10.5h after RO membrane replacement. All statistical analyses of data were done using GraphPad Prism (GraphPad Software Inc., San Diego, USA), and a value of P < 0.05 was considered statistically significant.</p><p><strong>Results: </strong>After RO membrane replacement, all QC results of clinical chemistry and immune tests passed except TG that showed positive bias of 536% and 371% at two levels, respectively. Moreover, TG results of the same serum samples were significantly higher at 0.5h than 10.5h after RO membrane replacement. Meanwhile, there was worse agreement and correlation of TG results between C16000 and BS2000M at 0.5h than 10.5h after replacement. Furthermore, the absorbance of TG blank, calibrator 1 and calibrator 2 was significantly higher at 0.5h and 2.5h after replacement than before replacement, and the absorbance gradually returned to normal value at 10.5h after replacement.</p><p><strong>Conclusions: </strong>Replacement of RO membrane could cause significant interference to TG test while have no effects on other laboratory tests performed in the study, which may be due to glycerol contamination. Our data provides important reference for management of test interference caused by RO membrane replacement. Clinical laboratory should observe the effects of RO membrane replacement on laboratory tests through both water quality monitoring and QC detection.</p>","PeriodicalId":94370,"journal":{"name":"Biochemia medica","volume":"34 1","pages":"010705"},"PeriodicalIF":0.0,"publicationDate":"2024-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10864026/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139743052","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}