Clinical Chemistry Laboratory Research Articles

B-341 Comparative Study of Free Light Chains in the Framework of the Project Prevalence of Monoclonal Gammopathies in Adult Uruguayan Population

Abstract Background Within the framework of a study to evaluate the Prevalence of Monoclonal Gammopathies in the Adult population of Uruguay through detection monoclonal bands by capillary electrophoresis and free light chains in serum, the aim is evaluating the comparison of quantification of FLC (Free Light Chains) in this group of patients with 2 assays: Freelite Biding Site® versus Sebia® FLC Elisa. Methods Study period: September 2021 to November 2022. Prospective, single-cohort, descriptive study. Approved by the Hospital de Clinicas Ethics committee, Montevideo, Uruguay.A total of 3905 patients were included (≥40 years, without previously known plasma cell disorder).Serum samples were collected from three health centers, and processed in Clinical Chemistry Laboratory at Hospital de Clinicas, following an algorithm designed to perform electrophoretic proteinogram (by capillary electrophoresis); suspicious samples with monoclonal bands were confirmed by immunotyping, and in some cases by immunofixation (difficult interpretation), and quantification FLC by 2 different assays (Sebia FLC: manual sandwich ELISA technique- BIO-TEK wash/reader; Freelite The Binding Site immunoturbidimetric assay : Spa Plus and Optilite instruments. Comparative analysis of FLC is a transversal and descriptive study.For statistical analysis: Spearman test, Passing and Bablok and Bland-Altman plot. Results κFLC, λFLC and ratio κ/ λ were measured in 93 of the 104 positive serum samples for Monoclonal Gammopathies (new diagnoses, prevalence 2.7%), using two groups Sebia FLC and Spa Plus Freelite, and Sebia FLC and Optilite Freelite. During the project, the Spa Plus (n=48) FLC was replaced with Optilite (n=45), since the comparative group was not analytically homogeneous, so the comparison was carried out in two groups. Spearman rank correlation coefficients between first group (N:48) for κFLC, λFLC and ratio κ/ λ were r=0.596, 0,549, 0.709, respectively (p<0.0001); for the second group (N:45) Spearman rank correlation coefficients were r=0.778, 0.714, 0.878, respectively (p<0.0001). The first group showed good Spearman rank correlation for ratio, although less better correlation for kappa and lambda isolated. Bland Altman showed high media differences in assays for values for Sebia. For the second group, there was a better Spearman Correlation for ratio and in kappa and lambda isolated too. Bland-Altman plot revealed, in the second group analysis, that Freelite provides higher values than Sebia in Kappa and ratio, but not in Lambda. Passing Bablock showed differences systematic and proportional in different group of comparatives. Conclusions There is a good agreement; despite this, within high FLC concentrations, there are particularly significant differences between both assays, in both groups. We found in same cases FLC quantifications with Freelite ratios lower than those reported by the Elisa Sebia assay, which in these patients could change the diagnosis and therefore the opportunity for treatment or the time between follow-ups. In other cases, greater amount of ratio FLC assayed by Freelite, which may represent loss of linearity in subsequent dilutions. Falsely high results may occur due to polymerization of light chains.Our results suggest that Sebia FLC is a valid assay alternative, but needs more studies to demonstrate these findings; the prospective follow up of this group promises more.

Selection of Single-Analyte Delta Check Rules with Logistic Regression for Detection of Intravenous Fluid Contamination in a Clinical Chemistry Laboratory.

The conventional single-analyte delta check, utilized for identifying intravenous fluid contamination and other preanalytical errors, is known to flag many specimens reflecting true patient status changes. This study aimed to derive delta check rules that more accurately identify contamination. Results for calcium, creatinine, glucose, sodium, and potassium were retrieved from 326 103 basic or comprehensive metabolic panels tested between February 2021 and January 2022. In total, 7934 specimens showed substantial result changes, of which 1489 were labeled as either contaminated or non-contaminated based on chart review. These labeled specimens were used to derive logistic regression models and to select the most predictive single-analyte delta checks for 4 common contaminants. Their collective performance was evaluated using a test data set from October 2023 comprising 14 717 specimens. The most predictive single-analyte delta checks included a calcium change by ≤-24% for both saline and Plasma-Lyte A contamination, a potassium increase by ≥3.0 mmol/L for potassium contamination, and a glucose increase by ≥400 mg/dL (22.2 mmol/L) for dextrose contamination. In the training data sets, multi-analyte logistic regression models performed better than single-analyte delta checks. In the test data set, logistic regression models and single-analyte delta checks demonstrated collective alert rates of 0.58% (95% CI, 0.46%-0.71%) and 0.60% (95% CI, 0.49%-0.74%), respectively, along with collective positive predictive values of 79% (95% CI, 70%-89%) and 77% (95% CI, 68%-87%). Single-analyte delta checks selected by logistic regression demonstrated a low false alert rate.

Evaluation of the implementation of the rational use of laboratory tests in the clinical chemistry laboratory

Abstract Objectives The ‘Rational Laboratory Use Project’ (RLUP) was launched in 2018 by the Department of Examination and Diagnosis Services under the General Directorate of Health Services of the Republic of Turkey’s Ministry of Health. In this study, we aimed to determine the rate of implementation of RLUP in medical biochemistry laboratories, and to contribute to new regulations by collecting the information and opinions of the laboratory experts participating the survey. Methods Thirty questions were uploaded to an online survey tool (SurveyMonkey®, San Mateo, ABD). The first five were descriptive for laboratories. Among the remaining 25 questions, one is open-ended and addresses the various topics encompassed by the project’s scope. Results The questionnaire was completed by 202 medical biochemistry specialists, of whom 82.12 % reported that they did not implement autoverification. 55.65 % defined consultations in Hospital Management Information System (HIMS), but; 70.49 % were not using it actively. 57.69 % of the participants answered, “I agree” to the statement “I think RLUP is feasible”. It was observed that the specialists tried to implement rational laboratory practices partially depending on their laboratory capacity, hospital administration and Laboratory Information Management System (LIMS). Conclusions Increasing clinicians’ awareness could increase the success of this project, which might provide more effective diagnosis and treatment for the patient. In our view, actively involving stakeholders of the information management system, which is not under the direct control of laboratory professionals, in the RLUP will accelerate the development of the project.

Sigma metrics – a good quality control guide to assess analytical performance of a clinical chemistry laboratory

Background: Clinical laboratories function to deliver accurate, reliable, and timely reported results which are used in decision-making, diagnosis, and monitoring. Sigma metrics help to assess analytic methodologies and provide benchmarks for laboratories to design protocols for internal quality control (IQC), address poor assay performance, and assess the efficiency of existing laboratory processes. Thus, this study was undertaken to estimate the coefficient of variation (CV%), bias%, and total allowable error (TEa) of quality control (QC) samples using EM 200, to compare the TEa using Clinical Laboratories Improvement Act (CLIA) guidelines, and to analyze the sigma metrics of level 1 QC samples. Aims and Objectives: The aims and objectives of the study are to estimate the CV%, Bias%, TEa of QC samples using EM 200, to compare the TEa using CLIA guidelines, and to analyze the sigma metrics of level 1 QC samples. Materials and Methods: A cross-sectional study was carried out in the Central Biochemistry Lab, Karwar Institute of Medical Sciences, Karwar. IQC data level 1 of 15 analytes was analyzed using EM200 for 3 months. CV% is calculated from internal quality data, whereas bias% is obtained from an external quality assurance program. Sigma metrics were calculated using bias% and CV%. TEa was calculated and compared with CLIA guidelines. Results: We have < 3 sigma values (unstable, unacceptable) for urea, creatinine, BID, serum glutamic oxaloacetic transaminase, serum glutamate pyruvate transaminase (SGPT), protein, cholesterol, calcium, 3–6 (ideal) for glucose, uric acid, total bilirubin, alkaline phosphatase, albumin, high-density lipoprotein, and >6 (excellent) for triglycerides. TEa observed less than or close to CLIA suggests quality requirement met, and TEa observed more than CLIA (urea, creatinine, BID, SGPT, protein, and calcium) suggests methodologies need evaluation. Conclusion: Sigma metrics help to assess analytical methodologies and augment laboratory performance. Each and every laboratory can use sigma metrics as a guideline for QC strategy and a self-assessment tool for proper functioning.

Immune response to SARS-CoV-2 vaccine administered to patients with solid cancers under systemic treatment: A prospective, monocentric study (Immunocovid-19).

e23093 Background: Despite vaccination, COVID-19 could still cause severe disease in immunocompromised patients (pts). While subsequent vaccine doses increase immune response in the general population, few data concerning cancer pts under systemic treatment are reported. Methods: This study will be conducted on blood samples from 1000 pts admitted to Reggio Emilia AUSL-IRCCS Cancer Center and undergoing systemic therapies who received ≥ 2 vaccine doses. The samples will be analyzed at Clinical Microbiology and Chemistry Laboratories of Reggio Emilia AUSL-IRCCS. We will perform antibody IgM-IgG serology by means of COVID-19 VIRCLIA® Monotest and anti-spike antibodies evaluation using LIAISON® SARS CoV-2 Trimerics IgG. We will also investigate cell immune response (B and T lymphocyte counts) and analyze specific lymphocyte subsets on the first 200 pts treated with chemo- (CT) or immunotherapy (IO). Then, we will evaluate the T-cell response on the first 50 pts and those with an inadequate anti-spike serologic response through the T-SPOT.COVID test. Statistical analyses will be conducted by the Clinical Studies and Statistical Unit Staff. Results: Here, we report preliminary data on the first 240 pts enrolled and treated with CT (55.4%), IO (26.3%), or other therapies (18.3%). Most of the pts were male (58%), had metastatic cancer (82%), and no previous COVID-19 infection (60%). 84% of pts were affected by gastrointestinal, lung, urogenital and breast cancer. We stratified pts in three groups according to the time from the last vaccine dose (0-6/6-12/ > 12 months). We showed no significant decrease in cellular and humoral immune response over time from the last vaccine dose, independent of the specific treatment received, also if CT (Table 1). Furthermore, clinical characteristics as gender, treatment, and primary tumor site appear not to influence immune response, even if a trend to a higher response in pts previously affected by COVID-19 has been observed. The T-SPOT.COVID test performed on the first 27 pts showed that 19% had no T-cell activation, even with good IgG response. Conclusions: This feasible and cost-effective study has a potential impact on public health. Although these are preliminary data, the immune response to COVID-19 vaccines remains good after 12 months from the last dose administered in cancer pts. The enrollment is ongoing, and we could provide relevant information on the influence of clinical factors on the immune response and identify specific subgroups that could benefit from different vaccine approaches. [Table: see text]

Analytical performance evaluation of the Mindray enzymatic assay for hemoglobin A1c measurement

Hemoglobin A1c (HbA1c) plays a crucial role in diabetes management. We aimed to evaluate the analytical performance of a new enzymatic method kit for HbA1c measurement. The performance of the enzymatic method, including precision, accuracy, and linearity, was evaluated. Moreover, the interference effect from conventional interferents, Hb derivatives, Hb variants, and common drugs were assessed. In addition, the agreement of HbA1c results was compared between enzymatic methods, cation-exchange high-performance liquid chromatography (HPLC), and immunoassays. The intra-assay, between-assay, and total precision of HbA1c were all lower than 2%. HbA1c showed good linearity within the range of 3.96–20.23%. The enzymatic assay yielded results consistent with the external quality control samples, with a bias of less than ± 6% from the target values. The enzymatic method showed no interference from bilirubin, intralipid, vitamin C, Hb derivatives, common Hb variants, as well as antipyretic analgesics and hypoglycemic drugs. The HbA1c results of the enzymatic assay showed good agreement and accuracy compared to those obtained from the HPLC method and the immunoassay. The enzymatic method kit performed on the BS-600M chemistry analyzer is a reliable and robust method for measuring HbA1c. It is suitable for routine practice in clinical chemistry laboratories.

The diagnostic accuracy of quality control rules

Internal quality control in clinical chemistry laboratories are based on analyzing samples of stable control materials among the patient samples. The control results are interpreted by using quality control rules that usually are designed to detect systematic errors. The best rules have a high probability of error detection (Ped), i.e. to detect the maximal allowable (critical) systematic error and a low probability of false rejection (Pfr, false alarm). In this work we show that quality control rules can be represented by points on a ROC curve which appears when Ped is plotted against Pfr and only the control limit is varied. Further, we introduce a new method for choosing the optimal control limit, analogous to choosing the optimal operating point on the ROC curve of a diagnostic test. This decision needs knowledge of the pretest probability of a critical systematic error, the benefit of detecting it when it occurs and the cost of false alarm. The ROC curve analysis showed that if rules based on N = 2 are used, mean rules outperform Westgard rules because the ROC curve of the mean rules was lying above the ROC curves of the Westgard rules. A mean rule also had a lower maximum expected increase in the number of unacceptable patient results reported during the presence of an out-of-control error condition (Max E(NUF)) than comparable Westgard rules.

Application of DMAIC methodology to reduce pre-analytical errors in a tertiary hospital clinical chemistry laboratory in India

Application of DMAIC methodology to reduce pre-analytical errors in a tertiary hospital clinical chemistry laboratory in India

Evaluation of newborn screening program for maple syrup urine disease for optimization of amino acid ratio cutoffs: Experience from a single clinical chemistry laboratory

Evaluation of newborn screening program for maple syrup urine disease for optimization of amino acid ratio cutoffs: Experience from a single clinical chemistry laboratory

Quality control in the Netherlands; todays practices and starting points for guidance and future research.

Adequate analytical quality of reported results is primarily ensured by performing internal quality control (iQC). Currently, several different iQC practices are in use. As a prelude to the revision of a Dutch guidance document on analytical QC, a questionnaire was sent out to gain insights in the applied practices and the need for guidance. A questionnaire, containing 20 multiple-choice questions with possibilities for explanation and comment on iQC practices and aspects was distributed to all clinical chemistry laboratories within the Netherlands. Results were reported descriptively. Responses were received from 27 clinical laboratories (response 43 %). In 30 % the iQC was based on the analytical characteristics only, while 30 % used a 6-Sigma method, 19 % risk-based beyond 6-Sigma and 22 % used an alternative approach. 89 % of laboratories used a virtual analyzer model for iQC setup within one or more laboratory sites. Practices for determining standard deviation (SD) values included determining SD for each new iQC material (35 %), using historical SD values for new materials (35 %), and incorporating clinical tolerances into the SD value (31 %). Furthermore, 44 % of laboratories used patient moving averages for one or more tests. Daily iQC management was based on either "traffic lights" indicating in or out of control status, and review of all QC charts, often using multiple software systems. A large heterogeneity of iQC practices in clinical laboratories was observed in the Netherlands. Several starting points for further research and/or guidance were identified, particularly in relation to the determination of SD values, the virtual analyzer model and methods to ensure analyzer equivalence.

Total Laboratory Automation in Clinical Microbiology: A Note on Needs, Challenges, and Applications in a Pandemic Scenario

Recently, an increasing number of publications on automation in diagnostic laboratories, especially in microbiology, has illustrated its potential impact on modern medicine by enhancing the overall quality of culture-based microbiology testing. In the context of clinical microbiology, total laboratory automation (TLA) is now defined as automating the testing workflow, which comprises all phases from sample inoculation to outcome analysis. Hence, there is a need to design or implement proper laboratory automation management processes to enhance workflow, reduce analysis time, and deliver high-quality results without delay in treatment initiation. This review-cum-perspective article highlights the need and current advancements in diagnostic microbiology automation that could revolutionize laboratory operations in healthcare settings. Automation of the workflow is a crucial advancement in the recent history of laboratory diagnostics that unites many diagnostic specializations into a single track to increase the effectiveness, administration, standardization, reliability, and safety of lab tests. While clinical chemistry laboratories adopted and deployed laboratory automation decades earlier, the process of implementing them into routine clinical microbiological practices has several bottlenecks and is still a lengthy process and fraught with technical and regulatory challenges. Moreover, due to outbreaks including the COVID-19 pandemic of recent times, testing volumes are increasing, and automation could probably be a great solution for small and mid-sized laboratories. This article lists the TLA remedies and the specimen-processing tools that are presently available. The need and challenges to implementing automation in microbiological laboratories are discussed with a note on applications in pandemic scenarios.

Validation of the efficacy of pooled serum for serum glucose inhouse quality control material in comparison with commercial internal quality control in clinical chemistry laboratory

BackgroundThis study aimed to create an in-house glucose quality control material for humans, addressing the challenge of obtaining high-cost commercially prepared quality control materials in developing countries. MethodsAn in-house quality control material for glucose was prepared using a pooled serum sample and analyzed using a fully automated chemistry analyzer following the ISO 80 guidelines. The mean, standard deviation (SD), and coefficient of variance were calculated from the first 30 days of measurement, and the variability was checked over eight months using SPSS software. The study used Pearson's correlation with a 95% confidence interval and a P-value less than 0.05, which was statistically significant. ResultsThe average mean ± SD of human serum glucose was 185.2 ± 8.4 mg/dL, indicating that the precision between each measurement was better. The prepared in-house quality control material was stable for approximately five months without any significant change in the serum glucose concentration (mg/dl) (p-value<0.05). ConclusionsThe study suggests that room-temperature, 2–8 °C, and −20 °C to −30 °C storage of human serum samples for glucose analysis is a viable option, with stable glucose concentrations for up to 30 days. Pooled serum is a cost-effective method for in-house quality control, especially in resource-limited laboratories.

Precision matters: Repeatability and reproducibility of total PSA and homocysteine measurements in Alinity i-system.

The precision of test measurements is critical in clinical diagnostics, especially for biomarkers like total PSA and homocysteine, which are essential to disease assessment. Using the CMIA approach, this study investigates the repeatability and reproducibility of these biomarkers on the Abbott Alinity system. The present study was conducted in the clinical chemistry laboratory at Mohammed VI University Hospital of Oujda. The evaluation of the Alinity i-system's analytical performance for total PSA and homocysteine focused on assessing repeatability and intermediate precision. The assessment followed the protocols and guidelines established by the French Accreditation Committee (COFRAC). Our analysis yielded favorable findings regarding the performance of the Alinity assays. The coefficients of variation for both the within-run and between-run precision were less than 5.89% and 4.29%, respectively. These findings produce acceptable outcomes compared to the manufacturer's claims and the SFBC database. Our study underscores the tests' precision, affirming the CMIA method's reliability in measuring total PSA and homocysteine levels. The assessment of the Alinity i-system for total PSA and homocysteine showed significant analytical performance. Our findings have implications for laboratory personnel, researchers, and physicians supporting a continuous diagnostic accuracy improvement culture.

Insights from semi-structured interviews on integrating artificial intelligence in clinical chemistry laboratory practices

BackgroundArtificial intelligence (AI) is gradually transforming the practises of healthcare providers. Over the last two decades, the advent of AI into numerous aspects of pathology has opened transformative possibilities in how we practise laboratory medicine. Objectives of this study were to explore how AI could impact the clinical practices of professionals working in Clinical Chemistry laboratories, while also identifying effective strategies in medical education to facilitate the required changes.MethodsFrom March to August 2022, an exploratory qualitative study was conducted at the Section of Clinical Chemistry, Department of Pathology and Laboratory Medicine, Aga Khan University, Karachi, Pakistan, in collaboration with Keele University, Newcastle, United Kingdom. Semi-structured interviews were conducted to collect information from diverse group of professionals working in Clinical Chemistry laboratories. All interviews were audio recorded and transcribed verbatim. They were asked what changes AI would involve in the laboratory, what resources would be necessary, and how medical education would assist them in adapting to the change. A content analysis was conducted, resulting in the development of codes and themes based on the analyzed data.ResultsThe interviews were analysed to identify three primary themes: perspectives and considerations for AI adoption, educational and curriculum adjustments, and implementation techniques. Although the use of diagnostic algorithms is currently limited in Pakistani Clinical Chemistry laboratories, the application of AI is expanding. All thirteen participants stated their reasons for being hesitant to use AI. Participants stressed the importance of critical aspects for effective AI deployment, the need of a collaborative integrative approach, and the need for constant horizon scanning to keep up with AI developments.ConclusionsThree primary themes related to AI adoption were identified: perspectives and considerations, educational and curriculum adjustments, and implementation techniques. The study’s findings give a sound foundation for making suggestions to clinical laboratories, scientific bodies, and national and international Clinical Chemistry and laboratory medicine organisations on how to manage pathologists’ shifting practises because of AI.

Simple and Cost-Effective Quantum Dot Chemodosimeter for Visual Detection of Biothiols in Human Blood Serum.

An emission "turn-off" chemodosimeter for the naked-eye detection of biothiols using silica-overcoated cadmium selenide quantum dots is developed. Hole scavenging by the thiol group of cysteine, homocysteine, or glutathione on interaction with quantum dots resulted in an instant and permanent emission quenching under physiologically relevant conditions. Also, the emission suppression is so specific that thiols and substituted thiols (methionine and cystine) can easily be distinguished. A pilot experiment for the visual detection of serum thiols in human blood was also conducted. Densitometry analysis proved the potential of this system as a new methodology in clinical chemistry and research laboratories for routine blood and urine analyses using a simple procedure. This method enables one to visually distinguish biothiols and oxidized biothiols, whose ratio plays a crucial role in maintaining "redox thiol status" in the blood.

SIX SIGMA METRICS: INDICATOR OF QUALITY ASSURANCE FOR CLINICAL BIOCHEMSITRY

Introduction: In present scenario Quality is the important aspect of laboratory practices. Mostly internal and external quality control are utilized to maintain quality in laboratory. Quality assurance of laboratory services is the need of present time in health care which require Quality Planning, Quality Control (QC), Quality Assessment (QA) and Quality Improvement . Aims &amp; Objectives: 1. To quantify the defects and errors in analytical phase of laboratory testing by sigma metrics and to represent the calculated sigma value. 2. Application of six sigma test in laboratory with the IQC and EQAS to maintain quality laboratory services. Methodology: Study was conducted at Clinical Biochemistry Laboratory, GMC Akola. We run IQC samples on daily basis and EQAS samples are running on monthly basis. Retrospectively we utilized data of IQC and EQAS from January to October 2023 for 16 Biochemical Analytes. Sigma metrics for each parameter was calculated. Result: The sigma metrics for IQC indicated that 1 out of 16 analytes qualified six sigma quality performance. Of these 15 analytes performance with sigma metrics was beteween three and six. We found different sigma value like more than6 for only HDL cholesterol and more than 3 for Amylase, Total Bilirunbin, Creatinine, Cholesterol, Glucose, Phosphorus, total Protein , SGPT , TG, UA, Urea, SGOT, which is among the acceptable range of performance. Conclusion: In our study sigma value was highest for HDL cholesterol and other 15 analytes show sigma value between 3 to 6 which is acceptable range. Sigma analysis is a continuous procedure and by taking the help of method decision chart we can improve on decision on making in clinical chemistry laboratory regarding optimising QC procedure.

Sigma Metrics Assessment as Quality Improvement Methodology in a Clinical Chemistry Laboratory

Sigma Metrics Assessment as Quality Improvement Methodology in a Clinical Chemistry Laboratory

Biochemical diagnosis of congenital disorders of glycosylation.

Congenital disorders of glycosylation (CDG) are one of the fastest growing groups of inborn errors of metabolism, comprising over 160 described diseases to this day. CDG are characterized by a dysfunctional glycosylation process, with molecular defects localized in the cytosol, the endoplasmic reticulum, or the Golgi apparatus. Depending on the CDG, N-glycosylation, O-glycosylation and/or glycosaminoglycan synthesis can be affected. Various proteins, lipids, and glycosylphosphatidylinositol anchors bear glycan chains, with potential impacts on their folding, targeting, secretion, stability, and thus, functionality. Therefore, glycosylation defects can have diverse and serious clinical consequences. CDG patients often present with a non-specific, multisystemic syndrome including neurological involvement, growth delay, hepatopathy and coagulopathy. As CDG are rare diseases, and typically lack distinctive clinical signs, biochemical and genetic testing bear particularly important and complementary diagnostic roles. Here, after a brief introduction on glycosylation and CDG, we review historical and recent findings on CDG biomarkers and associated analytical techniques, with a particular emphasis on those with relevant use in the specialized clinical chemistry laboratory. We provide the reader with insights and methods which may help them properly assist the clinician in navigating the maze of glycosylation disorders.

THE DIFFERENCES OF HEMATOCRIT LEVEL IN IMMEDIATE AND DELAYED BLOOD SAMPLES ON MICROHEMATOCRIT METHOD

Background: Hematology specimen examination should be performed at room temperature in less than 2 hours. Recommended specimen storage temperatures are in the range of 2°- 6°C. However, examining laboratory samples with uncertain storage time and temperature is often delayed. Aims: To determine the difference between the hematocrit values of blood samples examined immediately and those that were delayed for more than 2 hours at room temperature. Methods: This study was conducted from April to June 2023 at the Clinical Chemistry Laboratory of Universitas Bali Internasional. A total of 24 venous blood samples were grouped into three treatment groups that were stored for 3 hours (P1), 6 hours (P2), and 12 hours (P3) at room temperature (18-220C), and one control group was examined immediately. Data were analyzed using the Mann-Whitney U test (α=0.05). The results: Statistical tests showed that the comparison of control with P1 was not significantly different (p=0.313), while the comparison of control with P2 (p=0.003) and the control with P3 (p=0.000) was significantly different. Conclusions: There was no significant difference in hematocrit values between blood samples examined immediately and blood samples delayed for 3 hours. Significant differences in hematocrit values were shown in comparing blood samples examined immediately with blood samples delayed for 6 hours and examined immediately with blood samples delayed for 12 hours.

STABILITAS PLASMA LIOFILISAT BUATAN SENDIRI SEBAGAI BAHAN KONTROL KUALITAS PADA LABORATORIUM KIMIA KLINIK TERHADAP PEMERIKSAAN TOTAL PROTEIN DAN ALBUMIN

The stability test of the control material is very important because the stability indicates the control material does not change significantly during storage. The use of commercial control is not economically feasible in many countries because of the unavailability or high cost. Therefore, the manufacture of lyophilized human plasma will be great use to several small and private laboratories, including puskesmas laboratories. This study aims to determine the stability of homemade lyophilized plasma as a quality control agent in a clinical chemistry laboratory on total protein and albumin parameters. This type of research is an experimental research with a time series group design. This research was conducted at the campus laboratory and Pramita Laboratory. Samples were taken from 1 respondent in April - May 2022, stored at a temperature of 2-8°C and checked every week for 8 weeks. The results of the examination of total protein levels mean weeks 1 to 8 were 6,42 mg/dL, 6,65 mg/dL, 6,73 mg/dL, 6,50 mg/dL, 6,25 mg/dL, 6,47 mg/dL, 6,28 mg/dL, 6,28 mg/dL. The results of the examination of albumin levels on average 1 to 8 were 3,99 mg/dL, 3,91 mg/dL, 3,63 mg/dL, 3,80 mg/dL, 3,97 mg/dL, 3,43 mg/dL, 3,60 mg/dL, 3,72 mg/dL. The results Leavy Jenning's chart analysis showed plasma lyophilized test results for total protein and albumin levels were still within the limit of ± 2SD. And in regression test the KD value for Total protein 40.32% and the KD value for Albumin 32.54%, showed that the storage time for total protein and albumin had effect on stability of plasma lyophillized. So it can be concluded the examination of total protein and albumin levels stored at a temperature of 2-8°C was stable for 8 weeks