Biochemia medica最新文献

Introduction: The ISO 15189:2022 standard considers both the robustness of analytical methods and the risk of erroneous results in the quality control plan (QCP) design. Westgard et al.'s nomogram recommends quality control (QC) rules based on sample run size to ensure that the maximum expected number of unreliable patient results remains below one. This study aimed to implement a standardized, risk-based QC strategy across multiple analyzers without integrated on board QC, ensuring practical quality assurance.

Material and methods: Thirty-two biochemistry parameters on Alinity c systems and three on Cobas Pro systems were included. The analytical performance of each parameter on each analyzer was assessed using sigma metric. Workload requirements were considered to determine the desired run size. Based on the "sigma metric statistical QC run size nomogram" proposed by Westgard et al., a multistage bracketed QCP was designed for each parameter. When multiple designs were available, the simplest QC rule was prioritized.

Results: Seven QCPs were initially established for 35 parameters. In the absence of automation, practical adaptations based on sigma metrics were implemented. Additionally, to streamline management, the QCP covering the greatest number of parameters per analyzer was prioritized, which ultimately resulted in the adoption of only two general QCP. Only 4 individualized QCP were required to cover 10 parameters with lower sigma values.

Conclusions: This approach demonstrates the feasibility of implementing a refined QC strategy for parameters with sigma ≥ 4 in a highly automated laboratory, ensuring consistent quality assurance and efficient resource allocation for higher-risk tests.

Introduction: High-density lipoprotein (HDL) particles are key participants in reverse cholesterol transport. Cholesterol efflux capacity (CEC) and apolipoprotein A1 (Apo A1) are HDL-related biomarkers often used to evaluate HDL particle functionality and quantity. This study aimed to assess the correlation between CEC and Apo A1 concentrations and explore whether methodological aspects influence the correlation results.

Materials and methods: This meta-analysis was prospectively registered in the PROSPERO database (registration number CRD42024552535). Three databases, PubMed, Web of Science, and Cochrane Library, were screened for the studies published between January 2000 and May 2024. The correlation results were analyzed using a random-effects model, and sensitivity and subgroup analyses were performed.

Results: A total of 19 studies with 4967 participants were included. This meta-analysis's results indicated a statistically significant positive moderate strength correlation between CEC and Apo A1 concentrations. A high level of study heterogeneity was observed among the included studies. Further exploration into this heterogeneity revealed that different cell culture lines and cholesterol acceptors used to evaluate CEC impact the overall result of the pooled correlation estimate. The methods used to evaluate Apo A1 did not significantly affect the correlation estimate between CEC and Apo A1 concentrations.

Conclusions: The correlation between CEC and Apo A1 lacks strength and consistency for Apo A1 being used as a surrogate marker for HDL function in a clinical setting. Currently, there is a high need for the standardization of CEC measurement methodologies that impact the overall results and comparability of the studies that have already been conducted.

Spurious elevations in intact parathyroid hormone (iPTH) can lead to unnecessary interventions. We describe a dialysis patient who developed unexpectedly high iPTH concentrations months after total parathyroidectomy with forearm autotransplantation (TPTX-AT). Blood samples had been collected from the grafted forearm, resulting in falsely elevated iPTH values. Once the sample was collected from the non-grafted arm, iPTH concentrations normalized. This case highlights the importance of sampling site awareness in laboratory diagnostics and demonstrates how implementing a simple laboratory information system (LIS)-based protocol can prevent misinterpretation.

Introduction: Traditional internal quality control (IQC) has limitations in detecting systematic errors in clinical laboratories. Patient-Based Real-Time Quality Control (PBRTQC) has emerged as a complementary method, offering new approaches for quality monitoring. Among these, monitoring daily positivity rates provides meaningful insights into laboratory performance.

Materials and methods: This study highlights a case in which PBRTQC was implemented to detect and address a reagent batch issue in thyroid peroxidase antibody (TPO-Ab) testing. Over one year (July 2023 to July 2024), daily positivity rates and their fluctuations were retrospectively analyzed and daily positivity rate alarm limits were established for monitoring.

Results: A notable increase in the TPO-Ab positivity rate was identified starting in June 2024. For outpatients and inpatients, the positivity rates in June and July 2024 were 46.1% ± 7.8% (N = 9039) and 61.4% ± 12.0% (N = 8735), respectively. For the physical examination population, the positivity rates during the same months were 30.0% ± 11.7% (N = 4754) and 52.5% ± 18.1% (N = 5726), respectively. These rates were significantly higher than the pre-June 2024 average monthly positivity rates of 30.0% ± 2.9% (N = 9070 per month) for patients and 11.0% ± 2.4% (N = 4663 per month) for the physical examination population.

Conclusions: PBRTQC, particularly monitoring daily positivity rates, is a valuable tool for early detection of systematic errors. Establishing PBRTQC systems can supplement traditional IQC to improve laboratory test quality.

Introduction: A paradigm shift is occurring in lipid testing, as fasting is no longer required. We aimed to determine whether low-density lipoprotein cholesterol (LDL-C) concentrations calculated using three different equations, along with the components used in these calculations, vary with different fasting durations in routine clinical practice.

Materials and methods: The concentrations of LDL-C were calculated using the Friedewald, Martin-Hopkins, and Sampson/NIH equations, along with the lipid components involved in these equations, depending on time since the last meal in a cohort of 77,300 outpatients at a community hospital. The study population was divided into groups according to fasting durations by 2-hour intervals. A general linear model was applied to identify differences between fasting and nonfasting groups.

Results: Regardless of the calculation method, LDL-C concentrations varied with fasting duration for up to 8-10 hours. The greatest absolute mean differences in LDL-C concentrations between fasting and nonfasting states were - 0.32, - 0.30, and - 0.26 mmol/L when using the Friedewald, Sampson/NIH, and Martin-Hopkins equations, respectively. Among the equation components, triglyceride concentrations were the most sensitive to fasting duration, remaining elevated for 4-6 hours after the last meal, while total cholesterol and non-high-density lipoprotein cholesterol (HDL-C) concentrations decreased for up to 8-10 hours postprandially. However, HDL-C concentrations remained relatively stable.

Conclusions: The variation in postprandial LDL-C concentrations was observed not to differ between the three calculation methods and reached negligible concentrations after at least 8 hours of fasting. If LDL-C concentrations measured in a nonfasting state are near clinical decision thresholds, subsequent lipid measurement should be performed in a fasting state.

Neuroblastomas represent a diverse group of neuroblastic tumors characterized by variability in their clinical progression and degree of differentiation. In rare cases, patients with neuroblastoma may present with paraneoplastic syndromes, such as watery diarrhea, hypokalemia, and achlorhydria (WDHA syndrome), linked to the secretion of vasoactive intestinal peptide (VIP). We report a case of a 14-month-old girl presented with a three-week history of watery diarrhea and signs of dehydration with no other symptoms. The patient's medical history was unremarkable, and no medication use was reported. Venous blood gas analysis revealed a normal anion gap metabolic acidosis with severe hypokalemia. The patient was referred to our hospital 48 hours post-admission due to persistent hypokalemic metabolic acidosis, unresponsive to intravenous fluid therapy. The primary causes of normal anion gap metabolic acidosis in young children are gastrointestinal bicarbonate loss due to diarrhea and renal bicarbonate loss. Semi-quantitative urine organic acid analysis, reported 48 hours after admission, revealed increased vanillylmandelic acid (VMA) (89 mmol/mol creatinine) and homovanillic acid (HVA) (21 mmol/mol creatinine), raising the suspicion of a neuroblastoma. Subsequent analysis of an acidified urine sample confirmed a more than threefold increase in VMA, HVA, normetanephrine, norepinephrine, and 3-methoxytyramine concentrations. In addition, VIP was markedly elevated (1994 ng/L) in a blood sample. The diagnosis of neuroblastoma was confirmed through imaging and histological examination. This case illustrates that chronic diarrhea with metabolic dysregulation (e.g. hypokalemia) can be the first and only symptom in patients with VIP-secreting neuroblastoma which can result in delayed diagnosis of neuroblastoma.

The study of Cristelli et al. attempted to find fault with the rules suggested by Westgard Advisor software, claiming that implementing those rules did not improve the method performance. A fundamental misunderstanding of the utility and purpose of the analytical Sigma-metric and QC rules needs to be clarified.

Introduction: Small cell lung cancer (SCLC) is an aggressive malignant disease with poor survival outcomes. The aim of this study was to investigate leukocyte telomere length (LTL) and redox status parameters during chemotherapy and evaluate their prognostic potential based on the hypothesis that shorter LTL and oxidative stress burden correlate with poorer survival.

Materials and methods: This longitudinal study included 60 SCLC patients and 73 healthy controls. Leukocyte telomere length was measured by quantitative PCR (qPCR) method, while redox status parameters (MDA - malondialdehyde, IMA - ischemia-modified albumin, PON1 - paraoxonase 1, redox index) were determined by spectrophotometric methods before, after two and after four cycles of chemotherapy.

Results: All measured parameters showed significant differences between patients and controls, except the oxy-score (P < 0.001). Significant differences in IMA, PON1 and redox index were observed between SCLC patient groups at different time points (P < 0.001). Significant differences in IMA and PON1 were observed between SCLC survival groups, with higher values found in survivors after two chemotherapy cycles (P < 0.001). Redox index was the highest in the pre-chemo group (P = 0.019). Among patients who died, PON1 activity differed significantly between those who died within 2 months and after 4 months (P = 0.028). Kaplan-Meier analysis showed that LTL and PON1 were significant predictors of survival, with values below the 25th percentile associated with a higher risk of death.

Conclusions: Leukocyte telomere length and PON1 are potential prognostic biomarkers for SCLC survival, suggesting their potential use in non-invasive biomarker panels for improved patient stratification.

Introduction: Accurate measurement of urinary total protein (UTP) is crucial for diagnosing renal and systemic diseases. This study aims to comprehensively evaluate potential carryover scenarios in UTP testing using AU5800 biochemistry analyzer and to identify factors influencing assay accuracy.

Materials and methods: High-concentration quality control materials and pure water was used to evaluate specific sample probe carryover. Additionally, 24-hour mixed urine samples from patients were used to evaluate specific carryover from the reagent probe, mixbars, and cuvettes. For cumulative sample carryover evaluation, pure water was used as reagent and mixed serum as sample for continuous testing. During the process, 24-hour urine samples were interspersed, and UTP concentrations were measured at 0, 10, 20, and 30 minutes. Cumulative reagent carryover was evaluated by testing pure water sequentially with eight reagents sharing the same analytical unit and inner cuvettes as UTP, with UTP concentrations of 24-hour urine samples recorded at 0, 10, 20, and 30 minutes.

Results: Specific carryover from the sample probe, reagent probe, mixbars, and cuvettes was not detected during carryover evaluation of UTP testing. However, a significant cumulative reagent carryover of Immunoglobulin G (IgG) reagent was observed, while no cumulative sample carryover was identified.

Conclusions: The full range of possible carryover scenarios in UTP testing was evaluated using AU5800 biochemistry analyzer. Our data provide valuable references for evaluating carryover in laboratories, ensuring the accuracy and reliability of laboratory results.

Introduction: One of the critical points of the preanalytical phase is the patient's adherence to the required fasting duration before undergoing medical analysis. Although many laboratories have already protocols for blood-sample collection that require only a 6-hour fast, clinical guidelines remain unclear on this aspect, and fasting periods of 12 hours are sometimes still recommended. The aim of this study was to evaluate whether there are significant differences between the results obtained in patients' serum samples obtained post-fasting, 4 hours post-meal, and 6 hours post-meal for different predetermined parameters.

Materials and methods: 30 volunteers (16 females and 14 males) aged between 23 and 62 years were selected for this study. Each participant underwent an initial analysis after a 10-hour fast (baseline), a second analysis 4 hours after a controlled meal, and a third analysis 6 hours after the meal. The parameters studied correspond to previously selected biochemical, hematological, and coagulation tests. To assess if there are significant differences in the results obtained for each analyte, criteria based on the total allowable error (TEa) and the reference change value (RCV) were used.

Results: All parameters evaluated in this study met the criteria based on the RCV at both 4 and 6 hours, although some parameters did not meet TEa criteria.

Conclusions: The results obtained in this study demonstrated that a fasting period of 4 or 6 hours is sufficient to obtain reliable results. This could significantly improve the quality of life for patients undergoing analysis without compromising the quality of their results.