Volume 62, Issue 7

Spinal muscular atrophy (SMA) is the leading genetic cause of infant mortality, characterized by progressive neuromuscular degeneration resulting from mutations in the survival motor neuron ( SMN1 ) gene. The availability of disease-modifying therapies for SMA therapies highlights the pressing need for easily accessible and cost-effective blood biomarkers to monitor treatment response and for better disease management. Additionally, the wide implementation of newborn genetic screening programs in Western countries enables presymptomatic diagnosis of SMA and immediate treatment administration. However, the absence of monitoring and prognostic blood biomarkers for neurodegeneration in SMA hinders effective disease management. Neurofilament light protein (NfL) is a promising biomarker of neuroaxonal damage in SMA and reflects disease progression in children with SMA undergoing treatment. Recently, the European Medicines Agency issued a letter of support endorsing the potential utilization of NfL as a biomarker of pediatric neurological diseases, including SMA. Within this review, we comprehensively assess the potential applications of NfL as a monitoring biomarker for disease severity and treatment response in pediatric-onset SMA. We provide reference ranges for normal levels of serum based NfL in neurologically healthy children aged 0–18 years. These reference ranges enable accurate interpretation of NfL levels in children and can accelerate the implementation of NfL into clinical practice.

Ascites is the pathological accumulation of fluid within the peritoneal cavity. It often occurs as results of liver cirrhosis, malignant neoplasia, tuberculous infection, cardiac insufficiency, renal diseases, etc. Determining the etiology is an essential step in the management of patients with new-onset ascites. Abdominal paracentesis with appropriate ascitic fluid analysis is probably the most cost-effective method of determining the cause of ascites. We performed a literature search of PubMed and identified articles published in the field of ascites, to evaluate diagnostic values of various parameters in defining the etiologies of ascites and then provides diagnostic algorithm for patients with new-onset ascites. In patients with ascites, the constituent ratio of underlying etiology varies between developed and developing countries. It is a challenge to define the etiologies of ascites in developing countries. Routine ascitic fluid analysis should include the serum ascites albumin gradient (SAAG), total protein concentration, cell count and differential. Optional ascitic fluid analysis includes cholesterol, fluid culture, cytology, tumor markers, lactate dehydrogenase, adenosine deaminase (ADA), triglyceride, amylase, glucose, brain natriuretic peptide (BNP), etc. Our review evaluated diagnostic values of the above parameters in defining the etiologies of ascites. Diagnostic algorithm established in this review would provide a practical and convenient diagnostic strategy for clinicians in diagnosing patients with new-onset ascites.

Clinical Decision Support Systems (CDSS) have been implemented in almost all healthcare settings. Laboratory medicine (LM), is one of the most important structured health data stores, but efforts are still needed to clarify the use and scope of these tools, especially in the laboratory setting. The aim is to clarify CDSS concept in LM, in the last decade. There is no consensus on the definition of CDSS in LM. A theoretical definition of CDSS in LM should capture the aim of driving significant improvements in LM mission, prevention, diagnosis, monitoring, and disease treatment. We identified the types, workflow and data sources of CDSS. The main applications of CDSS in LM were diagnostic support and clinical management, patient safety, workflow improvements, and cost containment. Laboratory professionals, with their expertise in quality improvement and quality assurance, have a chance to be leaders in CDSS.

Plenty of studies demonstrate that hospital-acquired anemia (HAA) can increase transfusion rates, mortality, morbidity and cause unnecessary patient burden, including additional length of hospital stay, sleep disruption and venipuncture harms resulting from blood samples unlikely to change clinical management. Beyond patient costs, community costs should also be considered, such as laboratory time and resources waste, environmental impact, increasing pressure on labs and fewer tests available on time for patients who can benefit from them most. Blood over-testing does not support the principles of non-maleficence, justice and respect for patient autonomy, at the expense dubious beneficence. Reducing the number and frequency of orders is possible, to a certain extent, by adopting nudge strategies and raising awareness among prescribing doctors. However, reducing the orders may appear unsafe to doctors and patients. Therefore, reducing blood volume from each order is a better alternative, which is worth implementing through technological, purchasing and organizational arrangements, possibly combined according to need (smaller tubes, adequate analytic platforms, blind dilution, blood conservative devices, aggregating tests and laboratory units).

Objectives To describe and validate an isotope dilution-liquid chromatograph-tandem mass spectrometry (ID-LC-MS/MS) based reference measurement procedure (RMP) for zonisamide to accurately measure serum and plasma concentrations. Methods Quantitative nuclear magnetic resonance (qNMR) spectroscopy was employed to determine the absolute content of the reference material used in order to establish traceability to SI units. Separation of zonisamide from known or unknown interferences was performed on a C8 column. For sample preparation a protocol based on protein precipitation in combination with a high dilution step was established. Assay validation and determination of measurement uncertainty were performed based on guidelines from the Clinical and Laboratory Standards Institute, the International Conference on Harmonization, and the Guide to the expression of uncertainty in measurement. Results The RMP was proven to be highly selective and specific with no evidence of a matrix effect, allowing for quantification of zonisamide within the range of 1.50–60.0 μg/mL. Intermediate precision was <1.4 % and repeatability CV ranged from 0.7 to 1.2 % over all concentration levels. The relative mean bias ranged from 0.0 to 0.8 % for native serum levels and from 0.2 to 2.0 % for Li-heparin plasma levels. The measurement uncertainties for single measurements and target value assignment ranged from 1.1 to 1.4 % and 0.8–1.0 %, respectively. Conclusions We present a novel LC-MS/MS-based candidate RMP for zonisamide in human serum and plasma which provides a traceable and reliable platform for the standardization of routine assays and evaluation of clinically relevant samples.

Objectives An isotope dilution liquid chromatography-tandem mass spectrometry (ID-LC-MS/MS)-based candidate reference measurement procedure (RMP) was developed and validated to accurately measure serum and plasma concentrations of carbamazepine. Methods Quantitative nuclear magnetic resonance (qNMR) spectroscopy was used to determine the absolute content of the reference material, ensuring its traceability to SI units. The separation of carbamazepine from potential interferences, whether known or unknown, was achieved using a C18 column. A protein precipitation protocol followed by a high dilution step was established for sample preparation. Assay validation and determination of measurement uncertainty were performed in accordance with the guidelines of the Clinical and Laboratory Standards Institute, the International Conference on Harmonization (ICH), and the Guide to the Expression of Uncertainty in Measurement (GUM). In order to demonstrate equivalence to the already existing RMP a method comparison study was performed. Results The RMP was proven to be highly selective and specific with no evidence of a matrix effect, allowing for quantification of carbamazepine within the range of 0.800–18.0 μg/mL. Intermediate precision and repeatability (n=60 measurements) was found to be <1.6 % and <1.3 % over all concentration levels and independent from the matrix. The relative mean bias ranged from −0.1 to 0.6 % for native serum and from −0.3 to −0.1 % for Li-heparin plasma levels. The measurement uncertainties for single measurements and target value assignment were found to be <1.8 % and <1.3 %, respectively. Method comparison showed a good agreement between the Joint Committee of Traceability in Laboratory Medicine (JCTLM) listed RMP and the candidate RMP resulting in a Passing–Bablok regression equation with a slope of 1.01 and an intercept of −0.01. The bias in the patient cohort was found to be 0.9 %. Conclusions We present a novel LC-MS/MS-based candidate RMP for carbamazepine in human serum and plasma which provides a traceable and reliable platform for the standardization of routine assays and evaluation of clinically relevant samples.

Objectives Phenobarbital serves as an antiepileptic drug (AED) and finds application in the treatment of epilepsy either as monotherapy or adjunctive therapy. This drug exhibits various pharmacodynamic properties that account for its beneficial effects as well as potential side effects. Accurate measurement of its concentration is critical for optimizing AED therapy through appropriate dose adjustments. Therefore, our objective was to develop and validate a new reference measurement procedure (RMP) for the accurate quantification of phenobarbital levels in human serum and plasma. Methods A sample preparation protocol based on protein precipitation followed by a high dilution step was established in combination with a liquid chromatography-tandem mass spectrometry (LC-MS/MS) method using a C8 column to separate target analytes from known and unknown interferences. Assay validation and determination of measurement uncertainty were performed based on current guidelines. Selectivity and Specificity were assessed using spiked serum and plasma samples; to investigate possible matrix effects (MEs) a post-column infusion experiment and a comparison of standard line slopes was performed. Precision and accuracy were determined within a multiday precision experiment. Results The RMP was shown to be highly selective and specific, with no evidence of matrix interferences. It can be used to quantify phenobarbital in the range of 1.92 to 72.0 μg/mL. Intermediate precision was less than 3.2 %, and repeatability coefficient of variation (CV) ranged from 1.3 to 2.0 % across all concentration levels. The relative mean bias ranged from −3.0 to −0.7 % for native serum levels, and from −2.8 to 0.8 % for Li-heparin plasma levels. The measurement uncertainties (k=1) for single measurements and target value assignment were 1.9 to 3.3 % and 0.9 to 1.6 %, respectively. Conclusions A novel LC-MS/MS-based candidate RMP for the quantification of phenobarbital in human serum and plasma is presented which can be used for the standardization of routine assays and the evaluation of clinically relevant samples.

Objectives Primidone is an anticonvulsive drug used in the treatment of epilepsy and essential tremor. It offers beneficial effects in controlling seizures, but its usage is also associated with possible side effects. To ensure optimal therapy, it is crucial to measure its concentration through accurate quantification methods. Therefore, our main goal was to develop and validate a new reference measurement procedure (RMP) for accurately measuring primidone levels in human serum and plasma. Methods In our study, we focused on the separation of primidone from both known and unknown interferences using a C18 column. To achieve accurate sample preparation, we developed a protocol involving protein precipitation followed by a high dilution step. The validation of the assay and determination of measurement uncertainty were carried out following guidelines from organizations such as the Clinical and Laboratory Standards Institute, the International Conference on Harmonization, and the Guide to the Expression of Uncertainty in Measurement. These rigorous validation processes ensure the reliability and accuracy of our method for quantifying primidone levels in human serum and plasma samples. Results The RMP was shown to be highly selective and specific, with no evidence of matrix interference. It can be used to quantify primidone in the range of 0.150–30.0 μg/mL. Intermediate precision was less than 4.0 %, and repeatability CV ranged from 1.0 to 3.3 % across all concentration levels. The relative mean bias ranged from 0.1 to 3.9 % for native serum levels, and from −2.6 to 2.8 % for lithium-heparin plasma levels. The measurement uncertainties for single measurements and target value assignment were 1.5–4.1 % and 0.9–1.0 %, respectively. Conclusions In this study, we introduce an innovative LC-MS/MS-based candidate RMP specifically designed for primidone in human serum and plasma. Our RMP offers a traceable platform, facilitating the standardization of routine assays and enabling the evaluation of clinically relevant samples. With this novel approach, we aim to enhance the accuracy and reliability of primidone measurements, ultimately benefiting the field of clinical research and patient care.

Objectives A reference measurement procedure (RMP) using isotope dilution liquid chromatography-tandem mass spectrometry (ID-LC-MS/MS) was developed and validated with the aim of accurately measuring carbamazepine-10,11-epoxide concentrations in human serum and plasma. Methods To establish traceability to SI units, the absolute content of the reference material was determined using quantitative nuclear magnetic resonance (qNMR) spectroscopy. As sample preparation a protein precipitation protocol followed by a high dilution step was established. Chromatographic separation from carbamazepine and potential metabolites was achieved using a C18 stationary phase. Selectivity, specificity, matrix effects, precision and accuracy, inter-laboratory equivalence, and uncertainty of measurement were evaluated based on guidelines from the Clinical and Laboratory Standards Institute, the International Conference on Harmonization, and the Guide to the Expression of Uncertainty in Measurement. Results The RMP demonstrated very good selectivity and specificity, showing no evidence of a matrix effect. This enabled accurate quantification of carbamazepine-epoxide in the concentration range of 0.0400–12.0 μg/mL. The intermediate precision was found to be less than 2.1 %, and the repeatability coefficient of variation (CV) ranged from 1.2 to 1.8 % across all concentration levels. Regarding accuracy, the relative mean bias varied from 1.4 to 2.5 % for native serum levels and from 1.4 to 3.5 % for Li-heparin plasma levels. The measurement uncertainty for single measurements ranged from 1.6 to 2.1 %. Conclusions In this study, we introduce a new LC-MS/MS-based candidate RMP for accurately measuring carbamazepine-10,11-epoxide in human serum and plasma. This novel method offers a traceable and dependable platform, making it suitable for standardizing routine assays and assessing clinically relevant samples.

Objectives Correct interpretation of thyroid function tests relies on correct reference intervals (RIs) for thyroid-stimulating hormone (TSH) and free thyroxine (FT4). ISO15189 mandates periodic verification of RIs, but laboratories struggle with cost-effective approaches. We investigated whether indirect methods (utilizing historical laboratory data) could replace the direct approach (utilizing healthy reference individuals) and compared results with manufacturer-provided RIs for TSH and FT4. Methods We collected historical data (2008–2022) from 13 Dutch laboratories to re-establish RIs by employing indirect methods, TMC (for TSH) and refineR (for FT4). Laboratories used common automated platforms (Roche, Abbott, Beckman or Siemens). Indirect RIs (IRIs) were determined per laboratory per year and clustered per manufacturer (>1.000.000 data points per manufacturer). Direct RIs (DRIs) were established in 125 healthy individuals per platform. Results TSH IRIs remained robust over the years for all manufacturers. FT4 IRIs proved robust for three manufacturers (Roche, Beckman and Siemens), but the IRI upper reference limit (URL) of Abbott showed a decrease of 2 pmol/L from 2015. Comparison of the IRIs and DRIs for TSH and FT4 showed close agreement using adequate age-stratification. Manufacturer-provided RIs, notably Abbott, Roche and Beckman exhibited inappropriate URLs (overall difference of 0.5–1.0 µIU/mL) for TSH. For FT4, the URLs provided by Roche, Abbott and Siemens were overestimated by 1.5–3.5 pmol/L. Conclusions These results underscore the importance of RI verification as manufacturer-provided RIs are often incorrect and RIs may not be robust. Indirect methods offer cost-effective alternatives for laboratory-specific or platform-specific verification of RIs.

Objectives Data generation in clinical settings is ongoing and perpetually increasing. Artificial intelligence (AI) software may help detect data-related errors or facilitate process management. The aim of the present study was to test the extent to which the frequently encountered pre-analytical, analytical, and postanalytical errors in clinical laboratories, and likely clinical diagnoses can be detected through the use of a chatbot. Methods A total of 20 case scenarios, 20 multiple-choice, and 20 direct questions related to errors observed in pre-analytical, analytical, and postanalytical processes were developed in English. Difficulty assessment was performed for the 60 questions. Responses by 4 chatbots to the questions were scored in a blinded manner by 3 independent laboratory experts for accuracy, usefulness, and completeness. Results According to Chi-squared test, accuracy score of ChatGPT-3.5 (54.4 %) was significantly lower than CopyAI (86.7 %) (p=0.0269) and ChatGPT v4.0. (88.9 %) (p=0.0168), respectively in cases. In direct questions, there was no significant difference between ChatGPT-3.5 (67.8 %) and WriteSonic (69.4 %), ChatGPT v4.0. (78.9 %) and CopyAI (73.9 %) (p=0.914, p=0.433 and p=0.675, respectively) accuracy scores. CopyAI (90.6 %) presented significantly better performance compared to ChatGPT-3.5 (62.2 %) (p=0.036) in multiple choice questions. Conclusions These applications presented considerable performance to find out the cases and reply to questions. In the future, the use of AI applications is likely to increase in clinical settings if trained and validated by technical and medical experts within a structural framework.

Objectives Severe hypo- and hypercalcemia are common and urgent treatment is recommended. Free calcium (fCa) is the gold standard but needs blood gas tests with challenging preanalytics. Total calcium (tCa) and calculated adjusted calcium (aCa) are readily available, but their interpretation is hampered by identical tCa and aCa cutoffs, laborious local aCa calculation and difficult comparability of calcium biomarkers. Methods Laboratory results from University Medicine Leipzig were evaluated over a five-year period (236,274 patients). A local aCa equation was derived by linear least squares regression, the agreement between fCa, tCa and aCa assessed with Cohen’s κ and decision thresholds derived by this indirect method. Results The local aCa equation was created from data of 9,756 patients, each with one paired measurement of tCa, fCa and albumin. Derived aCa cutoffs (1.95/3.15 mmol/L) differ markedly from derived tCa cutoffs (1.6/2.9 mmol/L) and severe hypo- and hypercalcemia can be more accurately assessed by aCa (κ=0.489, 0.812) than by tCa (κ=0.445, 0.744). Comparing our approach to standard care (tCa, literature cutoff), a total 3,250 of 3,680 (88.3 %) misclassified measurements were correctly classified when using aCa with evidence-based cutoffs. Conclusions Optimized cutoffs for aCa and tCa hold great potential for improved patient care. Locally derived aCa equations differ mostly in the chosen mean normal calcium and provide minimal overall improvement, but entail a close examination of the used cutoffs before application.

Objectives Data in literature indicate that in patients suffering a minor head injury (MHI), biomarkers serum levels could be effective to predict the absence of intracranial injury (ICI) on head CT scan. Use of these biomarkers in case of patients taking oral anticoagulants who experience MHI is very limited. We investigated biomarkers as predictors of ICI in anticoagulated patients managed in an ED. Methods We conducted a single-cohort, prospective, observational study in an ED. Our structured clinical pathway included a first head CT scan, 24 h observation and a second CT scan. The outcome was delayed ICI (dICI), defined as ICI on the second CT scan after a first negative CT scan. We assessed the sensitivity (SE), specificity (SP), negative predictive value (NNV) and positive predictive value (PPV) of the biomarkers S100B, NSE, GFAP, UCH-L1 and Alinity TBI in order to identify dICI. Results Our study population was of 234 patients with a negative first CT scan who underwent a second CT scan. The rate of dICI was 4.7 %. The NPV for the detection of dICI were respectively (IC 95 %): S100B 92.7 % (86.0–96.8 %,); ubiquitin C-terminal hydrolase-L1 (UCH-L1) 91.8 % (83.8–96.6 %); glial fibrillary protein (GFP) 100 % (83.2–100 %); TBI 100 % (66.4–100 %). The AUC for the detection of dICI was 0.407 for S100B, 0.563 for neuron-specific enolase (NSE), 0.510 for UCH-L1 and 0.720 for glial fibrillary acidic protein (GFAP), respectively. Conclusions The NPV of the analyzed biomarkers were high and they potentially could limit the number of head CT scan for detecting dICI in anticoagulated patients suffering MHI. GFAP and Alinity TBI seem to be effective to rule out a dCI, but future trials are needed.

Objectives Hemoglobinopathies, including thalassemia and hemoglobin (Hb) variants, are common hematological disorders in tropical countries. Accurate and precise separation of hemoglobin types and reliable quantitation are necessary for differential diagnosis of these disorders. Methods We have evaluated the analytical performances of premier resolution-high-performance liquid chromatography (PR-HPLC; Trinity Biotech, Co. Wicklow, Ireland) to assist in the presumptive diagnosis of thalassemia and Hb variants commonly found in Southeast Asian countries. HbA 0 , HbA 2 , HbE, and HbF levels were separated and quantified in 120 blood samples from unrelated adult subjects and compared with those analyzed by capillary zone electrophoresis (CZE; CAPILLARYS™ 2, Sebia, Norcross, GA, US). The Hb analysis patterns of Hb variants obtained from the PR-HPLC system were also compared to those obtained from HPLC (VARIANT II, β-thalassemia Short Program, Bio-Rad, Laboratories, Hercules, CA, US) and CZE systems. Results The PR-HPLC had excellent precision with a coefficient of variation (CV) for HbA 2 quantitation of 3.8 % within-run and 5.2 % between-run. The levels of HbA 2 /E quantified by the PR-HPLC system correlated well with those of the CZE system ( r =0.997). In addition, thalassemia interpretation results obtained from the PR-HPLC and the CZE showed 100 % agreement. Moreover, chromatograms of the PR-HPLC were also comparable to those of VII-HPLC and CAP2-CZE electropherograms. Conclusions The PR-HPLC system would be applicable to diagnose common forms of thalassemia and Hb variants in Southeast Asia.

Objectives Serum angiotensin-converting enzyme (ACE) is the only biomarker routinely used in the laboratory diagnostics of sarcoidosis, and ACE inhibitor (ACEi) drugs are among the most prescribed drugs worldwide. Taking ACEi can mislead medical teams by lowering ACE activity, delaying diagnosis and giving a false impression of disease activity of sarcoidosis. We aimed to develop a simple method to detect the presence of ACEi drugs in samples, to investigate the ACEi medication-caused interference and consequences in a retrospective study. Methods ACE activity and the level of ACE inhibition were determined for 1823 patients with suspected sarcoidosis. These values were compared with the therapeutic information at the first and follow-up visits. Results A total of 302 patients had biochemical evidence of an ACEi drug effect during diagnostic ACE activity testing. In their case, ACE activity was significantly lower (median(IQR): 4.41 U/L(2.93–6.72)) than in patients not taking ACEi (11.32 U/L(8.79–13.92), p<0.01). In 62 sarcoidosis patients, the ACEi reduced ACE activity to the reference range or below. Only in 40 % of the cases was the medication list recorded in the outpatient chart and only in 3 cases was low ACE activity associated with ACEi use. 67 % of the repeated ACE activity measurements were also performed during ACEi therapy. Conclusions Our study revealed that the use of ACEi is common in patients with suspected sarcoidosis. The ACE activity lowering effect of ACEi drugs may escape the attention of medical teams which can lead to diagnostic errors and unnecessary tests. Nevertheless, these pitfalls can be avoided by using a method suggested by our team.

Objectives Vitamin D and K are believed to promote bone health, but existing evidence is controversial. This study aimed to measure several metabolites of both vitamins by liquid chromatography tandem mass spectrometry (LC-MS/MS) in a cohort of postmenopausal women with low and normal bone mineral density (BMD). Methods Vitamin metabolites (25-hydroxyvitamin D (25[OH]D), 24,25-dihydroxyvitamin D (24,25(OH) 2 D), phylloquinone (K1), menaquinone-4 (MK-4) and MK-7) were measured in 131 serum samples by LC-MS/MS. The vitamin D metabolite ratio (VMR) was calculated. Parathyroid hormone (PTH), type I procollagen-N-terminal-peptide (PINP) and C-terminal telopeptides of type I collagen (CTX-I) were measured by immunoassay. Dual X-ray absorptiometry was performed to identify participants with normal (T-score>−1) and low (T-score<−1) BMD. Results Mean age was 58.2±8.5 years. BMD was normal in 68 and low in 63 women. Median (interquartile range) for 25(OH)D and total vitamin K concentrations were 53.5 (39.6–65.9) nmol/L and 1.33 (0.99–2.39) nmol/L. All vitamin metabolites were comparable in individuals with normal and low BMD. Furthermore, BMD and trabecular bone score were comparable in participants with adequate and inadequate vitamin status (at least one criterion was met: 25(OH)D <50 nmol/L, 24,25(OH) 2 D <3 nmol/L, VMR <4 %, total vitamin K <0.91 nmol/L). PTH, but not PINP or CTX-I, was inversely correlated with 25(OH)D, 24,25(OH) 2 D and VMR. Synergistic effects between vitamin D and K were not observed. Conclusions Vitamin D and K status is not related to BMD and trabecular bone quality in postmenopausal women. Inverse associations were only seen between vitamin D metabolites and PTH.

Objectives Lymphocyte subsets are the predictors of disease diagnosis, treatment, and prognosis. Determination of lymphocyte subsets is usually carried out by flow cytometry. Despite recent advances in flow cytometry analysis, most flow cytometry data can be challenging with manual gating, which is labor-intensive, time-consuming, and error-prone. This study aimed to develop an automated method to identify lymphocyte subsets. Methods We propose a knowledge-driven combined with data-driven method which can gate automatically to achieve subset identification. To improve accuracy and stability, we have implemented a Loop Adjustment Gating to optimize the gating result of the lymphocyte population. Furthermore, we have incorporated an anomaly detection mechanism to issue warnings for samples that might not have been successfully analyzed, ensuring the quality of the results. Results The evaluation showed a 99.2 % correlation between our method results and manual analysis with a dataset of 2,000 individual cases from lymphocyte subset assays. Our proposed method attained 97.7 % accuracy for all cases and 100 % for the high-confidence cases. With our automated method, 99.1 % of manual labor can be saved when reviewing only the low-confidence cases, while the average turnaround time required is only 29 s, reducing by 83.7 %. Conclusions Our proposed method can achieve high accuracy in flow cytometry data from lymphocyte subset assays. Additionally, it can save manual labor and reduce the turnaround time, making it have the potential for application in the laboratory.

Objectives Misidentification errors in tumor marker tests can lead to serious diagnostic and treatment errors. This study aims to develop a method for detecting these errors using a machine learning (ML)-based delta check approach, overcoming limitations of conventional methods. Methods We analyzed five tumor marker test results: alpha-fetoprotein (AFP), cancer antigen 19-9 (CA19-9), cancer antigen 125 (CA125), carcinoembryonic antigen (CEA), and prostate-specific antigen (PSA). A total of 246,261 records were used in the analysis. Of these, 179,929 records were used for model training and 66,332 records for performance evaluation. We developed a misidentification error detection model based on the random forest (RF) and deep neural network (DNN) methods. We performed an in silico simulation with 1 % random sample shuffling. The performance of the developed models was evaluated and compared to conventional delta check methods such as delta percent change (DPC), absolute DPC (absDPC), and reference change values (RCV). Results The DNN model outperformed the RF, DPC, absDPC, and RCV methods in detecting sample misidentification errors. It achieved balanced accuracies of 0.828, 0.842, 0.792, 0.818, and 0.833 for AFP, CA19-9, CA125, CEA, and PSA, respectively. Although the RF method performed better than DPC and absDPC, it showed similar or lower performance compared to RCV. Conclusions Our research results demonstrate that an ML-based delta check method can more effectively detect sample misidentification errors compared to conventional delta check methods. In particular, the DNN model demonstrated superior and stable detection performance compared to the RF, DPC, absDPC, and RCV methods.

Objectives The current study was designed to evaluate the analytical performance of the new Mindray highly sensitive cardiac troponin I (hs-cTnI) chemiluminescent immunoassay on Mindray CL-1200i, as a thorough validation of novel hs-cTnI methods is required before introduction into clinical practice. Methods The evaluation of the analytical performance of this hs-cTnI immunoassay encompassed the calculation of the limit of blank (LOB), limit of detection (LOD), functional sensitivity, imprecision, linearity, 99th percentile upper reference limit (URL) and concordance with another previously validated hs-cTnI chemiluminescent immunoassay. Results The LOB and LOD were 0.32 and 0.35 ng/L, whilst the functional sensitivity (expressed as cTnI value with <10 % imprecision), was 0.35 ng/L. The linearity was excellent throughout a wide range of clinically measurable values (r=1.00 between 0.8 and 9,726.9 ng/mL). The intra-assay, inter-assay and total imprecision were 1.1–1.3 %, 5.5–8.1 % and 5.6–8.2 %, respectively. The 99th percentile URL calculated using residual plasma from 246 ostensibly healthy blood donors was 9.2 ng/L (4.3 ng/L in women vs. 12.3 ng/L in men). The Spearman’s correlation between Mindray hs-cTnI and Access hs-TnI was 0.97, with mean bias of 7.2 % (95 % CI, 2.6–11.9 %). Conclusions Although we failed to confirm the very optimistic analytical characteristics previously reported for this method, our evaluation of the novel Mindray hs-cTnI immunoassay on CL-1200i demonstrated that the overall performance is comparable to that of other commercially available hs-cTnI techniques, making it a viable alternative to other methods.

Objectives This study was undertaken to assess CD91 expression on monocytes and changes in monocyte subset distribution during acute tissue damage and bloodstream infection (BSI). Methods We investigated blood specimens from healthy individuals, trauma and cardiac surgery patients as a model of tissue damage, and patients with BSI, by flow cytometry using a panel of antibodies comprising CD45, HLA-DR, CD14, CD16 and CD91 for the identification of monocyte subsets. Results While infrequent in healthy subjects, CD91low/neg monocyte levels were markedly high in BSI, trauma and after cardiac surgery. This monocyte subset expanded up to 15-fold in both patient cohorts, whereas CD14+CD16+ inflammatory monocytes were multiplied by a factor of 5 only. CD14+CD91low monocytes displayed a significantly lower density of HLA-DR and markedly reduced expression of CD300e, compared to the other subsets. They also expressed high levels of myeloperoxidase and showed robust phagocytic and oxidative burst activity. Conclusions Expansion of CD91low monocytes is a sensitive marker of acute inflammatory states of infectious and non-infectious etiology.