Analytical Variables Research Articles

Unraveling Uncertainty: The Impact of Biological and Analytical Variation on the Prediction Uncertainty of Categorical Prediction Models.

Interest in prediction models, including machine learning (ML) models, based on laboratory data has increased tremendously. Uncertainty in laboratory measurements and predictions based on such data are inherently intertwined. This study developed a framework for assessing the impact of biological and analytical variation on the prediction uncertainty of categorical prediction models. Practical application was demonstrated for the prediction of renal function loss (Chronic Kidney Disease Epidemiology Collaboration [CKD-EPI] equation) and 31-day mortality (advanced ML model) in 6360 emergency department patients. Model outcome was calculated in 100 000 simulations of variation in laboratory parameters. Subsequently, the percentage of discordant predictions was calculated with the original prediction as reference. Simulations were repeated assuming increasing levels of analytical variation. For the ML model, area under the receiver operating characteristic curve (AUROC), sensitivity, and specificity were 0.90, 0.44, and 0.96, respectively. At base analytical variation, the median [2.5th-97.5th percentiles] percentage of discordant predictions was 0% [0%-28.8%]. In addition, 7.2% of patients had >5% discordant predictions. At 6× base analytical variation, the median [2.5th-97.5th percentiles] percentage of discordant predictions was 0% [0%-38.8%]. In addition, 11.7% of patients had >5% discordant predictions. However, the impact of analytical variation was limited compared with biological variation. AUROC, sensitivity, and specificity were not affected by variation in laboratory parameters. The impact of biological and analytical variation on the prediction uncertainty of categorical prediction models, including ML models, can be estimated by the occurrence of discordant predictions in a simulation model. Nevertheless, discordant predictions at the individual level do not necessarily affect model performance at the population level.

Mycobacterium avium complex (MAC) infection in severely immunocompromised people living with HIV: Findings from a five-year cohort.

We sought to clarify the current incidence, risk factors and symptoms of disseminated Mycobacterium avium complex (dMAC) infection in admitted people living with HIV in a hospital in the Southeast of Spain. 5-years observational, retrospective and single-centre study. Demographic, clinical and analytical variables, along with microbiological, treatment and follow-up were collected. Five cases of dMAC infection in severely immunocompromised people living with HIV people living were found. dMAC was diagnosed in 22.7% of patients under 100 CD4. All patients presented with fever and clinical manifestations of pneumonia, lymphadenopathy, or gastrointestinal symptoms. Despite low CD4 levels and high viral loads in some cases, primary prophylaxis had not been previously administered. Until 2018, U.S. American guidelines recommended antimycobacterial prophylaxis for patients with low CD4 cell counts, a practice not adopted in Europe. Untreated dMAC infection is associated with high morbidity and mortality rates. dMAC infection represents a prevalent disease in severely immunosuppressed people living with HIV. dMAC requires a high index of suspicion in this population, in order to perform mycobacterial cultures from different samples.

Biological Variation of Hemostasis Analytes in Atrial Fibrillation Patients Using Dabigatran.

Analytical criteria for laboratory analysis based on biological variation are considered state-of-the-art. While biological variance should ideally be measured in patient populations for whom the tests are relevant, data are mostly only available from healthy individuals. We determined the biological variance of activated partial thromboplasmin time (APTT), prothrombin time (PT), fibrinogen, and trough dabigatran levels in patients with atrial fibrillation (AF) who were treated with dabigatran. Between 2019 and 2022, patients with AF treated >3 months with dabigatran were included. Blood was collected monthly up to 10 times for the measurement of APTT, PT, fibrinogen, and trough dabigatran levels. Between-subject variance (CVG), within-subject variance (CVI), and analytical variance (CVA) were calculated. Eighteen participants (median age 65.8 years, 22.2% women) were included, with 130 samples in total. For APTT, the CVG was 11.5%, the CVI 8.8%, and the CVA 1.1%. For PT, these values were 5.2%, 4.0%, and 1.0% and for fibrinogen 13.6%, 11.8%, and 1.6%, respectively. For the dabigatran levels, the percentages were 37.9%, 33.0%, and 3.4%, respectively. We assessed the biological variance of APTT, PT, fibrinogen, and dabigatran in a patient population with long-term dabigatran use. The analytical performances of coagulation laboratory tests in patients with AF treated with dabigatran were comparable to those in healthy volunteers.CCMO Registration Number: NL67304.078.18.

Estimating Reference Change Values Using Routine Patient Data: A Novel Pathology Database Approach.

The reference change value (RCV) is calculated by combining the within-subject biological variation (CVI) and local analytical variation (CVA). These calculations do not account for the variation seen in preanalytical conditions in routine practice or CVI in patients presenting for treatment. As a result, the RCVs may not reflect routine practice or align with clinicians' experiences. We propose a novel RCV approach based on routine patient data that is potentially more clinically relevant. This study used the refineR algorithm to determine RCVs using serial patient data extracted from a local Laboratory Information System (LIS). The model was applied to biomarkers with a range of result ratio distributions varying from normal to log-normal. Results were compared against conventional formula-based RCVs using CVI estimates from a state-of-the-art biological variation study. Monte Carlo simulations were also used to validate the LIS data approach. The RCVs estimated from LIS data were: 11-deoxycortisol (men): -70%/+196%, 17-hydroxyprogesterone (men): -49%/+100%, albumin: -10%/+11%, androstenedione (men): -47%/+96%, cortisol (men): -54%/+51%, cortisone (men): -32%/+51%, creatinine: -16%/+14%, phosphate (women): -23%/+29%, phosphate (men): -27%/+29%, testosterone (men): -38%/+60%. The formula-based RCV estimates showed similar but slightly lower results, and the Monte Carlo simulations confirmed the applicability of the new approach. RCVs may be estimated from patient results without prior assumptions about the shape of the ratios between serial results. Laboratories can determine RCVs based on local practice and population.

Effects of model-overfit on model-assisted forest inventory in boreal forests with remote sensing data

Abstract While remote sensing can be an effective tool in building a forest inventory, field measurements and model fitting can be both expensive and challenging. One strategy to reduce forest inventory costs is to leverage forest inventory models fitted to a different population (external models), although the effectiveness of external models is poorly understood. One concern is that models may predict well to the sample data, but poorly to the population—which is termed ‘overfitting’. The effect of overfit may be especially problematic in attempts to predict for a different population (a forest area not covered by any sample plots). Assessing overfit is difficult and its consequence for estimation are not well understood, especially in the context of prediction using external models. This study assesses how overfitting affects model-assisted forest inventory estimation when using internal and external models. We used field and remotely sensed data (Sentinel-2 images and airborne laser scanning data) from two forest areas in Finland. We evaluated four modeling approaches: ordinary least square regression (OLS), random forest, k-nearest neighbors, and gaussian process regression. Both analytical and bootstrap variance estimators were used to evaluate model-assisted estimation performance. Internal models, especially OLS, were the most affected by model overfitting, leading to bias in the population means and underestimation of variance. Estimates using external models provided unbiased means and realistic intervals except in the case of deliberate excessive overfitting. The bootstrap variance estimator was found to be more robust to overfit than the analytical variance estimator for the internal model, but was not helpful for the external model. Internal models should be parsimonious to generalize well to the population and avoid bias. The bootstrap estimator of variance is recommended for internal models, especially if there is concern about model overfitting.

Review: Current Laboratory and Point-of-Care Pharyngitis Diagnostic Testing and Knowledge Gaps.

Pharyngitis is an inflammatory condition of the pharynx and/or tonsils commonly seen in both children and adults. Viruses and bacteria represent the most common encountered etiologic agents-yeast/fungi and parasites are infrequently implicated. Some of these are predominantly observed in unique populations (eg, immunocompromised or unvaccinated individuals). This manuscript (part 2 of 3) summarizes the current state of laboratory and point-of-care diagnostic testing and highlights the expanding role of nucleic acid amplification in the expedited diagnosis and management of patients with acute pharyngitis. It discusses preanalytical, analytical, and postanalytical variables that impact the performance of culture, rapid antigen, and nucleic acid amplification testing. Finally, it sets the stage for part 3, which discusses the emerging role of biomarkers in the management of individuals with acute pharyngitis.

Assay variables and early clinical evaluation of low-angle light scattering for platelet function analysis.

The recently developed platelet aggregation technique based on low-angle light scattering (LaSca) in diluted platelet-rich plasma (PRP) requires only a small sample volume and provides information about platelet aggregation and shape change. This study aimed to investigate the influence of preanalytical and analytical variables and to validate the method in a real-life pediatric hematology hospital setting. Platelet aggregation was induced by ADP in diluted PRP in the presence of 2mM calcium at 23°C. The study included healthy adults (n = 30), healthy children (n = 20), and pediatric patients with suspected or diagnosed platelet function abnormalities (n = 25). The assay parameters were stable for at least 3h after isolation of PRP and were sensitive to plasma dilution in the range of 2-8%. The initial aggregation velocity was significantly reduced in pediatric patients compared with healthy children (p < 0.05). ADP-induced light transmission amplitude was moderately correlated with LaSca amplitude of aggregation in healthy children (p = 0.52, p < 0.05) but not in pediatric patients. We standardized the protocol for platelet aggregation assessment by LaSca and characterized the influence of preanalytical and analytical variables on it.

Evaluation of inter- and intra-variability in gut health markers in healthy adults using an optimised faecal sampling and processing method.

Despite advances in gut health research, the variability of important gut markers within individuals over time remains underexplored. We investigated the intra-individual variation of various faecal gut health markers using an optimised processing protocol aimed at reducing variability. Faecal samples from ten healthy adults over three consecutive days demonstrated marker-specific intra-individual coefficients of variation (CV%), namely: stool consistency (16.5%), water content (5.7%), pH (3.9%), total SCFAs (17.2%), total BCFAs (27.4%), total bacteria and fungi copies (40.6% and 66.7%), calprotectin and myeloperoxidase (63.8% and 106.5%), and untargeted metabolites (on average 40%). For thirteen microbiota genera, including Bifidobacterium and Akkermansia, variability exceeded 30%, whereas microbiota diversity was less variable (Phylogenetic Diversity 3.3%, Inverse Simpson 17.2%). Mill-homogenisation of frozen faeces significantly reduced the replicates CV% for total SCFAs (20.4-7.5%) and total BCFAs (15.9-7.8%), and untargeted metabolites compared to faecal hammering only, without altering mean concentrations. Our results show the potential need for repeated sampling to accurately represent specific gut health markers. We also demonstrated the effectiveness of optimised preprocessing of human stool samples in reducing overall analytical variability.

Laboratory medicine and sports: where are we now?

Laboratory medicine in sport and exercise has significantly developed during the last decades with the awareness that physical activity contributes to improved health status, and is present in monitoring both professional and recreational athletes. Training and competitions can modify concentrations of a variety of laboratory parameters, so the accurate laboratory data interpretation includes controlled and known preanalytical and analytical variables to prevent misleading interpretations. The paper represents a comprehensive summary of the lectures presented during the 35th Annual Symposium of the Croatian Society of Medical Biochemistry and Laboratory Medicine. It describes management of frequent sport injuries and sums up current knowledge of selected areas in laboratory medicine and sports including biological variation, changes in biochemical parameters and glycemic status. Additionally, the paper polemicizes sex hormone disorders in sports, encourages and comments research in recreational sports and laboratory medicine. In order to give the wider view, the connection of legal training protocols as well as monitoring prohibited substances in training is also considered through the eyes of laboratory medicine.

Cerebrospinal Fluid Total, Phosphorylated and Oligomeric A-Synuclein in Parkinson's Disease: A Systematic Review, Meta-Analysis and Meta-Regression Study.

Background: The diagnostic accuracy for Parkinson's disease (PD), a synucleinopathy, based on diagnostic criteria is suboptimal. A biomarker for synucleinopathies is pivotal both from a clinical and from a research point of view. CSF a-synuclein has been extensively studied over the past two decades as a candidate biomarker of synucleinopathies. Herein, we present data on studies focusing on total, phosphorylated and oligomeric CSF a-synuclein in PD. Methods: Pubmed, Scopus and Web of Science were searched for studies with >10 PD patients and control subjects, with data (mean, SD) on total, phosphorylated or oligomeric a-synuclein. Cohen's d, as a measure of effect size, was calculated for all a-synuclein forms. Subgroup analysis and meta-regression were performed in an effort to explain between-study heterogeneity. Results: Thirty studies on total, six studies on oligomeric and one study on phosphorylated a-synuclein were included. Total a-synuclein was decreased and oligomeric a-synuclein increased in PD patients vs. controls. The effect size was medium for total and high for oligomeric a-synuclein. A-syn forms provided suboptimal combined sensitivity/specificity for the differentiation of PD from controls. There was significant between-study heterogeneity. The PD cohort characteristics (sex, age, disease duration, UPDRS, H & Y) and study characteristics (study design, healthy vs. neurological controls, control for CSF blood contamination, method of a-syn measurement) could not account for between-study heterogeneity. Publication bias was limited. Conclusions: CSF a-synuclein levels lack sufficient accuracy to be used as biomarkers for PD. The standardization of (pre)analytical variables may improve the discriminatory power of a-synuclein forms in the future.

Concordant inter-laboratory derived concentrations of ceramides in human plasma reference materials via authentic standards

In this community effort, we compare measurements between 34 laboratories from 19 countries, utilizing mixtures of labelled authentic synthetic standards, to quantify by mass spectrometry four clinically used ceramide species in the NIST (National Institute of Standards and Technology) human blood plasma Standard Reference Material (SRM) 1950, as well as a set of candidate plasma reference materials (RM 8231). Participants either utilized a provided validated method and/or their method of choice. Mean concentration values, and intra- and inter-laboratory coefficients of variation (CV) were calculated using single-point and multi-point calibrations, respectively. These results are the most precise (intra-laboratory CVs ≤ 4.2%) and concordant (inter-laboratory CVs < 14%) community-derived absolute concentration values reported to date for four clinically used ceramides in the commonly analyzed SRM 1950. We demonstrate that calibration using authentic labelled standards dramatically reduces data variability. Furthermore, we show how the use of shared RM can correct systematic quantitative biases and help in harmonizing lipidomics. Collectively, the results from the present study provide a significant knowledge base for translation of lipidomic technologies to future clinical applications that might require the determination of reference intervals (RIs) in various human populations or might need to estimate reference change values (RCV), when analytical variability is a key factor for recall during multiple testing of individuals.

Mass balance analysis for therapeutic peptides: Case studies, applications, and perspectives

The concept of mass balance is discussed as it pertains to the pharmaceutical development of therapeutic peptides. Case studies are presented demonstrating how to perform a mass balance assessment on solid drug substance and solution drug product, and the role of mass balance in the context of the overall product control strategy is discussed. Utilizing mass balance as a specification test where the result is calculated from other critical quality attribute tests, each with their own specification, offers little value as a formalized quality acceptance criterion and may create more deviations, non-value added investigations, and potential batch failures. While useful in characterizing the performance of analytical methods and as part of a rigorous understanding of the manufacturing process and control strategy development, mass balance should not be required as a specification control and should instead be demonstrated during method development and through well-designed forced degradation experiments. Analytical method variability is discussed in relation to the analytical target profile, and the overall impact of sources of variability on the mass balance calculation is described in support of this position.

B-115 Software Data Processing and Review LC-MS/MS Workflow Improvements for Clinical Research

Abstract Background In the field of quantitative LC-MS/MS, the need for efficient, accurate and user-friendly data review software is paramount, with the data generated in the clinical laboratory meeting local guidelines, as well as rigorous method performance characteristics defined by the FDA Bioanalytical Method Validation and CLSI C62-Ed2 guidelines. The quantitative LC-MS/MS workflow is dependent on interfacing to LMS/LIMS for sample traceability, batch analysis using matrix-matched external calibrators and quality controls for quantification and acceptance, and stable-isotope labeled internal standards to compensate for sample extraction, recovery, matrix effects and analytical variability. The demands on the laboratory to run multiplexed analyte panels and analyze a greater number of samples produces large amounts of analytical data which must still go through batch and quality review before release from the laboratory to the clinicians. The Waters Quan Review Software significantly reduces the burdensome aspects of batch quality control by introducing a series of innovative features. These include improvements in workflow, a modernized interface, and the ability to flag exceptions based on acceptance criteria. Methods Samples for three multiplexed LC-MS/MS panels with previously defined analytical method performance characteristics were acquired using Waters IVD Systems controlled by MassLynx software. The data was processed, quantified, and reviewed using both the existing TargetLynx XS IVD Application Manager and the new Quan Review Software. The three quantitative LC-MS/MS methods were the analysis of four immunosuppressants drugs in whole blood, a twelve steroid panel in plasma and a urine dilute and shoot method for a drugs of abuse panel containing greater than 80 analytes. Each method used matrix matched calibrators and QCs for quantification and batch control with performance characteristics including calibration linearity, carryover, precision and accuracy. Results The analytical performance data generated using the new MS Quan data review software met the same performance criteria as the TargetLynx XS data. For immunosuppressants, the % difference of the mean repeatability and total precision (%CV) for the individual analyte QCs processed using both software was within ±1.3% and ±4.4% respectively. The mean % bias of External Quality Assurance Samples (n=40) for each immunosuppressant processed using both software was within ±7.9%. The modernized, task-oriented accelerated workflows and focused review by exception reduced review time by up to 50%. Conclusions The new Quan Review Software generated results equivalent to the existing TargetLynx XS Application Manager. The software’s enhanced workflow capabilities streamlined the review process in a new user-friendly interface which reduced the training burden enabling scientists to generate high-quality data quickly and easily. The exception focused review functionality allowed tailored rule sets which reduced the time spent reviewing data by up to 50%. Whilst the batch-level review and task-oriented workflow improved batch acceptance and simplified the review of complicated datasets into easy tasks. By integrating these features, Data Review software offers a comprehensive solution that not only improves the efficiency and accuracy of batch quality control but also contributes to the overall reliability and integrity of quantitative LC-MS/MS analysis. For Research Use Only. Not for Use in Diagnostic Procedures.

B-297 Tacrolimus Concentrations in Envarsus vs Prograf Patients: An Evaluation of the Clinical Impact of LC-MS/MS and Immunoassay Methods on Tacrolimus measurement

Abstract Background Tacrolimus is a calcineurin inhibitor used as part of an immunosuppressive regimen in kidney and liver transplant patients to prevent graft-versus-host disease (GvHD) and requires therapeutic drug monitoring due to its narrow therapeutic index. Tacrolimus levels are commonly measured using two different methodologies - immunoassay and liquid chromatography tandem mass spectrometry (LC-MS/MS). A global proficiency study to assess and compare the measurement of trough levels by these two methodologies noted a positive bias with the ARCHITECT immunoassay which is likely due to the presence of tacrolimus metabolites. The aim of our study is to assess the impact of two different formulations of tacrolimus on the accuracy of its analytical measurement. While differences between immunoassay and LC-MS/MS results have been evaluated for immediate-release tacrolimus (Prograf), it has yet to be characterized for extended-release formulations such as Envarsus. The discrepancy between immunoassay and LC-MS/MS has clinical implications, as dosage modifications are based on measured concentrations, analytical variation may cause intervals of subtherapeutic or supratherapeutic exposure, increasing the risk of graft rejection or toxicity. Methods Development of an LC-MS/MS method for the simultaneous quantification of tacrolimus and its major metabolite, desmethyl tacrolimus, was performed in whole blood. Traceable calibrators and quality control material for tacrolimus and specimens supplemented with desmethyl tacrolimus were used to determine accuracy and precision. Tacrolimus concentrations were measured by LC-MS/MS and ARCHITECT immunoassay methods in excess whole blood specimens from patients treated with either Prograf or Envarsus. Measurement biases between LC-MS/MS and immunoassay methodologies were determined for both formulations of tacrolimus. Results External calibration curves for both tacrolimus and desmethyl tacrolimus were linear (R2&amp;gt;0.995), and the analytical measurement range (AMR) for tacrolimus spanned from 1.1 - 31.6 ng/ml. Calibrator and Quality control (QC) biases were within 15% of their target values throughout the AMR and within-run imprecision was less than 10% (n=25) for all calibrators and QCs. Between-run imprecision for Low, Mid, and High QC levels over a period of 2 weeks (n=5 days) was less than 10%. Comparative bias of tacrolimus concentrations between immunoassay and LC-MS/MS was significantly lower (P value=0.0074) for Envarsus (n=20 specimens) relative to Prograf (n=32 specimens). Conclusions The differential bias between immunoassay and LC-MS/MS in the measurement of tacrolimus in patients dosed with immediate-release versus extended-release formulations suggests that their distinct pharmacokinetic profile may impact the accuracy of the measurement. Therefore, applying observed measurement biases from different assays derived from Prograf patients to Envarsus patients and vice versa may result in erroneous estimation of tacrolimus concentrations.

A-193 Optimizing Emergency Laboratory Operations Through Six-Sigma Strategies for Enhanced Efficiency and Effectiveness: A Pilot Study

Abstract Background Quality assurance is vital in laboratory diagnostics to ensure patient safety and accurate results. Laboratories employ internal and external quality control measures, particularly focusing on the analytical phase. Sigma metrics, representing process variation, play a crucial role in assessing accuracy, with Six Sigma setting high standards for operational excellence. This study aims to enhance laboratory testing procedures by analyzing the analytical phase. In 2022, the Emergency laboratory at KFAFH, Jeddah, achieved optimal sigma performance, marking a significant improvement in analytical testing. http://www.westgard.com/sigma-vp-kfafh.htm. In 2023, The study also demonstrated a 30% productivity increase, driven by sustained efforts and Sigma metrics implementation, leading to cost reductions and improved quality. Real-time patient moving averages enhance quality assurance, extending coverage to the total testing process. The primary objectives include redesigning IQC procedures and optimizing resource utilization. This will be accomplished by reducing the frequency of controls, minimizing unnecessary reruns, optimizing resource allocation, and managing total costs, all while ensuring compliance and averting violations. Methods A retrospective-prospective study was conducted at the Emergency Laboratory of King Fahad Armed Forces Hospital in Jeddah, Saudi Arabia, from May 2021 to October 2023. The study assessed 841,558 tests for 131,785 emergency patients. Forty-seven analytes were evaluated for Internal Quality Control and External Quality Control (CAP), with monthly data collection. Chemistry and Hematology parameters were analyzed using Unity Real-Time software on Alinity-ci and Alinity-hq analyzers. Data was collected in three stages: baseline, pre-Sigma verification, post-Sigma implementation, and a sustainability phase. The methodology involved DMAIC model tools like flowcharts, cause &amp; effect analysis, and sigma metric scales. Six Sigma process tools, including DPM and process capability analysis, were used. Interventions included Six Sigma metrics for QC performance, DPM for TAT process improvement, and patient moving average Real-time for proactive risk management in reducing analytical testing variation. Results Excellent performance (&amp;gt; 6 sigma) was achieved for 70% of chemistry test parameters for three control levels.: This indicates a high level of process capability and reliability in laboratory operations, ensuring accuracy and consistency in test results. The study successfully reduced process variation in Emergency Room (ER) laboratory Turnaround times (TATs), leading to an increase in process capability as measured on the Sigma scale, which improved from 1.35 to 3.1, indicating a more robust and efficient laboratory operation. Reducing the cost and efficiency of internal failure controls by 29% and at the same time saving in labor cost/workload marked a decrease in QC frequency from 7.0% to 0.18%, reaching the target goal of TATs and satisfaction. Conclusions The adoption of Six Sigma methodologies resulted in a notable decrease in QC runs, signaling cost savings. These high-quality methods streamline laboratory operations, improve cost-effectiveness for the healthcare system, and ultimately benefit patients and clinicians. Six Sigma methodologies play a crucial role in selecting appropriate QC designs for each parameter, ensuring efficient control while maximizing cost-effectiveness. Emphasizing the importance of suitable QC strategies and continuous technologist training is vital for mitigating analytical errors and enhancing turnaround time through comprehensive automation of the analytical phase.

B-138 A Harmonization Program Leading to Improved Accuracy and Precision of Hemoglobin A1c (HbA1c) Testing: A Six-Year Multi-Site, Multi-Instrument Review and Comparison

Abstract Background Across four global laboratory locations in North America, Europe, and Asia a quality control system was implemented in the measurement of Hemoglobin A1c (HbA1c). The intent was to improve accuracy and reduce imprecision, both being independent contributors to total analytical performance. Methods Quality control (QC) data, created during routine clinical operations, was used for this analysis. Analysis of QC data evaluated bias and precision separately and provided the ability to predict and monitor performance. The in-process harmonization program indicated a change in instrumentation was needed to meet and maintain a more stringent analytical error profile. The instrumentation change allowed for a before and after comparison across platforms. Results Use of a harmonized quality control system allowed for the visualization of the role bias and precision play in measurements. Improved performance was confirmed using native matrix samples tested routinely from participation in the National Glycohemoglobin Standardization Program. Independently assessing bias and precision highlighted the cumulative and offsetting effects that challenge quality assessment and risk mitigation. Bias appeared to have both a transient and systematic nature. The transient bias contributed to the overall normal distributive property of the quality data. In contrast, the systematic accumulation of bias appeared to occur slowly, over multiple reagent and calibration cycles. The accumulation of bias occurred in the direction of the assay drift. While precision commonly consumes the largest amount of analytical error within an instrument, the dual (negative and positive) nature of bias similarly affects the harmonization of an instrument group. Conclusions Changing the way data is viewed to include assessments of bias improved performance and aided in the identification of opportunities to reduce analytical variances that results in inter- and intra-individual variation. Harmonization of instruments should include methods to assess and describe bias, independent of precision.

Development and validation of an in vitro model to study thrombin generation on the surface of catheters in platelet-poor and platelet-rich plasma

IntroductionCoagulation activation on medical devices remains a significant problem as it can lead to dramatic thromboembolic complications. Understanding its poorly described mechanisms and finding optimal pharmacological prevention means is crucial to improve patient safety. MethodsWe developed an in vitro model to study thrombin generation (TG) initiated by the contact of plasma with the surface of catheters. Interventional cardiology catheters were cut into segments and inserted in the bottom of multi-well plates; TG was then measured with the calibrated automated thrombogram (CAT). Model performance (analytical, intra- and inter-individual variability) was investigated and compared with activation of thrombin generation by tissue factor (TF) or contact pathway activator (ellagic acid), in the presence (PRP) and absence (PPP) of platelets. Model response to unfractionated heparin (UFH) was also assessed. ResultsTG was greater when measured in presence of catheter segments, compared to conditions without activators. The analytical variability of the model was good (CV ≤ 5 %), both with PPP and PRP. Intra-individual variability was between 15 and 30 % with PPP and between 10 and 15 % with PRP. Inter-individual variability was between 15 and 30 % with both kinds of plasma samples. The analytical performance of the catheter-initiated TG model was equivalent to that observed when TG was initiated with TF or ellagic acid. Catheter-initiated TG was measurable until 0.1 IU/mL UFH with PPP and until 1.0 IU/mL UFH with PRP, highlighting the crucial requirement of platelets. ConclusionOur model is suitable for studying TG initiated with catheters. Inhibition of TG by UFH is overestimated in the absence of platelets.

Effect of Data Quality and Data Quantity on the Estimation of Intrinsic Solubility: Analysis Based on a Single-Source Data Set.

Aqueous solubility is one of the most important physicochemical properties of drug molecules and a major driving force for oral drug absorption. To date, the performance of in silico models for the estimation of solubility for novel chemical space is limited. To investigate possible reasons and remedies for this, the Johnson and Johnson in-house aqueous solubility data with over 40,000 compounds was leveraged. All data were generated through the same high-throughput assay, providing a unique opportunity to explore the relationship between data quality, quantity, and model estimations. Six intrinsic solubility data sets with different sizes and noise levels were generated by making use of three different approaches: (i) inclusion or exclusion of amorphous solid residue, (ii) measured or experimental log D to identify the intrinsic solubility, and (iii) adopting or omitting a quality check process in the data processing workflow. A random forest regressor was trained on the data sets with three different sets of descriptors calculated from RDKit, ADMET predictor, or Mordred, and the performances were evaluated with nested cross-validation as well as ten refined test sets. The models confirm, as expected, that with the same data set size, high-quality data leads to better model performance; however, also, models trained with larger data sets containing analytical variability can give equally accurate estimations compared to models trained with small, clean, and diverse data sets. However, noise introduced by including the presence of amorphous solid postsolubility measurement in the training data set cannot be overcome by increasing data size, as they are introducing a biased systematic positive error in the data set, confirming the importance of critical data review. Finally, two top-performing models were tested on the first test set from the second solubility challenge, achieving RMSE values of 0.74 and 0.72 and log S ± 0.5 of 46 and 48%, respectively. These results demonstrated improved performance compared to those reported in the findings of the competition, highlighting that a single-source curated data set can enhance the prediction of intrinsic solubility.

Intraindividual variability of semen quality, proteome, and sncRNA profiles in a healthy cohort of young adults.

Within-subject variability of semen parameters and molecular components of ejaculates in young men remains poorly understood. To investigate intraindividual variability (IIV) of semen parameters and molecular markers in repeated ejaculates from young men. Semen parameters were assessed in samples collected 6-8 days apart from 164 18-19-year old participants of the Russian Children's Study, a prospective cohort. Subsets of paired samples were used for label-free quantitation and targeted mass-spectrometry of proteins in seminal plasma (SP) and seminal extracellular vesicles (EVs), and for small non-coding RNA (sncRNA) profiling in EVs and spermatozoa using RNA-seq. The mean difference between two ejaculates, within-subject variation, intraclass correlation, and concordance correlation were used to assess IIV for all parameters. Low variability with high reproducibility and high reliability was considered if CVw<15% and ICC>0.90, respectively. Analytical variability was low for all investigated parameters in technical replicates. IIV was assessed for basic semen parameters and proteins in SPs and EVs: 319 and 777 proteins, respectively, using untargeted analysis; 9 and 10 proteins using targeted quantification. We also described the IIV for sncRNA, including microRNA, piwi-interacting RNA, tRNA, and tRNA-derived small RNA (tsRNA) in EVs (409 sncRNA and 78 tsRNA) and in spermatozoa (265 sncRNA and 15 tsRNA). We identified 22 and 27 non-overlapping proteins in SP and EVs, respectively, and 46 and 9 sncRNA, including 5 and 0 tsRNA in seminal EVs and spermatozoa, respectively, with low variability. The fatty acid synthase (FAS) had the lowest IIV in both media in targeted protein quantification. We identified a number of proteins and sncRNA with low variability among 111 proteins, 176 sncRNA, and 12 tsRNA which were previously suggested as biomarkers of male fertility and reproductive outcomes: lactotransferrin, cysteine-rich secretory protein 3, alpha-1-antichymotrypsin, epididymal sperm-binding protein 1, glutathione S-transferase Mu 3, alpha-1-acid glycoprotein 2, serum amyloid P-component, aminopeptidase N, neprilysin, FAS, and miR-10b-3p, miR-122-5p, miR-205-5p, miR-222-3p, miR-34c-5p, miR-509-3-5p, miR-888-5p, miR-892a, miR-363-3p, miR-941, miR-146a-5p, miR-744-5p. These molecules have low IIV and may be promising candidate biomarkers of male fertility and reproductive health.

PROFUGO study protocol: Predictive model for the early diagnosis of anastomotic leak after esophagectomy and gastrectomy

In esophagogastric surgery, the appearance of an anastomotic leak is the most feared complication. Early diagnosis is important for optimal management and successful resolution. For this reason, different studies have investigated the value of the use of markers to predict possible postoperative complications. Because of this, research and the creation of predictive models that identify patients at high risk of developing complications are mandatory in order to obtain an early diagnosis.The PROFUGO study (PRedictivO Model for Early Diagnosis of anastomotic LEAK after esophagectomy and gastrectomy) is proposed as a prospective and multicenter national study that aims to develop, with the help of artificial intelligence methods, a predictive model that allows for the identification of high-risk cases. of anastomotic leakage and/or major complications by analyzing different clinical and analytical variables collected during the postoperative period of patients undergoing esophagectomy or gastrectomy.