Analytical Error Research Articles

Carbon Dioxide in Soil, Ground and Surface Waters of the Northern Regions: Role, Sources, Test Methods (a Review)

Modern research proves the need to include waterbodies in regional and global models of carbon exchange. The concentration of carbon dioxide in surface waters is generally higher than equilibrium with a partial atmospheric pressure of 400 µatm allows. The study of the functioning and regional role of aquatic systems, especially regard to inorganic carbon dynamics, is insufficient, especially in circumboreal regions. The review highlights the theoretical foundations and relevance of studies of dissolved carbon dioxide; methodological approaches in assessing this indicator, as well as the role of dissolved CO2 in natural waters of boreal and arctic regions. Soil organic matter and dissolved carbon dioxide are the main sources of CO2 in surface waters, but this contribution has not yet been quantified. This is due to the underestimation of the abiotic aspects of soil gas exchange, the absolute predominance of studies of gas exchange at the soil-atmosphere interface without taking into account the interaction with groundwater, as well as methodological difficulties in measuring gas concentrations in soil-ground and surface waters. Instrumental measurement methods are not standardized, and the calculated ones have very high systematic and analytical errors. The conclusion points to the need to study the hydrological continuum: from source (terrestrial ecosystems) to large rivers and lakes, with particular attention to the incorporation of CO2 from groundwater into the carbon budget of the entire watershed.

Protein Synthesis Determined from Non-Radioactive Phenylalanine Incorporated by Antarctic Fish.

Direct measurements of temperature-dependent weight gains are experimentally challenging and time-consuming in long-lived/slow-growing organisms such as Antarctic fish. Here, we reassess methodology to quantify the in vivo protein synthesis rate from amino acids, as a key component of growth. We tested whether it is possible to avoid hazardous radioactive materials and whether the analytical pathway chosen is robust against analytical errors. In the eelpout, Pachycara brachycephalum, 13C9H1115N1O2 phenylalanine was injected intraperitoneally and muscle tissue was sampled before injection and at 1.5 h time intervals up to 6 h thereafter. The incorporation of 13C15N-labeled-phenylalanine into muscle was monitored by quantification of bound and free phenylalanine through liquid chromatography-mass spectrometry. We found an increase in the pool of labeled, free phenylalanine in the cytosolic fraction that leveled off after 4.5 h. The labeled phenylalanine bound in the proteins increased linearly over time. The resulting protein synthesis rate (Ks) for P. brachycephalum was as low as 0.049 ± 0.021% day-1. This value and its variability were in good agreement with literature data obtained from studies using radioactive labels, indicating that this methodology is well suited for characterizing growth in polar fish under in situ conditions in remote areas or on research vessels.

An Orthogonal Frequency Division Multiplexing and Universal Filtered Multi-Carrier System with Degraded Impulsive Noise Channel Analytical Bit Error Rate Performance Assessment

An Orthogonal Frequency Division Multiplexing and Universal Filtered Multi-Carrier System with Degraded Impulsive Noise Channel Analytical Bit Error Rate Performance Assessment

Developing an evidence-based approach to quality control

Effective Quality Control remains one of the pillars of Clinical Biochemistry. An understanding of the possible analytical errors that may occur, how to detect them efficiently and how to prevent them from causing patient harm are critical components of a Quality System. For some time, there have been questions about the theoretical basis of the models used to describe and detect analytical error. The current theory recognises two types of error, systematic and random and a system based on sampling the analytical process using a synthetic material to detect these errors. However, there are at least two other errors that are present. One is related to the QC material and the other, irregular errors. In this Opinion Piece, some of the underlying assumptions of Quality Control systems are described and analysed.

Kinetics and pulses of zircon growth in migmatites beneath a volcanic arc: An example from the high‐T Ryoke Complex, southwest Japan

AbstractWe present an analysis of kinetics and pulses of zircon growth in migmatites formed at middle to lower crustal depths beneath a volcanic arc. Migmatites in high‐T metamorphic complexes at active continental margins, such as in the Ryoke Complex of southwest Japan, are thought to have been produced beneath volcanic arcs. Thermal models suggest that melt advection supplies the heat to form such high‐T complexes. We found that zircons in the migmatites of the Ryoke Complex grew in multiple discrete stages by rapid diffusion‐controlled growth. The individual growth pulses can be distinguished using a Gaussian mixture model when the duration of each growth pulse is shorter than 1σ of the analytical error of the zircon age dating, and where the interval between each growth pulse is larger than 2σ of them. This method allows extraction of the growth pulses even when the zircon exhibits incomplete textural evidence for multiple stages of growth. Application of the method to the Ryoke Complex revealed three and four pulses of zircon growth with 3–10 Myr intervals for two migmatite samples respectively in the Mikawa area and three pulses with 2–4 Myr intervals from one migmatite sample in the Yanai area. The detected zircon growth pulses are consistent with previously reported pulses of plutonic activity in the two areas, with the exception of the oldest growth pulse in the Mikawa area. Therefore, the growth pulses are interpreted to be the result of thermal pulses because of melt flux events at lower to middle crustal levels. The inferred intervals of pulsed melt fluxes are similar to those of individual caldera formation in coeval caldera clusters at the surface.

What Tweets and YouTube comments have in common? Sentiment and graph analysis on data related to US elections 2020.

Most studies analyzing political traffic on Social Networks focus on a single platform, while campaigns and reactions to political events produce interactions across different social media. Ignoring such cross-platform traffic may lead to analytical errors, missing important interactions across social media that e.g. explain the cause of trending or viral discussions. This work links Twitter and YouTube social networks using cross-postings of video URLs on Twitter to discover the main tendencies and preferences of the electorate, distinguish users and communities' favouritism towards an ideology or candidate, study the sentiment towards candidates and political events, and measure political homophily. This study shows that Twitter communities correlate with YouTube comment communities: that is, Twitter users belonging to the same community in the Retweet graph tend to post YouTube video links with comments from YouTube users belonging to the same community in the YouTube Comment graph. Specifically, we identify Twitter and YouTube communities, we measure their similarity and differences and show the interactions and the correlation between the largest communities on YouTube and Twitter. To achieve that, we have gather a dataset of approximately 20M tweets and the comments of 29K YouTube videos; we present the volume, the sentiment, and the communities formed in YouTube and Twitter graphs, and publish a representative sample of the dataset, as allowed by the corresponding Twitter policy restrictions.

Variability of cardiac troponin levels in normal subjects and in patients with cardiovascular diseases: analytical considerations and clinical relevance.

In accordance with all the most recent international guidelines, the variation of circulating levels of cardiac troponins I and T, measured with high-sensitivity methods (hs-cTnI and hs-cTnT), should be used for the detection of acute myocardial injury. Recent experimental and clinical evidences have demonstrated that the evaluation of hs-cTnI and hs-cTnT variations is particularly relevant: a) for the differential diagnosis of Acute Coronary Syndromes (ACS) in patients admitted to the Emergency Department (ED); b) for the evaluation of cardiovascular risk in patients undergoing major cardiac or non-cardiac surgery, and in asymptomatic subjects of the general population aged >55years and withco-morbidities; c) for the evaluation of cardiotoxicity caused by administration of some chemotherapy drugs in patients with malignant tumors. The aim of this document is to discuss the fundamental statistical and biological considerations on the intraindividual variability of hs-cTnI and hs-cTnT over time in the same individual. Firstly, it will be discussed in detail as the variations of circulating levels strictly depend not only on the analytical error of the method used but also on the intra-individual variability of the biomarker. Afterwards, the pathophysiological interpretation and the clinical relevance of the determination of the variability of the hs-cTnI and hs-cTnT values ​​ in patients with specific clinical conditions are discussed. Finally, the evaluation over time of the variation in circulating levels of hs-cTnI and hs-cTnT is proposed for a more accurate estimation of cardiovascular risk in asymptomatic subjects from the general population.

Comparison of Two Clinical Chemistry Analyzers by Total Analytical Error and Measurement Uncertainty

Although analytical errors contain a small portion of laboratory errors, they are important in terms of intervention ability and practicality of follow-up by laboratory professionals. Also, from this point of view, the test results' quality, reliability, and accuracy are crucial to laboratories. Therefore, to determine analytical performance parameters for quality management in the analytical phase, clinical laboratories utilize total analytical error (TAE), bias, coefficient of variation (CV), and uncertainty of measurement (MU). Fifteen biochemistry parameters were compared with Beckman Coulter AU 5800 for 2017 - 2018 and Roche Cobas 8000 for 2019 - 2020 in terms of TAE and MU. The results were evaluated between devices and compared with the EuBIVAS, CLIA, RCPA, PRDEQA%, pUQEAS%, pU%, and TEa-TR datasets. There were no significant differences between the devices for the mentioned periods. Device performances resulted in similar outcomes. During our four-year study, nearly all of our tests failed for EuBIVAS, RCPA, and pU%. On the contrary, almost all of our parameters gave valid results according to the CLIA, PRDEQA%, pUQEAS%, and TEa-TR ranges. It is crucial to distinguish between "mistake" and "uncertainty." The discrepancy between the measured value and the 'actual value' is called error. Uncertainty is a measure of how confident you are in the measurement outcome. We endeavor to remedy any known inaccuracies wherever feasible by applying adjustments from calibration certifications. On the other hand, any inaccuracy whose value is unknown is a cause of doubt.

Pooled Sera as an Alternative to Commercial Internal Quality Control in Clinical Laboratories

Introduction: Internal Quality Control (IQC) is run to assess the day-to-day performance of an analytical process, ensuring the reliability of patient results. However, commercial internal quality materials can be expensive and inaccessible for many laboratories. Therefore, there is a need for an effective and economical alternative to commercial IQC. Aim: To evaluate the effectiveness and stability of pooled sera as an IQC material. Materials and Methods: A laboratory study was conducted over a period of 50 days, from January 10 to February 28, 2023, in the Department of Biochemistry at Dr. Rajendra Prasad Government Medical College (DRPGMC), Kangra, Himachal Pradesh, India. Serum samples (150 μL) were collected from 100 leftover samples over a span of 10 days. The serum was thoroughly mixed and distributed into 75 aliquots. Commercial IQC was also reconstituted and distributed into 75 aliquots. Both the commercial and pooled sera IQC were stored at -20°C. One aliquot of pooled sera was analysed daily for 16 routine biochemistry parameters, along with the commercial IQC, for the entire 50-day period. The results from both materials were interpreted using L-J chart and Westgard multirule. The stability of pooled sera for these routine parameters was assessed by comparing the mean values of the biochemical parameters on day 1 and day 50. Data analysis was performed using Statistical Package for the Social Sciences (SPSS) version 20.0 software, and a paired t-test with a p-value <0.05 was considered statistically significant. The bias percentage for each pooled sera parameter was calculated and compared with the desirable bias for clinical significance. Results: Analytical errors were observed during the study period for Alkaline Phosphatase (ALP), urea, sodium, potassium, and chloride. The nature and number of analytical errors observed with both materials were the same, with Westgard rule 13s detecting random errors for ALP and rule 22s detecting systematic errors for urea and serum electrolytes (sodium, potassium, and chloride). Difference in the mean value of alanine transaminase, aspartate transaminase, and bilirubin, on day 1 and day 50 was statistically significant with p-values 0.035, 0.04, and 0.024, respectively. When these parameters were assessed for clinical bias, they were found to be clinically insignificant. Conclusion: Pooled serum is an effective and stable alternative IQC material for daily performance assessment of analytical processes. In-house IQC or pooled sera not only reduces the cost of quality control but also helps maintain continuity in the absence of commercial IQC, preventing any disruptions in the control system over an extended period.

Falsely elevated levels of 25(OH) vitamin D measured on alinity: two case reports

Background: Conventional biochemistry parameters employ the use of photometry and enzymatic reactions which reduce the possibility of analytical errors. On contrary, tests performed with immunoassay are known to be more prone to analytical interferences and may subsequently yield incorrect values. Case presentation: We present two cases investigated due to very high levels of vitamin D in the serum that exceeded the measurable limit of the analyzer. Protein electrophoresis showed a monoclonal peak, revealing elevated immunoglobulin G and elevated immunoglobulin M respectively. Gold standard analysis of vitamin D using liquid chromatography-mass spectrometry revealed normal vitamin D concentrations in both cases. Further, bone marrow puncture revealed a diagnosis consistent with multiple myeloma and Waldenstroms macroglobulinemia. Conclusion: Falsely elevated levels of vitamin D exceeding the maximum measurable limit is highly suspicious. Although analytical interference in immunoassay is limited, we should keep in mind that results obtained by this method are more prone to analytical errors.

Study of analytical error in lipase assay.

Lipase and amylase are the most frequently used biomarker for the diagnosis of pancreatic diseases, especially acute pancreatitis. Lipase has better diagnostic accuracy in comparison to amylase for the analysis of acute pancreatitis. However, lipase assay in random access analyzer is sometimes difficult to perform as it is exposed to different types of samples or reagents which may act as interference. In our laboratory, we found the raised values (>500 IU/L) of lipase with normal amylase in some samples. However, the immediate rerun of these samples for lipase only showed normal (<80 IU/L) lipase level. To root out this fallacy, we performed reagent and sample carryover studies. The cause of the falsely raised value of lipase was revealed by reagent carryover studies. All samples which assayed triglyceride (TGL) followed by lipase immediately after it showed elevated (>500 IU/L) lipase value. This is due to the interference of microbial lipase used in TGL reagents. This was corrected by separating the analysis of lipase and TGL into two different instruments. If interference testing is not done, the laboratories are prone to have an analytical error in reporting and hence lead to diagnostic error. Hence, after analyzer installation, interference testing should be included in the validation protocol.

Pre-analytical Variables: A Potential Source of Laboratory Error

Clinical laboratories have a great role in the management of patients. To ensure quality test results laboratories need to maintainstandards in all the three phase of total testing process- pre analytical, analytical and post-analytical. With the advancement ofmodern technologies analytical and post-analytical errors have been reduced significantly but pre-analytical errors are stillvery common, which can be as high as 71% of total error rate. This is because; many of the steps in this phase are related tohuman activities and outside of the laboratories that are not under the direct control of laboratory. Pre-analytical errors canoccur during test ordering by the physicians, patient preparation, sample collection, transportation or during processing of thesample. Though most of the errors in this phase remain within the reference limit but 25% can produce erroneous results thatcan affect patient health. In order to minimize errors in this phase it is mandatory to check and identify the sources of pre-analytical errors.

Segmental Aperture Imaging Algorithm for Multirotor UAV-Borne MiniSAR

This article takes on the challenges of synthetic aperture radar (SAR) imaging for miniaturized SAR (MiniSAR) onboard a multirotor unmanned aerial vehicle (UAV). Several unique challenges are systematically analyzed, and a corresponding analytical phase error model is established, which accurately models the effects of both translational and rotational motions of UAVs. A segmental aperture imaging (SAI) algorithm, an autofocus algorithm based on strong scatterers, is proposed. It simply divides the platform trajectory into uneven segments, which are first independently focused with motion compensation and then stitched together to form a complete SAR image. Both the theoretical derivation of the signal model and the implementation of the imaging algorithm are presented. A simulation analysis with actual UAV trajectory and attitude data is conducted, which demonstrates the efficacy and performance of the proposed imaging algorithm. It shows that the ideal focusing effect can be achieved as evaluated by various metrics, and the proposed algorithm has superior performance compared to the subaperture phase gradient autofocus (PGA) and minimum entropy autofocus (MEA) methods. Finally, the multirotor-borne MiniSAR system FUSAR-Ku is used for experiments to verify the proposed algorithm. Experimental results show that the proposed algorithm can achieve the theoretical decimeter-resolution imaging performance as measured by various metrics.

Errors of sensors for conversion of multi-phase currents into voltage in power supply systems

The paper presents the structure of the sensor for converting multi-phase primary currents into secondary voltages of reactive power of power supply networks, the algorithm for modeling processes in the sensor that sends a signal to the primary current monitoring and control devices provides a highly formalized graph model based on an analytical expression, static characteristics and sensor errors studied on the basis of its analytic expression.

An ESPRIT-Based Supervised Channel Estimation Method Using Tensor Train Decomposition for mmWave 3-D MIMO-OFDM Systems

This paper focuses on the downlink supervised channel estimation problem for the millimeter wave threedimensional multiple-input multiple-output orthogonal frequency division multiplexing (mmWave 3D MIMO-OFDM) systems, where both the transmitter and the receiver are equipped with uniform rectangular arrays (URAs). Based on the sparse scattering nature, the mmWave channel is modeled as a low-rank higher-order tensor. By formulating the channel and the received training signal as tensors, a fast ESPRIT-based Vandermondestructured tensor decomposition method is proposed to estimate the channel parameters involving angles of arrival and departure (AoAs/AoDs), delays and path gains. In specific, we first establish the relationship of the tensor ranks between the tensor train (TT) model and the higher-order tensor CANDECOMP/PARAFAC (CP) signal model. Then the TT decomposition is used to estimate the signal subspace and derive the shift invariance equation, which exploits the higher-order tensor low-rankness of the signal and the Vandermonde structure in the frequency domain. Based on the derived analytical estimation errors, theoretical justifications are provided to unveil the advantage of using TT decomposition. Moreover, we extend the proposed method in an iterative manner to pursue higher accuracy. According to our simulation results, compared with the state-of-the-art, the proposed method achieves higher estimation accuracy on both the channel parameters and the entire channel. In addition, up to 87% of computing time can be saved in comparison to the current best iterative algorithm in the experiments.

A Novel Motion Compensation Method Applicable to Ground Cartesian Back-Projection Algorithm for Airborne Circular SAR

The Ground-Cartesian factorized back-projection (G-CFBP) is an efficient time-domain processing algorithm without image interpolation, and can realize accurate imaging for curved trajectory synthetic aperture radar (SAR). Its superiority shows good potential in airborne circular SAR (CSAR) imaging. However, the motion compensation (MoCo) based on ground Cartesian back-projection (GCBP) in the airborne CSAR is still a challenge. There are two main problems: one is that the existence of the image spectrum aliasing makes the processing of the phase error estimation inaccurate; the other is that the mapping relationship of the phase error between the image spectrum domain and the azimuth time domain still needs to be studied within GCBP processing chain. To tackle the above two problems, a novel MoCo method applicable to the GCBP algorithm is proposed and can be mainly divided into two steps: the first step is to remove the sub-aperture image spectrum aliasing by a spectrum compression operation; the second step is to establish an analytical phase error structure, which includes an auto-selection criterion of the effective support region for GCBP image. The first step ensures the accuracy of the phase error estimation, and the second step establishes the inverse-mapping relationship of the phase error between the image spectrum and azimuth time. These two procedures are both vital in improving the accuracy and robustness of the GCBP-based MoCo for the CSAR imaging. The processed results of simulated and real data are provided to verify the effectiveness of the proposed method.

A New Perspective to Longstanding Challenges with Outpatient Hyperkalemia: A Narrative Review.

Outpatient hyperkalemia is a common problem with potentially deadly consequences. Potassium level thresholds to treat outpatient hyperkalemia are unstandardized and variable, leaving health care providers to rely on their own clinical judgment. This narrative review highlights the challenges of outpatient hyperkalemia management and includes recommendations for future studies that may standardize treatment, improve patient outcomes, and optimize health care utilization. PubMed, Google Scholar, and the reference lists of identified articles were used to include English, peer-reviewed studies and guidelines for this review. This narrative review examines outpatient hyperkalemia from both a laboratory and clinical perspective. In addition to peer-reviewed literature, guidelines and expert consensus statements were included to highlight the inconsistencies and paucity of evidence that health care providers rely on to make clinical decisions. There are multiple reasons why outpatient hyperkalemia management is both challenging and sub-optimal. Clinicians must discern if the potassium level result is accurate and, if so, does the result warrant referral to the emergency department. Factitious hyperkalemia, or falsely elevated potassium level results due to analytical errors, occurs frequently, but there are no ways to identify it other than for hemolyzed samples. Additionally, guidelines and expert panels are inconsistent on the thresholds for treatment and the management of hyperkalemia. Finally, there are inconsistencies between laboratories as to when and how providers are notified of results, and the suggested thresholds for urgent management. A study that integrates the expertise of clinical biochemists and clinicians is needed to inform evidence-based guidelines for the management of outpatient hyperkalemia. This was a comprehensive review of what is known and what still needs to be understood for the management of outpatient hyperkalemia. A formal tool to assess the quality of the included studies was not used and selection bias may have occurred.

Barometers Behaving Badly I: Assessing the Influence of Analytical and Experimental Uncertainty on Clinopyroxene Thermobarometry Calculations at Crustal Conditions

Abstract The composition of clinopyroxene and clinopyroxene-liquid (Cpx-Liq) pairs are frequently used to calculate crystallization/equilibration pressures in igneous systems. While canonical uncertainties are often assigned to calculated pressures based on fits to calibration or test datasets, the sources of these uncertainties (and thus ways to reduce them) have not been rigorously assessed. We show that considerable uncertainties in calculated pressures arise from analytical error associated with Electron Probe Microanalyser (EPMA) measurements of Cpx. Specifically, low X-ray counts during analysis of elements with concentrations &amp;lt;1 wt% resulting from insufficient count times and/or low beam currents yield highly imprecise measurements (1σ errors of 10–40% for Na2O). Low analytical precision propagates into the calculation of pressure-sensitive mineral components such as jadeite. Using Monte Carlo approaches, we demonstrate that elemental variation resulting from analytical precision alone generates pressures spanning ~4 kbar (~15 km) for a single Cpx and ~6 kbar for a single Cpx-Liq pair using popular barometry expressions. In addition, analytical uncertainties in mineral compositions produce highly correlated arrays between pressure and temperature that have been previously attributed to transcrustal magma storage. Before invoking such geological interpretations, a more mundane origin from analytical imprecision must be ruled out. Most importantly, low analytical precision does not just affect the application of barometers to natural systems; it has also affected characterization of Cpx in experimental products used to calibrate and test barometers. The impact of poor precision on each individual measurement is often magnified by the small number of measurements made within experimental charges, meaning that low analytical precision and true variability in mineral compositions have not been sufficiently mediated by averaging multiple EPMA analyses. We compile the number of Cpx measurements performed in N = 307 experiments used to calibrate existing barometers, and N = 490 new experiments, finding ~45% of experiment charges were characterized by ≤5 individual Cpx analyses. Insufficient characterization of the true composition of experimental phases likely accounts for the fact that all Cpx-based barometers exhibit large errors (± 3 kbar) when tested using global experimental datasets. We suggest specific changes to analytical and experimental protocols, such as increased count times and/or higher beam currents when measuring low concentration elements in relatively beam resistant Cpx in experiments and natural samples. We also advocate for increasing the number of analyses per experimental charge, resolving interlaboratory analytical offsets and improving data reporting. Implementing these changes is essential to produce a more robust dataset to calibrate and test the next generation of more precise and accurate Cpx-based barometers. In turn, this will enable more rigorous investigation of magma storage geometries in a variety of tectonic settings (e.g. distinguishing true transcrustal storage vs. storage in discrete reservoirs).

How to avoid analytical errors in blood gas analysis

How to avoid analytical errors in blood gas analysis - IJCBR- Print ISSN No: - 2394-6369 Online ISSN No:- 2394-6377 Article DOI No:- 10.18231/j.ijcbr.2022.068, International Journal of Clinical Biochemistry and Research-Int J Clin Biochem Res

Accuracy and Clinical Impact of Estimating Low-Density Lipoprotein-Cholesterol at High and Low Levels by Different Equations.

New more effective lipid-lowering therapies have made it important to accurately determine Low-density lipoprotein-cholesterol (LDL-C) at both high and low levels. LDL-C was measured by the β-quantification reference method (BQ) (N = 40,346) and compared to Friedewald (F-LDL-C), Martin (M-LDL-C), extended Martin (eM-LDL-C) and Sampson (S-LDL-C) equations by regression analysis, error-grid analysis, and concordance with the BQ method for classification into different LDL-C treatment intervals. For triglycerides (TG) &lt; 175 mg/dL, the four LDL-C equations yielded similarly accurate results, but for TG between 175 and 800 mg/dL, the S-LDL-C equation when compared to the BQ method had a lower mean absolute difference (mg/dL) (MAD = 10.66) than F-LDL-C (MAD = 13.09), M-LDL-C (MAD = 13.16) or eM-LDL-C (MAD = 12.70) equations. By error-grid analysis, the S-LDL-C equation for TG &gt; 400 mg/dL not only had the least analytical errors but also the lowest frequency of clinically relevant errors at the low (&lt;70 mg/dL) and high (&gt;190 mg/dL) LDL-C cut-points (S-LDL-C: 13.5%, F-LDL-C: 23.0%, M-LDL-C: 20.5%) and eM-LDL-C: 20.0%) equations. The S-LDL-C equation also had the best overall concordance to the BQ reference method for classifying patients into different LDL-C treatment intervals. The S-LDL-C equation is both more analytically accurate than alternative equations and results in less clinically relevant errors at high and low LDL-C levels.