Deming Regression Research Articles

A comprehensive evaluation of existing and new model-identification approaches for non-destructive concrete strength assessment

The common practice of concrete strength assessment is to combine non-destructive techniques (NDT) with core test measurements to develop a conversion model that is used to estimate the strengths at NDT test locations. In this work, different model identification approaches to develop this conversion model are investigated, namely regularized regression, quantile regression, Deming regression, bi-objective approach, geometric mean regression, orthogonal regression, and support vector machine (SVM) regression intending to improve the conversion model prediction capability so that accurate estimates of concrete strength can be obtained with a small number of cores. These approaches: in addition to other existing approaches, are first assessed using synthetic datasets and then tested on a real data case study by developing a set of cumulative distribution functions that provides information regarding the risk of a wrong prediction of concrete strength, outside a tolerable level. The results showed that concrete variability was best estimated using Deming regression, orthogonal regression, and bi-objective approach while local strengths were best estimated using quantile and regularized regression. Further, mean concrete strength estimation was observed to be not significantly affected by the choice of a model identification approach. Based on these results, a hybrid conversion model identification system that uses the bi-objective approach for mean and variability estimation and quantile regression for local strengths estimation is proposed. This study also proposes new tabular displays for the selection of the minimum number of cores required for reliable estimation of strength using information related to the NDT measurements and a choice of an accepted risk in the estimation. These tabular displays were produced using extensive analysis of synthetic data to determine the minimum number of cores required to limit the probability of the wrong estimation of strength within an admissible margin of error. Lastly, a web app was developed to easily provide the conversion models and the minimum number of cores for reliable concrete assessment.

Challenged comparison of tacrolimus assays

Monitoring tacrolimus trough concentrations is important for optimal immunosuppression in solid organ transplant recipients. Available assays generally correlate well with each other but little attention is given to patients in whom tacrolimus metabolite concentrations might be elevated, which could lead to artificially increased tacrolimus concentrations assessed by cross-reacting immunoassays. We addressed this hypothesis by investigating the correlation between four different assays (two immunoassays and two mass-spectrometry assays) in both a population with normal and a population with high dose requirements. Routine blood samples were collected in 37 control (CO) and 72 high dose patients (HD). Tacrolimus was measured with a CMIA, an ECLIA and two LCMS assays. Results were investigated using Deming regression analysis, Pearson correlation coefficients, Bland-Altman plots and by calculating bias. The CMIA demonstrated a positive bias of 23–26% compared with both LCMS assays. The correlation between CMIA and LCMS assays was good for the CO (r = 0.96) but less so for the HD group (r = 0.91). The ECLIA showed a positive bias of 11–13% compared with both LCMS assays. The correlation between ECLIA and LCMS assays was also good for the CO (r = 0.95) but again less for the HD group (r = 0.93). The correlation for both LCMS assays was excellent for either group (r > 0.99) with no bias. CMIA, ECLIA and LCMS assays for tacrolimus therefore correlate well for trough concentrations from solid organ transplant recipients. However, inter-assay differences exist, which seem more pronounced in patients who need a high dose of tacrolimus to reach a trough concentration in the therapeutic range.

Generalizing R 2 for deming regressions

The simple linear regression model and the associated goodness-of-fit measure, the coefficient of determination, R 2, are only appropriate when all measurement errors are associated with the measurement of the data in the dependent variable. When measurement errors are assumed in both variables, a Deming regression can be used; however, there is no associated R 2-type measure for this specific type of regression. In this paper, we propose a measure, which utilizes the minimum percentage improvement of the Deming regression over either the horizontal or the vertical line through the centroid of the data. We investigate some properties of this measure and its relation to R 2. We also consider other candidate methodologies for a generalized R 2 measure for a Deming regression model and investigate strengths and weaknesses of each as a way of beginning the conversation about which measure is the best and for which applications it is most suited.

Prediction of total carotenoids, color, and moisture content of carrot slices during hot air drying using non‐invasive hyperspectral imaging technique

The objective of this paper was to evaluate the performance of Partial Least Square Regression (PLSR) model and to assess the statistical agreement between two different measurement techniques, that is, Vis–NIR hyperspectral imaging (HSI) and standard laboratory methods for quality evaluation of dried carrots throughout the hot-air drying process. Carrots at commercial maturity of 3.5 months after planting were harvested in two seasons (2017 and 2018) and dried in a convective hot air dryer at 50°C, 60°C, and 70°C. Quality measurements were examined at intervals of 30 minutes. PLSR was performed as a regression model to predict quality attributes in carrots, while Passing–Bablok and Deming regressions alongside Blant–Altman analysis were applied as method comparisons. Excellent prediction performance for moisture content was observed with high R2T and R2v at 0.92 and 0.90 with values of RMSET and RMSEv at 8.15% and 8.16%. Satisfactory prediction accuracies were observed for total carotenoids (R2v = 0.64 and RMSEv = 32.62) μg/g, L* (R2v = 0.68 and RMSEv = 32.62), a* (R2v = 0.69 and RMSEv = 1.18), and b* (R2v = 0.60 and RMSEv = 1.45). Selected wavelengths for total carotenoids, moisture content, L*, a*, and b* based on the highest score of VIP loadings were 531, 973, 531, 531, and 680 nm, respectively. An adequate agreement of Blant–Altman analysis between the two methods within the upper and lower limits of 95% confidence interval (CI) were obtained for total carotenoids from 95.68 μg/g to 82.34 μg/g, moisture content (25.18% to 22.93%), L* (2.88 to −3.30), a* (4.15 to 3.43), and b* (4.53 to −3.11) with mean differences at 6.67, 1.12, −0.21, 0.36, and 0.71, respectively. Good correlation coefficients (r) were also observed at 0.89, 0.91, 0.78, and 0.83 for moisture content, L*, a*, and b* with a moderate correlation of total carotenoids at 0.69. The results indicate the potential feasibility of using non-invasive measurement of quality attributes using hyperspectral imaging during the drying of carrots. Novelty impact statement non-invasive measurement using hyperspectral imaging for quality determination in carrots during convective drying demonstrated promising results. Multivariate analysis of Partial Least Square Regression showed a good modeling performance for quality prediction in dried carrots. A good statistical agreements between non-invasive quality measurements using hyperspectral imaging and standard laboratory analysis were achieved by comparative analysis using Blant–Altman plot, Deming, and Passing–Bablok regression.

Assessment of one-year risk of ischemic stroke versus major bleeding in patients with atrial fibrillation

BackgroundPatients diagnosed with atrial fibrillation (AF) are at increased risk of stroke. Several guidelines to assess the risk of ischemic stroke and major bleeding in AF patients have been published. The CHA2DS2-VASc score has been adopted widely for predicting stroke within one year of the index AF diagnosis and is used to guide the prescription of anticoagulants. Anticoagulation therapy increases the risk of bleeding and scoring systems such as HAS-BLED assess the risk of major bleeding in anticoagulated patients. Despite these advances, no study has examined the risks of the two outcomes simultaneously. How patients’ fear of particular outcomes affects these risks also remains unknown. MethodsWe incorporated the risks of ischemic stroke and major bleeding within one year of the index AF admission as well as the fear of stroke and bleeding of each individual patient. The patients enrolled in this retrospective observational study were identified using hospital admission data from the Myocardial Infarction Data Acquisition System (MIDAS), a statewide database including all hospitalizations for cardiovascular disease in New Jersey. Probabilities of the outcomes (ischemic stroke, major bleeding, both, or neither within one year of the index AF admission) were estimated using multinomial regression with patient demographics and comorbidities (heart failure [HF], hypertension [HTN], diabetes mellitus [DM], anemia, chronic obstructive pulmonary disease [COPD], kidney disease [KD], prior stroke or transient ischemic attack [TIA]) as predictors. These estimates were used in a Deming regression to model the association of ischemic stroke and major bleeding in grouped patients. The assessment of the importance of each outcome was superimposed on the final model to arrive at a recommendation for anticoagulation therapy. ResultsThe results of the Deming regression indicated a positive relationship between ischemic stroke and major bleeding (slope = 1.67, 95% confidence interval [CI] 1.37 to 1.97). Estimates of the risks of the two outcomes and the lines of best fit from Deming regression were determined. This model for risk assessment of stroke and major bleeding within one year of the index AF hospital admission combined objective data and subjective assessment of the relative fear of stroke versus bleeding by each hypothetical patient on 0–100 scale. Examples with the fears of stroke versus major bleeding being equal (50-50) and a higher fear of stroke (80–20) are presented. ConclusionsThe new model for risk assessment of ischemic stroke and major bleeding within one year of the index AF hospital admission proposed in this work used objective, empirically driven measures, and subjective assessment of the outcomes’ importance for individual patients. Such models may assist physicians in their decision making regarding anticoagulation therapy.

Performance characteristics of the first Food and Drug Administration (FDA)-cleared digital droplet PCR (ddPCR) assay for BCR::ABL1 monitoring in chronic myelogenous leukemia.

Chronic myelogenous leukemia (CML) is a hematopoietic stem cell malignancy that accounts for 15–20% of all cases of leukemia. CML is caused by a translocation between chromosomes 9 and 22 which creates an abnormal fusion gene, BCR::ABL1. The amount of BCR::ABL1 transcript RNA is a marker of disease progression and the effectiveness of tyrosine kinase inhibitor (TKI) treatment. This study determined the analytical and clinical performance of a droplet digital PCR based assay (QXDx BCR-ABL %IS Kit; Bio-Rad) for BCR::ABL1 quantification. The test has a limit of detection of MR4.7 (0.002%) and a linear range of MR0.3–4.7 (50–0.002%IS). Reproducibility of results across multiple sites, days, instruments, and users was evaluated using panels made from BCR::ABL1 positive patient samples. Clinical performance of the assay was evaluated on patient samples and compared to an existing FDA-cleared test. The reproducibility study noted negligible contributions to variance from site, instrument, day, and user for samples spanning from MR 0.7–4.2. The assay demonstrated excellent clinical correlation with the comparator test using a Deming regression with a Pearson R of 0.99, slope of 1.037 and intercept of 0.1084. This data establishes that the QXDx™ BCR-ABL %IS Kit is an accurate, precise, and sensitive system for the diagnosis and monitoring of CML.

Validation of a New High-Throughput BD COR System Using the BD CTGCTV2 Assay

This study determined the precision and reproducibility of results for the BD CTGCTV2 (CTGCTV2) assay on the BD COR System (COR). The clinical performance of the CTGCTV2 assay conducted on COR was compared with its performance on the BD MAX System (MAX) for detecting Chlamydia trachomatis, Neisseria gonorrhoeae, or Trichomonas vaginalis. The multiday precision and multisite reproducibility studies were conducted using contrived panels of positive and negative urine and PreservCyt specimens. A total of 433 panel members, generated from remnant clinical specimens, were tested in the clinical comparison study. Each panel member was tested three times on MAX and three times on COR. The results in the same testing group were compared for agreement by target. The cycle threshold scores from MAX and COR were analyzed by paired t-test and Deming regression. The CTGCTV2 assay on COR showed high reproducibility in the multiday and multisite precision analysis. The point estimates of positive percent agreement and negative percent agreement in the clinical comparison study for all three targets were greater than 95%, with all corresponding lower bounds of two-sided 95% CIs greater than 90%. Cycle threshold score comparison showed no systematic difference between the two systems. The results of this study show equivalent performance of the CTGCTV2 assay on the MAX and COR systems.

Multicenter performance evaluation and reference range determination of a new one-stage factor VIII assay.

IntroductionWe conducted a multicenter evaluation of a new one‐stage factor VIII (FVIII) assay (Roche Diagnostics), intended for the quantitative assessment of FVIII activity. We evaluated the analytical performance of the FVIII assay on the cobas t 711 analyzer.MethodsExperiments performed at three laboratories used 3.2% citrated residual or commercially purchased plasma samples. Five human plasma pools and two controls were used to determine assay within‐run and within‐laboratory precision, and total reproducibility; coefficients of variation (CVs) and/or standard deviations (SDs) were calculated. Lot‐to‐lot variability and method comparison (vs Coagulation FVIII Deficient Plasma/Dade Actin FS Activated PTT reagent/Standard Human Plasma Calibrator on the Sysmex CS‐5100 analyzer; Siemens Healthineers) were evaluated by Passing–Bablok and Deming regression, respectively, and Pearson's r calculated. Assay‐specific reference range was determined using 199 fresh plasma samples from healthy adults, not receiving anticoagulants.ResultsAcross sites, SDs for repeatability were 0.016–0.046 for samples with ≤1.0 international units (IU)/dL FVIII activity; CVs were 0.9%–3.8% for samples with >1.0 IU/dl activity. Among samples with mean FVIII activity 0.344–133 IU/dl, good intermediate precision (SD 0.020 for samples with 0.344 IU/dl activity; CV 1.8%–4.7%) and good total reproducibility (CV 2.0%–13.3%) were observed. The FVIII assay showed excellent lot‐to‐lot variability (Pearson's r = .999) and good correlation with the comparator assay (Pearson's r = .993–.996). The reference range for FVIII activity was 82.2−218.0 IU/dl.ConclusionThe one‐stage FVIII assay demonstrated robust analytical performance on the cobas t 711 analyzer, supporting its use in routine laboratory practice.

Comparing Boron Soil Testing Methods for Coastal Plain Sandy Soils

ABSTRACT There are several methods for determining boron (B) in soil for soil testing purposes, yet variability among methods can lead to inconsistencies in determined concentrations for the same soil sample. The most typical method used to determine B in soil is hot-water B (HWB) extraction, but this method has reduced efficiency when dealing with large sets of soil samples along with other disadvantages such as non-uniformity in the boiling of samples. As a result, universal extractants have become increasingly popular for the extraction of B due to enhanced efficiency in a high throughput laboratory setting. This study uses a Deming regression model to compare the traditional HWB extraction method with two common universal extractants, Mehlich-1 (M1), and Mehlich-3 (M3), for coastal plain sandy soils. Results showed M3-B extractability is consistently higher than M1-B and HWB for all tested soils. The M3 method was then verified for precision using blind extension soil samples. The hot-water method was unsuccessful in producing reliable extractable B concentration in soils with high calcium carbonate and organic matter contents. Results from this study can be used to optimize B determination for high throughput production laboratory settings.

Automated contouring of non-contrast echocardiograms result in similar estimates of left ventricular function to manually contoured contrast-enhanced images in chemotherapy patients

Abstract Funding Acknowledgements Type of funding sources: Private company. Main funding source(s): Ultromics Ltd Introduction Transthoracic echocardiography (TTE) assessment of left ventricular (LV) function has a central role in early detection and treatment of cancer-therapy related cardiac dysfunction (CTRCD). Contrast TTE is recommended to aid accurate and reproducible LV contouring , but contrast agents are underused and high variability remains. Using machine learning (ML) to automatically contour the LV reduces variability, and may provide comparable clinical benefit to contrast-enhanced TTE. Purpose Retrospective single site study evaluating agreement between LV volumes and function from manually contoured contrast-enhanced TTE and automated contouring of non-contrast enhanced images. Methods Adults at risk of developing CTRCD who underwent TTE were recruited. LV volumes (end-diastolic and systolic; EDV and ESV, respectively) and function (ejection fraction; EF) were measured from contrast-enhanced images using manual contouring (MAN-CONT), and non-contrast enhanced images using automation (AUTO-NON). Method comparisons were summarised based on: (i) statistical equivalence (two one-sided t-tests), (ii) systematic difference between methods, via root mean-squared error (RMSE; Deming regression), and (iii) average bias (Bland-Altman). Statistical equivalence bounds were conservatively determined from reproducibility estimates in a similar cohort (EDV, 20 mL; ESV, 15 mL; EF, 5%; REF1), and used to interpret RMSE and bias. Results The cohort comprised of patients undergoing treatment for breast cancer, lymphoma, and myeloma. Similar body mass indices were seen between groups (median [IQR]: 26.5 [6.7] kg/m2; Kruskall-Wallace test, p = 0.320), but breast cancer patients were younger (55.0 [14.5], 58.5 [23], 60 [9], respectively; p = 0.034). For estimates of LV volumes and function, statistical equivalence, RMSE, and bias are presented in Table1. Average estimates (mean [SD]) of EDV, ESV, and EF were 121 [33] vs. 112 [33] mL, 50 [23] vs. 44 [19] mL, and 60 [9] vs. 61 [8]%, for MAN-CON and AUTO-NON respectively. Comparing between MAN-CON and AUTO-NON in breast cancer patients, all variables were statistically equivalent (Figure1), and while bias was lower than equivalence bounds, RMSE was only lower for EDV and ESV, not EF. For lymphoma patients, estimates of EDV were statistically equivalent, but not EF and ESV. Bias was lower than equivalence bounds for all variables, whereas RMSE was lower for ESV, but not EDV or EF. For myeloma patients, estimates of ESV and EF were statistically equivalent, but not EDV. While bias was lower than equivalence bounds for all variables, RMSE was not lower for any variable. Conclusions: Estimates of LV function from automated contouring of non-contrast TTE are similar to contrast-enhanced TTE (manually contoured), despite poorer image quality. Automated contouring using ML reduces variability, therefore increasing TTE sensitivity, which is critical when clinical management relies on accurate assessment of LV function. Abstract Table1 Abstract Figure1

Development of Indirect Quantitative Methods for 3-MCPD Fatty Acid Esters (3-MCPDEs) and Glycidyl Fatty Acid Esters (GEs) in Thermally Processed Foodstuffs.

For indirect determination of 3-chloro-1,2-propanediol fatty acid esters (3-MCPDEs) and glycidyl fatty acid esters (GEs) in thermally processed foodstuffs distributed in Japan, we modified two published methods, an enzymatic method (later approved as JOCS Standard Method for the Analysis of Fats, Oils, and Related Materials 2.4.14-2016 and Joint JOCS/AOCS Official Method Cd 29d-19) and EFSA method developed by the Joint Research Centre of the European Commission. The performance of these methods was demonstrated to be satisfactory. The partially modified enzymatic method showed mean recoveries of 93.7-98.5% for 3-MCPDEs, 94.4-98.4% for GEs, and HorRat(r) values of 0.06-0.78 in analyses of 6 types of foods including Japanese specific foods (fried rice cracker, fried instant noodle, biscuit, karinto, vegetable tempura, and frozen deep-fried chicken) spiked with 3-MCPD dioleate and glycidyl oleate at 0.02-0.04 mg/kg or 0.2-0.4 mg/kg. The partially modified EFSA method showed mean recoveries of 96.6-99.4% for 3-MCPDEs, 95.7-100.1% for GEs, and HorRat(r) values of 0.14-1.05 in analyses of 5 types of foods (not including karinto) spiked simultaneously with 3-MCPD dioleate and glycidyl oleate at either 0.02-0.04 mg/kg or 0.2-0.4 mg/kg. The results of analyses of 9 samples (fried rice cracker, biscuit, 2 potato crisps, fried potato snack, baked cracker, cracker dough, seafood tempura, and frozen deep-fried chicken) using these 2 methods were comparable. The 95% confidence intervals determined with weighted Deming regression analysis between the results of 3-MCPDEs or GEs in the same samples analyzed by the 2 methods showed: the slope around 1 (3-MCPDEs, 0.982-1.025; GEs, 0.887-1.078); and intercept close to 0 (3-MCPDEs, －0.002-0.003; GEs, －0.011-0.015). These data confirmed that the concentrations of 3-MCPDEs and GEs in food samples determined by 2 independent analytical methods were equivalent.

Comparison of the Vcheck and IMMULITE 2000 methods for T4 measurement in canine and feline serum

The aim of this study was to compare canine and feline thyroxine (T4) results obtained by the Vcheck method with those obtained by the IMMULITE 2000 immunoassay, which had previously been validated for canine serum. The concentration of T4 in 53 canine and 44 feline serum samples was determined concurrently by the Vcheck and IMMULITE methods, the latter as the reference method. The T4 values were compared using the IMMULITE Youden plot and Deming regression analysis. According to the regression analysis, the two methods gave comparable results. Spearman’s correlation shows a very high consistency of the results obtained by the two analyzers. The results of the Vcheck method were comparable to those of the IMMULITE 2000 reference method, so Vcheck may be used as an alternative assay to evaluate the serum thyroxine concentration in dogs and cats for the diagnosis of thyroid gland disease.

Usklađenost POCT metode sa potpuno automatizovanom metodom za određivanje HbA1c

Previous research suggests that point-of-care (POCT) determination of glycated hemoglobin (HbA1c) is a diagnostic test that can be an adequate alternative to measuring HbA1c in the laboratory. The main goal of this study was to examine the analytical characteristics of the novel INCLIX POCT method for HbA1c determination in order to test its performance before introducing this method into routine use. HbA1c is measured in a duplicate in 44 EDTA blood samples parallel on INCLIX POCT device (Sugitech, Inc.) and using automated turbidimetric immunoinhibition test on Olympus AU400 (Beckman Coulter). The within run imprecision was 7.58%, between runs imprecision was 6.63% and 6.22%, and day-to-day imprecision was 8.80% and 7.51%. Total laboratory imprecision was in agreement with those stated by the manufacturer. A statistically significant Pearson correlation coefficient was calculated (r = 0.871, P < 0.01; linear R2 = 0.757). Using Deming regression analysis, the following equation was obtained: y = - 1.80 + 1.304x. Our results indicate statistically significant correlation, linear relationship, and a significant degree of compatibility between the two analyzed methods. However, the negative bias of the HbA1c values determined on the POCT analyzer compared to the Olympus AU400 was confirmed, highlighting the need to standardize the INCLIX method.

Multifactorial effects of gluconic acid pretreatment of waste straws on enzymatic hydrolysis performance

The chemical compositions of lignin, hemicellulose and cellulose are so far unascertained to various lignocellulose in respect to effect of cellulose enzymatic hydrolysis. The novel and environment-friendly gluconic acid (GA) pretreatment technology showed impressive results on the enzymatic hydrolysis of cellulose in various agricultural straws. However, only few of the main reasons or critical issues pertaining to this reaction are known. Therefore, the novel GA pretreatment was carried out to remove hemicellulose from the three representative waste straws under different conditions. Next, for the enzymatic hydrolysis of the residual cellulose fraction in the pretreated straws, some mathematical correlations have been investigated between enzyme accessibility, hemicellulose removal rate, and cellulose crystallinity index. Both linear and nonlinear models were compared using five-parameter logic curve, four-parameter logic curve, and Deming regression. Hemicellulose removal was logically ascribed to be the trigger for cellulose saccharification efficiency during GA pretreatment of these waste straws.

Source identification of exhaust and non-exhaust traffic emissions through the elemental carbon fractions and Positive Matrix Factorization method

Our study implies the importance of exhaust and non-exhaust emissions in a highway road tunnel, which is crucial to assess their impacts on air quality, human health, climate and developing functional methods for controlling. The total suspended particulates (TSP) and road dust (RD) samples were collected by PUF samplers and manually sweeping, respectively. Campaigns were performed in the summer and winter of 2014 in a highway road tunnel in Bolu, Turkey. Chemical analyses were presented to characterize the contents of organic carbon (OC) fractions (OC1,2,3,4), elemental carbon (EC) fractions (EC1,2,3,4,5,6), polycyclic aromatic hydrocarbons (PAHs) and metals (Al, Ba, Ca, Cu, Mg, Mn, Pb, Sr, Cr and Fe) in the collected TSP and RD samples. Positive matrix factorization (PMF) and orthogonal (Deming) regression analysis were applied to find out the exhaust and non-exhaust vehicle emissions of metal and carbonaceous species in the tunnel. The results showed that the identified source profiles included resuspended road dust (43%), non-exhaust emissions (37%), diesel exhaust emissions (13%), and gasoline exhaust emissions (7%). The relationship between emission markers of metal species and EC carbon fractions was supported by correlation studies. Among these EC fractions, EC4 and EC2 were the most abundant fractions in aerosol and RD samples, respectively and so they highly represented the diesel and non-exhaust emissions. Besides, the EC1 fraction was the indicator of gasoline-fueled emissions. Lower EC1 and higher soot-EC contribution obtained in tunnel aerosol (AS) samples showed the dominance of diesel-fueled vehicles in the tunnel. The data represented herein would help to identify the characteristic of vehicle emissions.

Abstract 13362: Patient-centered Assessment Of Risk Of Stroke Vs. Bleeding In Patients With Atrial Fibrillation

Introduction: Clinicians use CHA 2 DS 2 -VASc to predict stroke at one year and HAS-BLED to predict bleeding at one year in patients with atrial fibrillation. However, the scores do not consider the fear of the two outcomes in the individual patient. Hypothesis: A new algorithm predicting the relative risk of stroke versus bleeding at one year implemented as a web application will classify individual patients with high degree of precision. Methods: Using the Myocardial Infarction Data Acquisition System (MIDAS) database, we developed an algorithm that considers the preferences of each individual patient as estimated from data from history in predicting the risk of bleeding or stroke from CHA 2 DS 2 -VASc and HAS-BLED. Given the patient demographics and comorbidities, the confidence intervals of predicted risks of the outcomes were first obtained by fitting a multinomial regression model. The estimates were fed into a Deming regression model to correlate the risks of the outcomes in subgroups of patients with similar risk factors. The line of best fit between the two outcomes represented the objective relationship between the outcomes. Each patient would state their fears of the outcomes on a 0 to 100 scale and adding up to 100, e.g. 20 vs. 80 for fear of stroke vs. fear of bleeding respectively. A prediction region around the line of best fit was then calculated based on the patient’s fears. Results: Based on the predicted risks of stroke and bleeding and the patient’s fears of bleeding, the algorithm produces a graph with two regions corresponding to whether the patient should be treated with anticoagulants. Thus, patients who feared stroke more than bleeding would be more likely to receive anticoagulation compared to a decision based on objective data. Conclusions: The algorithm shown in the figure and implemented as a web application helps clinicians make decisions on whether to prescribe anticoagulants or not based on objective data modified by individual patient preferences.

A novel, sensitive, and widely accessible besifloxacin quantification method by HPLC-fluorescence: Application to an ocular pharmacokinetic study

Besifloxacin has been embraced for the treatment of ocular bacterial infections. While LC-MS/MS has been used in investigating BSF pharmacokinetics, those costly instruments are not universally available and have complicated requirements for operation and maintenance.Additionally, pharmacokinetics of besifloxacin in dose-intense regimens are still unknown. Herein, a new quantification method was developed employing the widely accessible HPLC with fluorescence detection and applied to an ocular pharmacokinetic study with an intense regimen. Biosamples were pre-treated using protein precipitation. Chromatographic separation was achieved on a C18 column using mobile phase of 0.1% trifluoroacetic acid and acetonitrile. To address the weak fluorescence issue of besifloxacin, effects of detection parameters, elution pattern, pH of mobile phase, and reconstitution solvents were investigated. The method was fully validated per US-FDA guidelines and demonstrated precision (<13%), accuracy (91–112%), lower limit of quantification (5 ng/mL), linearity over clinically relevant concentrations (R2 > 0.999), matrix-effects (93–105%), recoveries (95–106%), and excellent selectivity. The method showed agreement with agar disk diffusion assays for in vitro screening and comparable in vivo performance to LC-MS/MS (Deming Regression, y = 1.010x + 0.123, r = 0.997; Bland-Altman analysis, mean difference was −6.3%; n = 21). Pharmacokinetic parameters suggested superior surface-retentive properties of besifloxacin. Maximum concentrations were 1412 ± 1910 and 0.15 ± 0.12 μg/mL; area under the curve was 1,637 and 1.08 µg·h/g; and half-life was 4.9 and 4.1 h; and pharmacokinetic-to-pharmacodynamic ratios were ≥ 409 and ≤ 17.8 against ocular pathogens in tears and aqueous humor, respectively. This readily available method is sensitive for biosamples and practical for routine use, facilitating besifloxacin therapy development.

The Variations of Insulin-like Growth Factor 1 Measured between Siemens Immulite, DiaSorin Liaison and IDS iSYS

Abstract Introduction/Objective Insulin-like Growth Factor 1 (IGF-1) is a biomarker for the evaluation of growth hormone activity in the hypothalamic-pituitary axis. The current most common methodology for IGF-1 measurement is automated immunometric assays. In this study, we compared the IGF-1 on Siemens Immulite 2000, DiaSorin Liaison XL and IDS iSYS. Methods/Case Report Residual 30-110 serum specimens were randomly selected from routine hospital orders. IGF- 1 was measured on these three platforms and compared with Passing-Bablok regression. Bias was evaluated using the Bland-Altman method. Results (if a Case Study enter NA) Weighted Deming regression analysis showed approximately 80% and 56% positive bias on IDS iSYS and DiaSorin Liaison, compared with Siemens Immulite (iSYS=1.81*Immulite-117.65, r=0.91; Liaison=1.56*Immulite-4.58, r=0.98). There was approximately 8% positive bias on Liaison, compared with iSYS (Liaison=1.08*iSYS+0.56, r=0.99). The Passing-Bablok regression analysis revealed approximately 67% and 54% positive bias (iSYS=1.67*Immulite-75, r=0.91; Liaison=1.54*Immulite-3.44, r=0.91). Approximately 8% positive bias on Liaison was observed, compared with iSYS (Liaison=1.08*iSYS+5.65, r=0.99). The Bland-Altman plot showed the agreement between iSYS and Immulite IGF-1 was on average 129.6±123.3 ng/mL, 98.6±148.8 ng/mL between Liaison and Immulite and 37.0±46.5 ng/mL between Liaison and iSYS. Conclusion Immunoassays rely on the specificity of antibodies. There are wide variations between different immunoassay platforms for IGF-1 measurement. The standardization of IGF-1 assay is lack. It would be a challenge for clinicians to monitor IGF-1 or treat the patients with pituitary disorders, when switching to another platform. The potential impact of the variations in IGF-1 measurement between different immunoassay platforms should be aware.

Performance Evaluation of the Quantitative Point-of-Care LumiraDx D-Dimer Test.

IntroductionFibrin degradation product d-dimer can be a valuable indicator for venous thromboembolism (VTE). The use of d-dimer testing in primary care settings can be limited by restricted access to laboratory services. This performance evaluation compares a quantitative, point-of-care (POC) d-dimer assay (LumiraDx d-Dimer Test) with a reference laboratory-based d-dimer assay.MethodsPlasma samples from patients presenting to secondary care in the UK, USA, and Germany were analyzed centrally using the LumiraDx d-Dimer Test and the reference test (bioMérieux VIDAS d-Dimer Exclusion II immunoassay). Method comparison used Passing–Bablok regression analysis with pre-specified equivalence criteria of r ≥ 0.9 and slope of 0.9–1.1. The NOVEL-3 study (NCT04375982) compared equivalency of fingerstick, venous blood (VB), and plasma samples from the same patient, tested at US primary care clinics next to the patient using the POC LumiraDx d-Dimer device. Measurements obtained from fingerstick and VB samples were compared with results from plasma samples, using Deming regression. The healthy reference range was determined using plasma samples of healthy volunteers, collected by commercial suppliers in Germany and the USA, which were analyzed centrally using the LumiraDx d-Dimer Test and the reference test.ResultsThe LumiraDx d-Dimer Test demonstrated agreement with the bioMérieux VIDAS d-Dimer Exclusion II immunoassay for plasma samples (r = 0.923, slope of 1.016, n = 1767). There was good agreement between fingerstick/VB samples and plasma samples (r = 0.980–0.986, n = 93) measured using the LumiraDx d-Dimer Test. Overall error rates were 1.8%. The healthy reference range 90% percentile for d-dimer was calculated as 533 µg/l fibrinogen equivalent units (FEU).ConclusionsThe quantitative LumiraDx d-Dimer Test is easy to use and can accurately measure d-dimer levels in a range of blood sample types, including fingerstick samples, which could improve assessment of VTE cases in community and hospital near-patient settings.

Body fat percentage estimation in children - searching for the most accurate equation.

Background and aims: Analysis of body composition is a very important issue, and it is often used as one of the crucial markers of overall health. The aim of the study was to analyse the relationship between the percentage of body fat ratio estimated using selected equations and adiposity obtained by bioimpedance in 7-16-year-olds from Kraków (Poland). Methods and results: The study included 1887 children and adolescents. Body weight and height were measured according to standard methods and Body Mass Index was calculated on the basis of those measurements. Biceps, triceps, subscapular, suprailiac, abdominal and calf skinfolds were measured. Adiposity was obtained using the BIA method as well as estimated by Siri, Goran, Slaughter, Deurenberg, Huang, Dezenberg, Ripka and Brożek equations. Relationship between results obtained from the equations and bioimpedance was assessed using Deming regression. All calculations were performed using Microsoft Excel and MedCalc. Statistically significant (p ≤ 0.001) relationship between adiposity obtained by bioimpedance and estimated was observed for all of the analysed equations. For girls, the strongest one was noted for Siri equation, with R = 0.83 (95%CI: 0.81-0.85). Among boys, the strongest relationship was observed for 3-skinfolds based equation developed by Ripka, with the Pearson's correlation coefficient value of 0.84 (95%CI: 0.81-0.85). Conclusions: The most useful equation to estimate the body fat percentage in the population of 7-16-year olds from Kraków (Poland) differed between the sexes. For boys, it was Ripka 3-skinfold equation, while for girls it was the equation developed by Siri.