Kolmogorov-Smirnov Statistical Test Research Articles

Vector Autoregressive Model Using Non-Normal Copula Errors

This article focuses on a bivariate vector autoregressive model of lag 1 with non-normal errors. We propose a bivariate error distribution using two identical marginals through a copula function. The copula used for the study is the Farlie-Gumbel-Morgenstern copula, which is considered to be one of the efficient class of copula in describing the dependence between two random variables. The model parameters are estimated using the method of inference functions for margins, and the finite sample properties of the model is illustrated through simulation studies. A real life example is considered to illustrate the applications of the proposed model. The adequacy of the copula model is examined using the two sample version of kolmogorov smirnov test statistic.

Search for Optimal Parameters in the Control Structure of a Surgical System for Soft Tissue Operations Based on In Vitro Experiments on Cardiovascular Tissue

The surgical robots currently used in cardiac surgery are equipped with a remote center of motion (RCM) mechanism that enables the required spherical workspace. The dynamics model of the surgical robot’s RCM mechanism presented in this work includes a direct current (DC) motor, an optimal proportional–integral–derivative (PID) controller, and a LuGre friction model that takes into account the Stribeck effect and surface deformation. A finite element method (FEM) analysis of transients was carried out using the energy hypothesis of von Mises with an optimal input signal from the mechatronic system with a PID controller obtained using the Runge–Kutta differentiation method in the Dormand–Prince ordinary differential equations variant (ODE45). Five criteria were adopted for the objective function: the safety factor related to the stress function in the time-varying strength problem, the first natural frequency related to stiffness and the resonance phenomenon, the buckling coefficient in the statics problem related to stability, the static factor of safety, and the displacement of the operating tip. The force inputs to the dynamics model were derived from in vitro force measurements on cardiovascular tissue using a force sensor. The normality of the statistical distribution of the experimental data was confirmed using the Kolmogorov–Smirnov statistical test. The problem of multi-criteria optimization was solved using the non-sorter genetic algorithm (NSGA-II), the finite element method, and the von Mises distortion energy hypothesis. Velocity input signals for the transient dynamics model were obtained from a second in vitro experiment on cardiovascular tissue using the minimally robotic invasive surgery (MIRS) technique. An experienced cardiac surgeon conducted the experiment in a modern method using the Robin Heart Vision surgical robot, and a system of four complementary metal–oxide–semiconductor (CMOS) optical sensors and ariel performance analysis system (APAS-XP 2002) software were used to obtain the endoscopic tool trajectory signal. The trajectory signal was accurate to ±2 [mm] in relation to the adopted standard, and it was smoothed using the Savitzky–Golay (SG) polynomial smoothing, whose parameters were optimally selected using the Durbin–Watson (DW) statistical test.

Evaluation of the Effect of Educational Bureaucracy on School Administration: A Blunting School Climate for Teachers

This study aims to determine the relationship between School Climate, Organizational Commitment and Educational Bureaucracy (coercive & enabling) to examine it according to some variables. In the study, relational survey model, which is one of the quantitative research methods, was used. The data were collected from a total of 280 teachers working in public primary and secondary schools in Gebze during the 2022-2023 academic year. Statistical analysis of the data was carried out with SPSS 26.0. ANOVA and t-tests were applied to the items to test the effect of dependent variables. Kolmogorov-Smirnov test statistics were applied and it was found that the answers given by the participants showed homogeneous distribution (p>0.05). Skewness and Kurtosis values were evaluated to obtain normal distribution values. Based on the results, it was concluded that there is a negative, low and significant relationship between School Climate, Organizational Commitment and Coercive Bureaucracy. It was seen that there is a positive, moderate and significant relationship between School Climate, Organizational Commitment and Enabling Bureaucracy. In addition, significant differences were found between the answers given to the scale items according to teachers' gender, age, institution and field.

Automated Shape and Process Parameter Optimization for Scaling Up Geometrically Non-Similar Bioreactors

Scaling bioprocesses remains a major challenge. Since it is physically impossible to increase all process parameters equally, a suitable scale-up strategy must be selected for a successful bioprocess. One of the most widely used criteria when scaling up bioprocesses is the specific power input. However, this represents only an average value. This study aims to determine the Kolmogorov length scale distribution by means of computational fluid dynamics (CFD) and to use it as an alternative scale-up criterion for geometrically non-similar bioreactors for the first time. In order to obtain a comparable Kolmogorov length scale distribution, an automated geometry and process parameter optimization was carried out using the open-source tools OpenFOAM and DAKOTA. The Kolmogorov–Smirnov test statistic was used for optimization. A HEK293-F cell expansion (batch mode) from benchtop (Infors Minifors 2 with 4 L working volume) to pilot scale (D-DCU from Sartorius with 30 L working volume) was carried out. As a reference cultivation, the classical scale-up approach with constant specific power input (233 W m−3) was used, where a maximum viable cell density (VCDmax) of 5.02·106 cells mL−1 was achieved (VCDmax at laboratory scale 5.77·106 cells mL−1). Through the automated optimization of the stirrer geometry (three parameters), position and speed, comparable cultivation results were achieved as in the small scale with a maximum VCD of 5.60·106 cells mL−1. In addition, even on the pilot scale, cell aggregate size distribution was seen to strictly follow a geometric distribution and can be predicted with the help of CFD with the previously published correlation.

The influence of profitability, liquidity, and capital structure on firm value

This study aims to examine the influence of profitability, liquidity, and capital structure on the value of companies listed on the Indonesian Stock Exchange (IDX) during the period 2018-2021. The population used in this study were food and beverage sub-sector manufacturing companies listed on the IDX over the four-year period from 2018 to 2021, comprising 42 companies. The sample obtained was 17 manufacturing companies listed on the IDX during the 2018-2021 period. The research method used in this study is the quantitative method with multiple linear regression analysis tools, where quantitative data is a study method that is based on conjunctive data. This study uses descriptive statistical tests, Kolmogorov Smirnov statistical tests, multiple linear regression tests, and hypothesis testing with the help of the SPSS 23 program. The results of this study show that profitability partially has a positive and significant effect on the firm’s value, and the variables of liquidity and capital structure simultaneously have no effect on the firm’s value.

Awareness, attitudes towards plagiarism, and acceptance of using Turnitin in academic writings among undergraduate students

The purpose of this study was to examine the association of awareness of plagiarism, attitudes towards plagiarism and acceptance of using Turnitin among undergraduate students in a public university. The study was conducted on 143 undergraduate students at Universiti Teknologi MARA, Negeri Sembilan campus. Data was collected using an online questionnaire in the Google Form platform. These students took the Academic Writing subject. The ordinal data were collected using the 5-point Likert Scale. By studying the normality of the data using Kolmogorov-Smirnov and Shapiro-Wilk statistical tests, the association between awareness of plagiarism, attitudes towards plagiarism, and acceptance of using Turnitin, can be made. The tests compared the sample's scores to a normally distributed set of scores with the same mean and standard deviation. This paper presents the major findings from non-parametric correlations (Spearman’s rank-order and Kendall Tau-b) and suggests future research direction in increasing undergraduates’ awareness of plagiarism and awareness of using Turnitin when submitting their academic assignments. To curb plagiarism among undergraduates in an academic writing course, the authors propose a plagiarism policy within academic institutions, strict sanctions on plagiarism, and teach students how to avoid plagiarism and the use of Turnitin.

Pre- and Postnatal Determinants Shaping the Microbiome of the Newborn in the Opinion of Pregnant Women from Silesia (Poland).

Pre- and postnatal factors influence the formation of the newborn's microbiome as early as birth and the intrauterine period has a substantial impact on the composition of the baby's gastrointestinal microbiota and its subsequent development. This study intends to measure pregnant women's knowledge of the importance of microbiota for the health of the newborn. The sample was selected based on defined inclusion and exclusion criteria. The assessment of women's knowledge was assessed by the Kolmogorov-Smirnov and Kruskal-Wallis statistical tests. This study population comprised 291 adult pregnant women with a mean age of 28.4 ± 4.7 years. A total of 34% (n = 99), 35% (n = 101), and 31.3% (n = 91) were at the 1-3 trimester, respectively. The results showed that 36.4% of the women were aware that the intrauterine period changes the makeup of the gastrointestinal microbiota, whereas 5.8% exhibited awareness of the composition of the child's normal gut microbiota. Most of the women surveyed-(72.1%)-know that colonization of the tract occurs as early as the birth period. Women with student status (those who will pursue higher education in the future) and those who had given birth to the most children exhibited higher levels of knowledge.

Analytical chemistry kernel library for spectroscopic profiling data

The kernel is a powerful mathematical tool in spectroscopic profiling data analysis. This paper gives a theoretical and systematic formulation for various kernel types. An open-source Python toolkit (ackl, “analytical chemistry kernel library”) is developed accordingly. Highlights of the toolkit include: (1) It designs a unified API and implements totally 31 kernel types (e.g., linear, poly, Gaussian, Matern, Cauchy, Sorensen, wavelet, Fejér, etc.), which is by far the most comprehensive kernel library. (2) It provides a tailored hyper-parameter optimization mechanism for each kernel, which suits the spectroscopic profiling data properties. (3) It designs a set of 16 evaluation metrics (e.g., classification accuracy, F1 score, MANOVA test statistic, Kolmogorov-Smirnov test statistic, Cohen effect size, Fisher's discriminant ratio, computational cost, etc.) to compare different kernels in discriminative tasks. Finally, we conducted spectroscopic profiling case studies using this tool and summarized a general guideline for kernel selection.

Multiscale modeling of ammonia adsorption on zinc sulfate-doped activated carbon: Sensitivity analysis, parameter identification, and model validation

In this study four models are developed and validated to describe the dynamic adsorption of ammonia on zinc sulfate-doped activated carbon, ranging from simple single-scale to complex multiscale models. They are based on equations for mass balance, thermodynamics, hydrodynamics, and adsorption kinetics. Since the values of the parameters are needed for the implementation of the models, the doped activated carbon is characterized and ammonia isotherms measurements are performed at three different temperatures, i.e., 288, 303, and 313 K. A method based on parameter sensitivity analysis is used to evaluate the estimability of the unknown parameters of the Toth isotherm equation. Experimental breakthrough curves were then measured at various ammonia concentrations and gas flow rates. These curves were used to determine the overall mass transfer and axial dispersion coefficients, as well as the effective and intracrystalline diffusion, involved in the model equations. The models were implemented and solved using Comsol Multiphysics®. The study showed that the adsorption process was limited by the diffusion of ammonia and adsorption on the zinc sulfate crystal. The models were validated using breakthrough curves different from those used for parameter identification. The agreement between model predictions and measurements was evaluated using performance indices and confirmed by a Kolmogorov-Smirnov statistical test.

Processing speed test: Results from a Japanese normative sample of healthy participants compared with a US normative sample

BackgroundThe Processing Speed Test (PST), a validated iPad®-based cognitive screening test for MS, has been applied to the cognitive assessment of Japanese MS patients using US normative data. MethodsTo develop PST normative data from Japanese healthy volunteers and compare the PST score distribution between Japanese and US healthy volunteers, 254 healthy Japanese-speaking volunteers were enrolled and stratified by age (20–65 years). Potential participants with a Mini-Mental State Examination score < 27 were excluded. PST raw scores (total correct) were from the Japan cohort and compared with age-restricted US normative data and propensity score-matched data created by matching sex, age, and educational level from a published study of 428 healthy participants. PST score distributions and standardized z-scores were compared using t-test and Kolmogorov–Smirnov test statistics. ResultsThe mean age of the Japan cohort was 44.1 years. The PST scores of Japanese volunteers were significantly different from those of the age-restricted (mean ± SD 61.8 ± 10.1 vs 53.7 ± 10.8; p < 0.001) and the propensity score-matched US cohort (62.1 ± 10.1 vs 53.3 ± 10.6; p < 0.001). ConclusionRegression analyses centered on US normative data could underestimate disease severity in Japanese MS patients, suggesting that separate normative data should be considered for each population sample.

Maximum $$\log _q$$ likelihood estimation for parameters of Weibull distribution and properties: Monte Carlo simulation

The maximum $${\log }_q$$ likelihood estimation method is a generalization of the known maximum $$\log $$ likelihood method to overcome the problem for modeling non-identical observations (inliers and outliers). The parameter q is a tuning constant to manage the modeling capability. Weibull is a flexible and popular distribution for problems in engineering. In this study, this method is used to estimate the parameters of Weibull distribution when non-identical observations exist. Since the main idea is based on modeling capability of objective function $$\rho (x;\varvec{\theta })=\log _q\big [f(x;\varvec{\theta })\big ]$$ , we observe that the finiteness of score functions cannot play a role in the robust estimation for inliers. The properties of Weibull distribution are examined. In the numerical experiment, the parameters of Weibull distribution are estimated by $$\log _q$$ and its special form, $$\log $$ , likelihood methods if the different designs of contamination into underlying Weibull distribution are applied. The optimization is performed via genetic algorithm. The modeling competence of $$\rho (x;\varvec{\theta })$$ and insensitiveness to non-identical observations are observed by Monte Carlo simulation. The value of q can be chosen by use of the mean squared error in simulation and the p value of Kolmogorov–Smirnov test statistic used for evaluation of fitting competence. Thus, we can overcome the problem about determining of the value of q for real data sets.

Efficiency and effectiveness of global onshore wind energy utilization

The progress of onshore wind expansion varies globally, as often expressed by a country’s installed capacity and capacity factor. However, installed capacity and capacity factor do not allow conclusions about how effectively and efficiently countries use their spatially diverse wind potential. It is unknown how far wind energy expansion is and whether the countries use the available potential in the best possible way. Thus, this study aims to quantify and compare the wind potential use effectiveness and efficiency for the 40 countries with the highest installed capacity in 2021. A global wind turbine site dataset and the wind farm potential index were used for estimating the suitability of current wind turbine sites. The wind potential use efficiency was calculated by comparing the (1) distributions of the wind farm potential index at wind turbine sites with (2) distributions of the wind farm potential index of the countries as a whole by the Kolmogorov-Smirnov test statistic. The capacity-to-suitable-area ratio defined the wind potential use effectiveness. The results reveal that 81.9% of the global onshore wind turbine fleet operates at suitable sites. Simultaneous occurrences of high effectiveness and efficiency are not given in any country: China, Brazil, and Italy use their wind potential more efficiently than many other countries. The USA and India adequately consider the wind resource efficiency for wind turbine siting. Germany has the highest effectiveness despite low efficiency. The results reveal how critical it is to quantify the progress of wind energy expansion based on the effectiveness and efficiency, not only the installed capacity and capacity factor.

Uniform inference for value functions

We propose a method to conduct uniform inference for the (optimal) value function, that is, the function that results from optimizing an objective function marginally over one of its arguments. Marginal optimization is not Hadamard differentiable (that is, compactly differentiable) as a map between the spaces of objective and value functions, which is problematic because standard inference methods for nonlinear maps usually rely on Hadamard differentiability. However, we show that the map from objective function to an Lp functional of a value function, for 1≤p≤∞, are Hadamard directionally differentiable. As a result, we establish consistency and weak convergence of nonparametric plug-in estimates of Cramér–von Mises and Kolmogorov–Smirnov test statistics applied to value functions. For practical inference, we develop detailed resampling techniques that combine a bootstrap procedure with estimates of the directional derivatives. In addition, we establish local and uniform size control of one-sided tests which use the resampling procedure. Monte Carlo simulations assess the finite-sample properties of the proposed methods and show accurate empirical size and nontrivial power of the procedures. Finally, we apply our methods to the evaluation of a job training program using bounds for the distribution function of treatment effects.

Determining the Relationship between Stress Management and the Level of Perceived Job Stress and the Quality of Services Provided by Midwives Working in the Maternity Department of Hospitals in Hamedan Province in 2022

Background and Objective: One of the important problems of midwifery is high job stress and its consequences. Having the ability to manage stress is one of the basic requirements of this profession that can reduce midwifery mistakes in the workplace. Although job stress exists in all jobs, midwives face higher levels of stress due to the nature of their job, and this issue can lead to a decrease in service quality. The present study was conducted to determine the relationship of stress management with the level of perceived job stress and the quality of services provided by midwives working in the maternity department of hospitals in Hamedan province, Iran. Materials and Methods: The statistical population of this descriptive cross-sectional study consisted of 210 midwives working in hospitals with obstetrics and gynecology departments in Hamedan province. The random sampling method was used to select the samples. The required data for this study were collected using a demographic information form, Cobin's Stress Management Questionnaire, Hospital Stress Scale, and Maternity Care Quality in Maternity Unit Scale. Data were analyzed in Stata-13 software using Kolmogorov-Smirnov statistical tests and multivariate linear regression. The significance level was considered less than 0.05. Results: The findings showed that 81.4% of midwives had a high level of stress management ability. Moreover, 65.7% of midwives perceived moderate-level job stress, and 79% of midwives provided good quality services in the delivery room. Based on the results, was a moderate and inverse relationship between stress management and perceived job stress (beta=-0.47), and a moderate and direct relationship between stress management and the quality of provided services (beta=0.56). It was also found that perceived job stress had a weak and inverse relationship with the quality of provided services (beta=-0.25). Conclusion: The results revealed that having the ability to manage stress and control job stress could improve the quality of services provided by midwives. It is necessary for midwife managers to improve the process of providing quality services by holding stress management workshops.

The Effect of Aerobic Training and Octopamine Supplement on Gene Expression Levels of VEGF and PDGFR in the Heart Tissue of Rats Exposed to Deep Fried Oil

Background: Deep-fried oils (DFO) produce toxins that endanger people's health. Using herbal supplements along with exercise training can help improve health. The purpose of this study was to investigate the effect of aerobic training (T) and octopamine (O) supplementation on VEGF and PDGFR gene expression levels in the heart tissue of rats poisoned with DFO. Materials and Methods: In this experimental study, 25 male Wistar rats were purchased and placed in 5 groups of 5 animals, including: 1) control, 2) DFO, 3) DFO+T, 4) DFO+O and 5) DFO+T+O. Over a course of 4 weeks, rats in groups 2 to 5 received DFO by gavage, and rats in groups 3 and 5 ran on the treadmill 5 times a week with moderate intensity; also, rats in groups 4 and 5 received 81 μmol/kg octopamine supplement intraperitoneally 5 days a week. The Kolmogorov-Smirnov statistical test, independent samples t-test and two-way analysis of variance were used to analyze the research findings (p<0.05). Results: DFO had a significant effect on increasing the gene expression levels of VEGF (p=0.001) and PDGFR (p=0.002); training had a significant effect on the reduction of VEGF (p=0.001) and PDGFR (p=0.012); also, octopamine consumption had a significant effect on the reduction of VEGF (p=0.001) and PDGFR (p=0.045). Conclusion: It seems that aerobic training and octopamine consumption alone have anti-inflammatory effects in the heart tissue of DFO-poisoned rats, however they do not have significant anti-inflammatory interactive effects.

A mixed distribution to fix the threshold for Peak-Over-Threshold wave height estimation

Modelling extreme values distributions, such as wave height time series where the higher waves are much less frequent than the lower ones, has been tackled from the point of view of the Peak-Over-Threshold (POT) methodologies, where modelling is based on those values higher than a threshold. This threshold is usually predefined by the user, while the rest of values are ignored. In this paper, we propose a new method to estimate the distribution of the complete time series, including both extreme and regular values. This methodology assumes that extreme values time series can be modelled by a normal distribution in a combination of a uniform one. The resulting theoretical distribution is then used to fix the threshold for the POT methodology. The methodology is tested in nine real-world time series collected in the Gulf of Alaska, Puerto Rico and Gibraltar (Spain), which are provided by the National Data Buoy Center (USA) and Puertos del Estado (Spain). By using the Kolmogorov-Smirnov statistical test, the results confirm that the time series can be modelled with this type of mixed distribution. Based on this, the return values and the confidence intervals for wave height in different periods of time are also calculated.

47 Systemic lupus erythematosus in Tunisian children: a case series

BackgroundChildhood–onset systemic lupus erythematosus (c-SLE) is the prototype of a multisystemic, inflammatory, heterogeneous autoimmune condition, characterized by simultaneous or sequential organ involvement. Compared with the adult onset form, c-SLE is thought to have a worse prognosis.ObjectivesTo review the epidemiological, and bio-clinical, characteristics of a c-SLE case series.MethodsThe files of patients diagnosed as c-SLE in the pediatrics department of Monastir, Tunisia from January 2004 to March 2022 were reviewed. Mean and standard-deviations were used to express normally-distributed variables, as verified by the Kolmogorov-Smirnov statistical test.ResultsFourteen patients were collected. Female to male ratio was 6:1. Mean ages at lupus onset and diagnosis were 9.9 ± 1.4 years, [5–13.8 years] and 10.75 ± 2.3 years [6–14 years], respectively. Only two children had a family history of autoimmune disease.The initial admission was motivated primarily by skin and musculoskeletal manifestations, in 64.3% and 51.7% of cases, respectively. General signs (fever, asthenia) were observed in 35.7% of cases, hematological and gastrointestinal manifestations in 28.6% of cases each. In 3 cases, upper gastric endoscopy was performed prior to admission, in view of abdominal pain and vomiting.The physical examination noted various anomalies. Malar rash (50%) and discoid lupus (28.6%) were the most frequent cutaneous manifestations, while skin biopsy was performed in three cases, all favorable for lupus. The musculoskeletal manifestations comprised arthralgia (71.4%), arthritis and myositis (14.3% each). Hematological manifestations included thrombocytopenia and leukopenia in 4 cases each, as well as 3 cases of auto-immune hemolytic anaemia and splenomegaly. Renal manifestations were dominated by proteinuria in 7 cases, followed by hematuria in 6 cases, and 2 cases of hypertension (associated with renal failure in one case). The renal biopsy was performed in one case showed a stage-2 lupus nephritis. Pleural effusion was observed in 3 cases, 3 cases of pneumonia, 2 cases of pericarditis, one case of myo-pericarditis and one case of central nervous system (CNS) lupus.Relevant results of the laboratory workup are illustrated in the following table:47 Table 1Laboratory testPerformed (%)Abnormal results (%)Erythrocyte sedimentation rate14 (100%)13 (92%)Antinuclear anti-bodies14 (100%)13 (92%)AntiDNA antibodies7 (50%)5 (71%)AntiSm antibodies8 (57%)5 (62%)Antiphospholipid antibodies8 (57%)5 (62%)Complement11 (78%)9 (81%)The formal diagnosis of SLE was established according to the ACR-1997 criteria in 7 cases (50%), the SLICC-2012 in 4 cases (28.6%) and EULAR/ACR-2019 in 3 cases (21.4%). The c-SLE diagnosis was associated with coeliac disease and Hashimoto thyroiditis in one case each.The therapeutic management was based on corticosteroids in 11 cases, followed by hydroxychloroquine in 3 cases, while cyclophosphamides and immunoglobulin were used for one case each.The outcomes were heterogeneous. Among 11 patients with sufficient follow-up, 6 cases of remission and 2 cases of relapse were noted. Major adverse events were not infrequent: one case each of cardiac tamponade, macrophage activation syndrome and severe CNS lupus were observed, all fatal.ConclusionChildhood–onset systemic lupus is a challenging disease, both to diagnose and to treat. The development of new criteria of higher specificity and sensitivity has greatly helped identify the incomplete types of lupus and allow for early stage diagnosis, and therefore prevent the serious complications of the disease.

85 Systemic lupus erythematosus in Tunisian children: a case series

BackgroundChildhood–onset systemic lupus erythematosus (c-SLE) is the prototype of a multisystem, inflammatory, heterogeneous autoimmune condition, characterized by simultaneous or sequential organ involvement. Compared with the adult-onset form, c-SLE have a worse prognosis.ObjectivesTo review the epidemiological, and bio-clinical, characteristics of a c-SLE case series.MethodsThe files of patients diagnosed as c-SLE in the pediatrics department of Monastir, Tunisia from January 2004 to March 2022 were reviewed. Mean and standard-deviation were used to express normally-distributed variables, as verified by the Kolmogorov-Smirnov statistical test.ResultsFourteen patients were collected. Female to male ratio was 6:1. Mean ages at lupus onset and diagnosis were 9.9 ± 1.4 years, [5–13.8 years] and 10.75 ± 2.3 years [6–14 years], respectively. Only two children had a family history of autoimmune disease.The initial admission was motivated primarily by skin and musculoskeletal manifestations, in 64.3% and 51.7% of cases, respectively. General signs (fever, asthenia) were observed in 35.7% of cases, hematological and gastrointestinal manifestations in 28.6% of cases each. In 3 cases, upper gastric endoscopy was performed prior to admission, in view of abdominal pain and vomiting.The physical examination noted various abnormalities. Malar rash (50%) and discoid lupus (28.6%) were the most frequent cutaneous manifestations, while skin biopsy was performed in three cases, all in keeping with lupus. The musculoskeletal manifestations were arthralgia (71.4%), arthritis and myositis (14.3%). Hematological manifestations included thrombocytopenia and leukopenia in 4 cases, as well as 3 cases of auto-immune hemolytic anaemia and splenomegaly. Renal manifestations were proteinuria in 7, haematuria in 6, and hypertension in 2 (with renal failure in one of the patients). The renal biopsy that was performed in one subject showed a class 2 lupus nephritis. Pleural effusion was observed in 3, pneumonia in 3, pericarditis in 2, myo-pericarditis in 1 and central nervous system (CNS) lupus in 1.Relevant results of the laboratory workup are illustrated in the following table:85 Table 1Laboratory testPerformed (%)Abnormal results (%)Erythrocyte sedimentation rate14 (100%)13 (92%)Antinuclear anti-bodies14 (100%)13 (92%)AntiDNA antibodies7 (50%)5 (71%)AntiSm antibodies8 (57%)5 (62%)Antiphospholipid antibodies8 (57%)5 (62%)Complement11 (78%)9 (81%)The formal diagnosis of SLE was established according to the ACR-1997 criteria in 7 cases (50%), the SLICC-2012 in 4 cases (28.6%) and EULAR/ACR-2019 in 3 cases (21.4%). The c-SLE diagnosis was associated with coeliac disease and Hashimoto thyroiditis in two of the subjects respectively.The therapeutic management was based on corticosteroids in 11 cases, hydroxychloroquine in 3, while cyclophosphamides and immunoglobulin were used for two subjects respectively.The outcomes were heterogeneous. Among 11 patients with sufficient follow-up, 6 cases of remission and 2 cases of relapse were noted. Major adverse events were not infrequent: one case each of cardiac tamponade, macrophage activation syndrome and severe CNS lupus were observed, all fatal.ConclusionChildhood–onset systemic lupus is a challenging disease, both to diagnose and to treat. The development of new criteria of higher specificity and sensitivity has greatly helped identify the incomplete types of lupus and allow for early-stage diagnosis, therefore preventing the serious complications of the disease.

Process modeling radiation oncology clinic workflow from therapeutic simulation to treatment: Identifying impending strain and possible treatment delays.

39 Background: The administration of safe, high-quality radiotherapy requires the systematic completion of a series of steps from CT simulation, physician contouring, dosimetric treatment planning, pre-treatment quality assurance, plan verification, and ultimately treatment delivery. Nevertheless, due consideration to the cumulative time required to complete each of these steps is often not given sufficient attention when determining patient start date. On one hand, the nature of cancer therapy relies on timely treatment delivery. On the other hand, overly ambitious treatment turnaround times can lead to staff burnout, and result in medical errors. We sought to better understand how changes in patient volume could impact turnaround time through a simulation-based study. Methods: We developed a process model workflow for a single physician, single linear-accelerator clinic that simulated arrival rates and processing times for patients undergoing radiation treatment using AnyLogic Simulation Modeling software (AnyLogic 8 University edition, v8.7.9). We varied the new patient arrival rate from 1 to 10 patients per week to understand the impact treatment turnaround times from simulation to treatment. We utilized processing time estimates for each of the required steps as was determined in a departmental focus group study. We assumed an eight hour workday, and that contouring, treatment planning, verification, and treatment delivery followed the following distributions, respectively (in hours): triangular (2, 4, 16); triangular (8, 16, 60); triangular (0.25, 0.5, 1). Results: Altering the number of patients simulated per week from 1-10 patients resulted in a corresponding increase average processing time from simulation to treatment from 4 to 7 days. The maximum processing time for patient from simulation to treatment ranged from 6-14 days. To compare individual distributions, we utilized the Kolmogorov-Smirnov (K-S) statistical test. We found that altering the arrival rate from 4 patients per week to 5 patients per week resulted in a statistically significant change in the distributions of processing times (p = 0.03) and resulted in a corresponding increase in the maximum patient processing time from approximately 6 days to 12 days, or from approximately 1 week to 2 weeks. Conclusions: The results of this simulation-based modeling study confirm the appropriateness of current staffing levels to ensure timely patient delivery while minimizing staff burnout. However, sustained increases in volume could require increased staffing to ensure timely treatment delivery while minimizing staff burnout. Simulation modeling can help guide staffing and workflow models to ensure timely treatment delivery.

Optimal method for determining the intraclass correlation coefficients of urinary biomarkers such as dialkylphosphates from imputed data

Urinary biomarkers are commonly used in epidemiological studies as surrogates or indicators of exposure to chemical substances. Evaluating the reliability of a biomarker is highly important because use of an unreliable marker may lead to misclassification and attenuation bias, resulting in flawed interpretations and conclusions. Although intraclass correlation coefficient (ICC) is regarded as a typical index of test reliability, methods for determining the ICCs of urinary biomarkers have not been standardised, and different methods have been used. This study evaluated different imputation methods for left-censored data, i.e., four imputation or one substitution methods, before calculating ICCs, and at the same time mathematically assessed the impact of the left-censoring proportion on the estimated ICCs. Biomarkers of exposure to organophosphate pesticides, i.e., dialkylphosphates, were used as an example. The Gibbs sampler-based left-censored missing value imputation approach had the best performance for imputation of values below reporting limits, with lower values on Kolmogorov–Smirnov test statistics than other imputation/substitution methods, i.e., a univariate distribution fitting approach, multiple imputation by chained equation, a bootstrap expectation–maximisation algorithm approach, and a single value substitution. In all imputation methods, however, ICCs decreased as censoring rates increased. We propose a method to estimate true ICCs based on mathematical estimation.