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Articles de revues sur le sujet « Levey- Jennings Chart »

Auteur : Grafiati

Publié le 2 juin 2025

Mis à jour le 31 juillet 2025

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1

Sufinah Dahari. "Modified Levey-Jennings Chart with Robust Estimator: A Case of Semiconductor Manufacturing Process." Journal of Advanced Research in Applied Sciences and Engineering Technology 43, no. 2 (2024): 189–202. http://dx.doi.org/10.37934/araset.43.2.189202.

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In the era of Industrial Revolution 4.0 and smart manufacturing, the development and deployment of control charts used in the semiconductor industry need to be automated. Consequently, artificial intelligence-based automation methods typically encompass the deployment of statistical software such as JMP. Automation involves frequent dataset updates; the control limits are recalculated as the parameters change (non-stationary behaviour). This requires the user to define the control chart type before its deployment on the production floor. An initially normally distributed dataset may be skewed

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Alwan, L. C., and M. G. Bissell. "Time series modeling for quality control in clinical chemistry." Clinical Chemistry 34, no. 7 (1988): 1396–406. http://dx.doi.org/10.1093/clinchem/34.7.1396.

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Abstract Autocorrelation of clinical chemistry quality-control (Q/C) measurements causes one of the basic assumptions underlying the use of Levey-Jennings control charts to be violated and performance to be degraded. This is the requirement that the observations be statistically independent. We present a proposal for a new approach to statistical quality control that removes this difficulty. We propose to replace the current single control chart of raw Q/C data with two charts: (a) a common cause chart, representing a Box-Jenkins ARIMA time-series model of any underlying persisting nonrandomne

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Rahmani, Afina Rusyda, Arifiani Agustin Amalia, and Dhiah Novalina. "Analisis Quality Control (QC) Pemeriksaan Albumin Dan Bilirubin Menggunakan Kontrol Harian Dan Matriks Sigma." Borneo Journal of Medical Laboratory Technology 7, no. 1 (2024): 481–89. https://doi.org/10.33084/bjmlt.v7i1.7863.

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Quality control (QC) merupakan suatu proses evaluasi pengujian mutu laboratorium yang bertujuan untuk menjamin sistem mutu laboratorium. Six sigma merupakan indikator kualitas yang digunakan untuk mengevaluasi kinerja analitik. Penelitian ini bertujuan untuk mengetahui nilai data kontrol harian melalui evaluasi grafik Levey-jennings dan mengetahui nilai sigma beserta DPMO pada pemeriksaan albumin dan bilirubin total. Metode penelitian yang digunakan yaitu metode deskriptif kuantitatif dengan pendekatan penelitian cross sectional. Metode pengambilan sampel pada penelitian ini menggunakan Teknik

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J, Nadaf Sameer, and Suresh G. Killedar. "Method Development and Validation for Estimation of Curcumin in Fabricated Nano-Sized Formulation: Inter-Laboratory Comparison, Capability and Statistical Analysis." Pharmaceutical Methods 9, no. 2 (2018): 8. https://doi.org/10.5281/zenodo.14586239.

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Objective: Current work was designed to develop a simple, rapid, and cost effective spectrophotometric method for the determination of curcumin in fabricated and marketed nano-sized formulation. Method: Methanol was optimized as solvent and further spectrophotometric detection was carried at analytical wavelength i.e. 421 nm. Method was further validated as per International conference on Harmonisation (ICH) guidelines for linearity, specificity, accuracy, precision; ruggedness and robustness. Results: The concentration of curcumin over range of 1-10 µg/ml obeys Beers law with a correlat

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Yudita, Ferina, Dwi Purbayanti, Fitria Hariati Ramdhani, and Eka Jaya. "Evaluasi Kontrol Kualitas Pemeriksaan Glukosa Darah di Laboratorium X Palangka Raya." Borneo Journal of Medical Laboratory Technology 5, no. 2 (2023): 358–65. http://dx.doi.org/10.33084/bjmlt.v5i2.5184.

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Quality Control is a managerial procedure to adjust the laboratory examination (analytic) stages and detect errors early. The purpose of this study was to describe the quality control in laboratory X in the city of Palangka Raya. The method used is the descriptive method. The results showed that in April 2022, the Mean (88,1 mg/dL), SD (1,09 mg/dL), CV (1,24%), d (0,14%), TE (2,62%), TEa (10%), Sigma (7,94), and in May 2022 the Mean (87,9 mg/dL), SD (1,00 mg/dL), CV (1,13%), d (0,04%), TE (2,31%), TEa (10%), Sigma (8,79). According to the Ministry of Health, the maximum CV value is < 5%, so

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Asinas, J. M. "Applying The Best Practice For Internal Quality Control (IQC) Management, Consolidation And Review Process In Sidra Medicine Clinical Chemistry Division." American Journal of Clinical Pathology 154, Supplement_1 (2020): S91. http://dx.doi.org/10.1093/ajcp/aqaa161.199.

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Abstract Introduction/Objective The management of internal quality control (IQC) in Sidra Medicine Clinical Chemistry Division has been evaluated in order to promote a more consolidated and efficient process of IQC management. The statistical data produced from Cerner QC Module are transferred to IQC review templates consisting of formulas to auto- calculate parameters such as multiple of expected QC failure frequency and desirable comparison limit between analyzers. The IQC review and documentation process using the in-house excel template requires several hours to complete, hence a faster an

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Sharma, D. "Use of the microsoft excel for automated plotting of Levey Jennings charts." Indian Journal of Medical Microbiology 29, no. 4 (2011): 454. http://dx.doi.org/10.4103/0255-0857.90201.

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Anastasiou, A. P., and E. Psarouli. "P.3.8 RADIOIMMUNOASSAY QUALITY CONTROL PROTOCOLS: QUESTIONING THE NECESSITY OF LEVEY JENNINGS AND CUSUM CHARTS." Physica Medica 127 (November 2024): 104658. http://dx.doi.org/10.1016/j.ejmp.2024.104658.

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Khatri, Roshan, Sanjay KC, Prabodh Shrestha, and J. N. Sinha. "Implementing Self Sustained Quality Control Procedures in a Clinical Laboratory." Journal of Nepal Medical Association 52, no. 189 (2013): 233–37. http://dx.doi.org/10.31729/jnma.560.

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Introduction: Quality control is an essential component in every clinical laboratory which maintains the excellence of laboratory standards, supplementing to proper disease diagnosis, patient care and resulting in overall strengthening of health care system. Numerous quality control schemes are available, with combinations of procedures, most of which are tedious, time consuming and can be “too technical” whereas commercially available quality control materials can be expensive especially for laboratories in developing nations like Nepal. Here, we present a procedure performed at our centre wi

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Kamieniecki, E., and N. Brown. "P116 An R program for automatic quality control of single antigen bead assays via Levey-Jennings charts." Human Immunology 84 (September 2023): 72–73. http://dx.doi.org/10.1016/j.humimm.2023.08.018.

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Sabrina Belmahi, Abdessamad Amrani, Oumaima Nassiri, Amjad Idrissi, El-houcine Sebbar, and Mohammed Choukri. "Verification of the analytical performance of the urinary creatinine assay on Abbott Architect ci8200." Open Access Research Journal of Biology and Pharmacy 13, no. 1 (2025): 001–5. https://doi.org/10.53022/oarjbp.2025.13.1.0042.

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The urinary creatinine assay is a pivotal diagnostic tool for assessing kidney function, hydration status, and muscle metabolism. This study evaluated the analytical performance of the urinary creatinine assay method using an Abbott kit on the Architect ci8200® automated system in the biochemistry laboratory of CHU Mohammed VI, Oujda. Method verification was conducted in two phases: intermediate fidelity testing using internal quality controls and repeatability testing on patient urine samples across low and high creatinine concentration levels. The results demonstrated excellent analytical pe

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Gomes, Gabriel Thé Araújo. "Quality Control in RT-PCR Viral Load Assays: Evaluation of Analytical Performance for HIV, HBV, and HCV." Electronic Journal of the International Federation of Clinical Chemistry and Laboratory Medicine 35, no. 2 (2024): 91–99. https://doi.org/10.5281/zenodo.15538167.

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IntroductionQuality Control Management (QCM) in clinical laboratoriesis crucial for ensuring reliable results in analyticalmeasurements, with biological variation being a key factor.The study focuses on assessing the analytical performance ofthe Reverse Transcription Polymerase Chain Reaction (RTPCR)system for Human Immunodeficiency Virus (HIV),Hepatitis B (HBV), and Hepatitis C (HCV). Five modelsproposed between 1999 and 2014 offer different approachesto evaluating analytical quality, with Model 2 based onbiological variation and Model 5 considering the currentstate of the art. The study eval

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Gruber, Lorenz, Artur Hausch, and Thomas Mueller. "Internal Quality Controls in the Medical Laboratory: A Narrative Review of the Basic Principles of an Appropriate Quality Control Plan." Diagnostics 14, no. 19 (2024): 2223. http://dx.doi.org/10.3390/diagnostics14192223.

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To ensure the quality of their analyses, medical laboratories carry out internal quality control (IQC) on a daily basis. IQC involves control samples with known target values for all parameters used by a laboratory in clinical practice. The use of IQC enables the laboratory to monitor the accuracy and precision of laboratory results. The use of appropriate IQC strategies has been accepted in medical laboratories for decades, and IQC has been included in international recommendations and guidelines. The term “IQC strategy” (also termed a quality control plan) refers to the types of IQC material

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Putri, Oktavia Amanda, Woro Umi Ratih, and Monika Putri Solikah. "Quality Control Inspection Results Platelets and Leukocytes Based on the Westgard Rule and Six Sigma at Rs Pku Muhammadiyah Bantul." Journal of Social Science 5, no. 4 (2024): 1159–67. http://dx.doi.org/10.46799/jss.v5i4.882.

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Internal Quality Consolidation (PMI) is a preventive and monitoring activity carried out by each laboratory continuously so that errors or deviations do not occur so that correct inspection results are obtained, one of which is carrying out quality control (QC) using the Westgard Rule and Six Sigma . The Westgard rule is used to see whether there are analytical errors that occur with the 12 S , 13 S , 22 S , R4 S , 41 S , 10 X series of rules . Six sigma is used to assess the quality of a laboratory's performance by looking at the minimum sigma value level with a value of 3σ and a maximum of ≥

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Kruk, Tamara, Sam Ratnam, Jutta Preiksaitis, et al. "Results of Continuous Monitoring of the Performance of Rubella Virus IgG and Hepatitis B Virus Surface Antibody Assays Using Trueness Controls in a Multicenter Trial." Clinical and Vaccine Immunology 19, no. 10 (2012): 1624–32. http://dx.doi.org/10.1128/cvi.00294-12.

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ABSTRACTWe conducted a multicenter trial in Canada to assess the value of using trueness controls (TC) for rubella virus IgG and hepatitis B virus surface antibody (anti-HBs) serology to determine test performance across laboratories over time. TC were obtained from a single source with known international units. Seven laboratories using different test systems and kit lots included the TC in routine assay runs of the analytes. TC measurements of 1,095 rubella virus IgG and 1,195 anti-HBs runs were plotted on Levey-Jennings control charts for individual laboratories and analyzed using a multiru

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Peng, Peiyi, Xuehong Peng, Xiaoyang Jiao, and Nuan Chen. "A unique Levey–Jennings control chart used for internal quality control in human papillomavirus detection." Virology Journal 19, no. 1 (2022). http://dx.doi.org/10.1186/s12985-022-01861-8.

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Abstract Objective The purpose of this study was to provide an updated estimate of the prevalences of different types of human papillomavirus (HPV) in females in Chaoshan District and to establish an internal quality control (IQC) method for excluding false-positive results in HPV detection by using the Levey–Jennings control chart. Method HPV types were detected in 23,762 cervical samples by using PCR membrane hybridization. The means and standard deviations (SDs) of the positive rates were calculated, the Levey–Jennings chart was plotted, and the rules for “out of control” and “warning” were

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Demosthenes, John Paul, Ben Chirag Ghale, Diviya Alex, et al. "Challenges and pragmatic solutions for assessing the reliability of HIV-1 viral load monitoring in resource-constrained settings." Intervirology, November 26, 2023. http://dx.doi.org/10.1159/000535064.

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Introduction: HIV-1 RNA detection is the most reliable method for monitoring treatment response among people living with HIV (PLHIV). Effective quality control measures that include internal quality control (IQC) are challenging in resource-constrained settings. Methods: We ascertained the utility of the assay low positive control (LPC) as an effective internal quality control (IQC) to monitor the reliability of the HIV-1 viral load assay. Variations in LPC values were measured for 390 different runs over ten years (2011-2021) and compared to in-house IQC data using Levey-Jennings control char

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Li, Houli, Di Zhang, Xiaoliang Cheng, et al. "Application of the Westgard Multi-Rule Theory to Internal Quality Control Evaluation of Voriconazole for Therapeutic Drug Monitoring." Current Pharmaceutical Analysis 16 (August 18, 2020). http://dx.doi.org/10.2174/1573412916999200818104337.

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Background: There is no worldwide recognized reference internal quality control method for therapeutic drug monitoring (TDM) of voriconazole (VCZ) by liquid chromatography (LC). In this study, we aimed to develop an internal quality control method for TDM of VCZ, evaluate it by the Westgard Multi-rule Theory, and guarantee the analytical quality of the assays. Method: The plasma concentration of VCZ was detected by two-dimensional liquid chromatography with ultraviolet detection (2D-LC-UV) method. The internal quality control results accompanying with TDM of VCZ in our laboratory from July 201

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Coskun, Abdurrahman. "Modified Levey-Jennings charts for calculated laboratory tests." Clinical Chemistry and Laboratory Medicine (CCLM) 44, no. 4 (2006). http://dx.doi.org/10.1515/cclm.2006.066.

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Weng, Binghuan, Ya-li Xu, Jun Ying, et al. "A novel use for Levey-Jennings charts in prenatal molecular diagnosis." BMC Medical Genomics 13, no. 1 (2020). http://dx.doi.org/10.1186/s12920-020-00758-1.

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Çubukçu, Hikmet Can. "QC Constellation: a cutting-edge solution for risk and patient-based quality control in clinical laboratories." Clinical Chemistry and Laboratory Medicine (CCLM), May 31, 2024. http://dx.doi.org/10.1515/cclm-2024-0156.

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Abstract Objectives Clinical laboratories face limitations in implementing advanced quality control (QC) methods with existing systems. This study aimed to develop a web-based application to addresses this gap, and improve QC practices. Methods QC Constellation, a web application built using Python 3.11, integrates various statistical QC modules. These include Levey-Jennings charts with Westgard rules, sigma-metric calculations, exponentially weighted moving average (EWMA) and cumulative sum (CUSUM) charts, and method decision charts. Additionally, it offers a risk-based QC section and a patie

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Giannoli, Jean-Marc, Mathieu Bernard, Julien L’Hirondel, André Heim, and Tony Badrick. "A model for managing quality control for a network of clinical chemistry instruments measuring the same analyte." Clinical Chemistry and Laboratory Medicine (CCLM), November 24, 2023. http://dx.doi.org/10.1515/cclm-2023-0965.

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Abstract Objectives Monitoring quality control for a laboratory or network with multiple instruments measuring the same analyte is challenging. We present a retrospective assessment of a method to detect medically significant out-of-control error conditions across a group of instruments measuring the same analyte. The purpose of the model was to ensure that results from any of several instruments measuring the same analytes in a laboratory or a network of laboratories provide comparable results and reduce patient risk. Limited literature has described how to manage QC in these very common situ

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Vincini, G., and W. Dimech. "A-245 Reagent Lot Variation—When should I be Concerned?" Clinical Chemistry 69, Supplement_1 (2023). http://dx.doi.org/10.1093/clinchem/hvad097.217.

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Abstract Background Reagent lot variation is often considered a major source of concern for infectious disease serology testing. Regular review of quality control testing data for specific assays confirms that, when using traditional statistical methods, such as using small datasets to establish mean/SD and then applying Westgard rules, reagent lot variation is the most common cause of variation observed. To investigate every incident is time consuming, costly and likely unnecessary in the majority of cases. But how do we create an alternative to monitoring QC data that accepts normal reagent

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