Literature DB >> 27506603

Criteria for assigning laboratory measurands to models for analytical performance specifications defined in the 1st EFLM Strategic Conference.

Ferruccio Ceriotti, Pilar Fernandez-Calle, George G Klee, Gunnar Nordin, Sverre Sandberg, Thomas Streichert, Joan-Lluis Vives-Corrons, Mauro Panteghini.   

Abstract

This paper, prepared by the EFLM Task and Finish Group on Allocation of laboratory tests to different models for performance specifications (TFG-DM), is dealing with criteria for allocating measurands to the different models for analytical performance specifications (APS) recognized in the 1st EFLM Strategic Conference Consensus Statement. Model 1, based on the effect of APS on clinical outcome, is the model of choice for measurands that have a central role in the decision-making of a specific disease or clinical situation and where cut-off/decision limits are established for either diagnosing, screening or monitoring. Total cholesterol, glucose, HbA1c, serum albumin and cardiac troponins represent practical examples. Model 2 is based on components of biological variation and should be applied to measurands that do not have a central role in a specific disease or clinical situation, but where the concentration of the measurand is in a steady state. This is best achieved for measurands under strict homeostatic control in order to preserve their concentrations in the body fluid of interest, but it can also be applied to other measurands that are in a steady state in biological fluids. In this case, it is expected that the "noise" produced by the measurement procedure will not significantly alter the signal provided by the concentration of the measurand. This model especially applies to electrolytes and minerals in blood plasma (sodium, potassium, chloride, bicarbonate, calcium, magnesium, inorganic phosphate) and to creatinine, cystatin C, uric acid and total protein in plasma. Model 3, based on state-of-the-art of the measurement, should be used for all the measurands that cannot be included in models 1 or 2.

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Year:  2017        PMID: 27506603     DOI: 10.1515/cclm-2016-0091

Source DB:  PubMed          Journal:  Clin Chem Lab Med        ISSN: 1434-6621            Impact factor:   3.694


  11 in total

Review 1.  Toward a Framework for Outcome-Based Analytical Performance Specifications: A Methodology Review of Indirect Methods for Evaluating the Impact of Measurement Uncertainty on Clinical Outcomes.

Authors:  Alison F Smith; Bethany Shinkins; Peter S Hall; Claire T Hulme; Mike P Messenger
Journal:  Clin Chem       Date:  2019-08-23       Impact factor: 8.327

2.  Analysis of current status of quantitative detection of biomarkers for liver fibrosis in Clinical labs in China.

Authors:  Chao Zhang; Chuanbao Zhang
Journal:  J Clin Lab Anal       Date:  2022-05-19       Impact factor: 3.124

3.  EQA/PT scheme to improve the equivalence of enzymatic results between mutual recognition laboratories in Beijing.

Authors:  Qing Tong; Shunli Zhang; Chang Zuo
Journal:  J Clin Lab Anal       Date:  2021-05-05       Impact factor: 2.352

Review 4.  Minimum requirements for the estimation of measurement uncertainty: Recommendations of the joint Working group for uncertainty of measurement of the CSMBLM and CCMB.

Authors:  Ivana Ćelap; Ines Vukasović; Gordana Juričić; Ana-Maria Šimundić
Journal:  Biochem Med (Zagreb)       Date:  2017-10-15       Impact factor: 2.313

5.  Patient posture for blood collection by venipuncture: recall for standardization after 28 years.

Authors:  Gabriel Lima-Oliveira; Gian Cesare Guidi; Gian Luca Salvagno; Elisa Danese; Martina Montagnana; Giuseppe Lippi
Journal:  Rev Bras Hematol Hemoter       Date:  2017-02-22

6.  Implementation of biological variation-based analytical performance specifications in the laboratory: Stringent evaluation of Improvacutor blood collection tubes.

Authors:  Hee-Jung Chung; Yoon Kyung Song; Sung Kuk Hong; Sang-Hyun Hwang; Hee Seung Seo; Dong Hee Whang; Myung-Hyun Nam; Do Hoon Lee
Journal:  PLoS One       Date:  2017-12-20       Impact factor: 3.240

7.  Proposed Imprecision Quality Goals for Urinary Albumin/Creatinine Ratio.

Authors:  Dae Hyun Ko; Sung Woo Lee; Jungwon Hyun; Hyun Soo Kim; Min Jeong Park; Dong Hoon Shin
Journal:  Ann Lab Med       Date:  2018-09       Impact factor: 3.464

Review 8.  Analytical Sigma metrics: A review of Six Sigma implementation tools for medical laboratories.

Authors:  Sten Westgard; Hassan Bayat; James O Westgard
Journal:  Biochem Med (Zagreb)       Date:  2018-06-15       Impact factor: 2.313

9.  Analytical Performance Specifications for 25-Hydroxyvitamin D Examinations.

Authors:  Etienne Cavalier; Callum G Fraser; Harjit P Bhattoa; Annemieke C Heijboer; Konstantinos Makris; Candice Z Ulmer; Hubert W Vesper; Samuel Vasikaran; Pierre Lukas; Pierre Delanaye; Anna Carobene
Journal:  Nutrients       Date:  2021-01-28       Impact factor: 5.717

10.  Internal Quality Control Data of Urine Reagent Strip Tests and Derivation of Control Rules Based on Sigma Metrics.

Authors:  Haeil Park; Younsuk Ko
Journal:  Ann Lab Med       Date:  2021-09-01       Impact factor: 3.464

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