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Related Concept Videos

Data Validation01:15

Data Validation

Method validation is a crucial process in analytical chemistry designed to confirm that a given method consistently produces reliable and high-quality results. This process is essential when a method is applied to different sample matrices or when procedural modifications are made, ensuring that the results meet acceptable standards across various applications.
Key parameters for method validation include:
Controlled-Current Coulometry: Coulometric Titration01:18

Controlled-Current Coulometry: Coulometric Titration

Coulometric titrations are a form of titrimetric analysis where the reagent is generated electrically, and its amount is evaluated based on current and generating time. The electron serves as the standard reagent. The procedure is similar to conventional titrations, such as endpoint detection.
The fundamental requirements for coulometric titrations are (1) 100% efficiency in the reagent-generating electrode reaction and (2) a stoichiometric and preferably rapid reaction between the generated...
Controlled-Current Coulometry: Overview01:27

Controlled-Current Coulometry: Overview

Controlled current coulometry, also known as amperostatic coulometry, is a technique used in electrochemical analysis to measure the quantity of a substance through the controlled passage of current. It involves the application of a constant current to an electrochemical cell containing the analyte of interest. As the current flows through the cell, the analyte undergoes a redox reaction at the electrode surface, resulting in a charge transfer. By monitoring the time required for a certain...
Quality Control01:05

Quality Control

Quality control is one of the three cyclical quality assurance activities that help keep a system under statistical control. Typical quality control activities include creating quality control charts, conducting proficiency testing, and documenting and archiving results.
Quality control helps track data, visualize trends, and identify variations, making it easier to detect deviations that may affect the accuracy of an analysis. One way to do this is by generating a quality control chart, which...
Pharmaceutical Alternatives: Excipients and Impurities-Related Therapeutic Nonequivalence01:19

Pharmaceutical Alternatives: Excipients and Impurities-Related Therapeutic Nonequivalence

Pharmaceutical products contain more than just the active drug; they also contain various excipients such as binders, solubilizers, stabilizers, preservatives, and other elements. In some cases, impurities or contaminants might be present. Traditionally, quality control in pharmaceuticals has primarily focused on the analysis of the active drug, often overlooking the impact of these additional components. The recent issue with heparin contamination by over-sulfated chondroitin sulfate, a...
Contaminants and Errors01:16

Contaminants and Errors

Effective sample preparation is crucial for accurate and reliable laboratory analysis. During this process, two significant sources of error can arise: concentration bias from improper sample splitting and contamination caused by methods used to reduce particle size, such as grinding or homogenization. Identifying and minimizing these potential errors is crucial to ensuring the validity of the analysis.
Another key consideration is determining the appropriate number of samples required to...

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Commutability limitations influence quality control results with different reagent lots.

W Greg Miller1, Aybala Erek, Tina D Cunningham

  • 1Department of Pathology, Virginia Commonwealth University, Richmond, VA, USA. gmiller@vcu.edu

Clinical Chemistry
|November 25, 2010
PubMed
Summary

Quality control (QC) materials often yield noncommutable results compared to patient samples during reagent lot changes. This frequent issue prevents QC data from reliably verifying patient sample result consistency between reagent lots.

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Area of Science:

  • Clinical Chemistry
  • Laboratory Medicine
  • Quality Assurance

Background:

  • Good laboratory practice mandates verifying new reagent lots before use.
  • Noncommutable quality control (QC) samples may hinder verification of patient sample result consistency across reagent lots.

Purpose of the Study:

  • To assess the commutability of QC samples with patient samples during reagent lot verification.
  • To determine if QC data accurately reflects patient sample behavior across different reagent lots.

Main Methods:

  • Analyzed 1483 reagent lot change-QC events across 82 analytes and 7 instrument platforms.
  • Used a modified 2-sample t test to compare differences between QC and patient sample results for reagent lot changes.

Main Results:

  • 40.9% of reagent lot change-QC events showed significant differences between QC and patient sample results (P < 0.05).
  • Even QC results within 1.0 SD interval (83.1% of total) showed significant differences in 37.7% of cases.
  • QC results with larger differences (≥1.0 SD) were significantly different from patient samples in 57.0% of cases.

Conclusions:

  • Noncommutable results for QC materials are frequent during reagent lot changes.
  • QC data cannot reliably verify the consistency of patient sample results when changing reagent lots.