ABSTRACT
Los autores realizan una revisión exhaustiva sobre la variación biológica, con el objeto de resaltar su aplicación práctica en la rutina diaria del laboratorio clínico. Se describe brevemente el método de estimación de los componentes de la variación biológica y se detalla la base de datos actualizada bianualmente y disponible para los profesionales del sector. Se pormenoriza el uso práctico en el control interno del proceso analítico, en la evaluación de los datos del control interno y externo, así como en la detección de errores analíticos y extraanalíticos. Finalmente, se explica con claridad cómo notificar la posibilidad de un cambio significativo en el estado de salud del paciente en el informe analítico (AU)
This is an exhaustive review on biological variation, which aims to highlight its practical application in daily routine of clinical laboratories. The methodology to estimate the components of biological variation is summarised and a database, which is updated every two years and available to professionals of the area, is explained in detail. Daily application of data derived from biological variation in daily practice in internal and external quality control, as well as, in the detection of analytical and non-analytical errors is clearly explained. Last, but not least, examples are given on how to notify to clinicians on possible changes in patients health status (AU)
Subject(s)
Humans , Male , Female , Reference Values , Clinical Laboratory Techniques/standards , Clinical Laboratory Techniques/trends , Clinical Laboratory Techniques , Biomarkers/analysis , Laboratory Equipment , Clinical Laboratory Information Systems/ethics , Clinical Laboratory Information Systems/organization & administration , Clinical Laboratory Information Systems/standards , Biomedical Technology/ethics , Biomedical Technology/methods , Biomedical Technology/standards , Laboratory Personnel/ethics , Laboratory Personnel/organization & administrationABSTRACT
Introducción. El modelo Seis Sigma es una herramienta de gestión de la calidad que se basa en la medida de la variabilidad de un proceso, en términos de desviación típica o de fallos por millón. Implica haber definido previamente una especificación de la calidad para el proceso que se investiga. Material y método. Este trabajo estudia los datos obtenidos en los programas de garantía externa de la calidad de la Sociedad Española de Bioquímica Clínica y Patología Molecular (SEQC), con el propósito de deducir consecuencias prácticas que aseguren el diagnóstico y el seguimiento correctos del paciente, mediante el informe aportado por el laboratorio. Se incluyen magnitudes biológicas con especificaciones de la calidad definidas para situaciones clínicas concretas (colesterol, glucosa, glucohemoglobina y antígeno prostático específico total) y con valores de variación biológica bajos (ión sodio, albúmina), intermedios (colesterol, creatinina, glucosa) y altos (hierro, triglicéridos). El valor sigma se calcula mediante el cociente entre el límite de tolerancia establecido y la variabilidad del proceso. Resultados. Los valores sigma obtenidos son adecuados (>=3) si se toman especificaciones muy permisivas, mientras que no lo son cuando se desea cumplir la especificación derivada de la variación biológica. Ello indica que los instrumentos y métodos analíticos disponibles en nuestro mercado requieren un procedimiento de control de la calidad muy cuidadoso (procesamiento de varias muestras control, necesidad de realizar repeticiones, etc.). Conclusiones. En ningún caso se debe confundir el objetivo de alcanzar la calidad necesaria para el adecuado uso clínico del informe analítico con el de conseguir un laboratorio industrialmente productivo; ambos forman parte del concepto de calidad total(AU)
Introduction. The Six Sigma model is a management tool based on measuring process variability, in terms of standard deviation or defects per million. It involves defining the specifications of the quality desired for the process investigated. Material and method. This work uses data obtained by the laboratories participating in the external surveys organized by the Spanish Society of Clinical Biochemistry and Molecular Pathology (SEQC), with the aim of promoting practical recommendations for assuring satisfactory patient diagnosis or monitoring through the laboratory report. The analytes included have quality specifications defined for specific clinical situations (cholesterol, glucose, HbA1C, total PSA) and have narrow (albumin, sodium), medium (cholesterol, creatinine, glucose) and wide (iron, triglyceride) biological variations. Results from control materials with the relevant concentrations to make clinical decisions have been used in this study. Sigma matrix is calculated from the ratio between quality specification and process coefficient of variation. Results. Results obtained show that sigma values are good (>=3) when using permissive quality specifications, whereas they are poor if quality specifications are derived from biological variation. This finding indicates that instruments and methods available in our field require a strict quality control procedure (several control samples per run, repeated tests, etc.). Conclusions. The objective of obtaining the quality required for adequate clinical use, must not be confused with that of achieving an economically productive laboratory; both are part of the concept of total quality management(AU)
Subject(s)
Humans , Male , Female , 25105/analysis , Biomedical Technology/methods , Clinical Laboratory Techniques/standards , Clinical Laboratory Techniques , Laboratories/standards , /methods , /organization & administration , /standards , Clinical Laboratory Techniques/trendsABSTRACT
Introducción. La variación biológica (VB) es la fluctuación fisiológica de los constituyentes de los fluidos humanos alrededor del punto homeostático, considerada de forma individual (CVI) o entre diferentes individuos. Los datos derivados de su estudio se usan como propuesta del valor de referencia de un cambio (VRC) entre resultados seriados de un mismo individuo. El VRC estimado a partir de individuos sanos se ha utilizado en el control de la evolución clínica de los pacientes con el fin de discriminar si se produce un cambio significativo en una serie de resultados analíticos. Objetivo. El objetivo del presente trabajo es revisar los datos de VB en situaciones patológicas para aplicarla al uso de la práctica clínica, especialmente en el seguimiento de pacientes. Material y método. El material usado en este estudio se recogió a partir de artículos referenciados en los buscadores electrónicos, libros y tesis doctorales. Se ha recopilado y ordenado alfabéticamente un total de 66 magnitudes biológicas en 34 situaciones patológicas. Resultados y conclusiones. Para la mayoría de las magnitudes estudiadas, los valores de CVI en estados patológicos son similares a los encontrados en individuos sanos. Sin embargo, para las magnitudes consideradas como marcadores específicos de órgano, los valores de CVI son muy diferentes (superiores o inferiores) a los obtenidos en personas sanas. Esto implica que los valores VRC procedentes de personas sanas pueden no ser adecuados para el seguimiento de los pacientes. Hay un riesgo de que se produzcan falsos positivos (o negativos) sobre cambios del estado de salud, con sus correspondientes implicaciones clínicas(AU)
Introduction. Biological variation (BV) refers to the natural fluctuation of a physiological constituent around the homeostatic set point within a person (CVI), as well as the natural variation between persons. The data derived from the components of BV are used to propose the reference change value (RCV) for monitoring patients. Objective. The aim of this review is to show the state of the art for biological variation data in non-healthy situations in order to have an indication of whether the data derived in specific pathological situations might be useful for clinical applications. Material and method. The information used in this study was retrieved from published articles referenced in electronic search systems, books and a doctoral thesis. The analytes studied were listed in alphabetical order. Results and conclusions. For the majority of quantities studied, CVI values are of the same order in disease and health: thus the use of RCV derived from healthy subjects for monitoring patients would be reasonable. However, for a small number of quantities considered to be disease specific markers, the CVI differed from those in health. This could mean that RCV derived from healthy CVI may not be appropriate for monitoring patients in certain diseases. Hence, disease specific RCV may be clinically useful(AU)
Subject(s)
Humans , Male , Female , Reference Values , Clinical Laboratory Techniques/methods , Clinical Laboratory Techniques , Clinical Laboratory Techniques/instrumentation , Clinical Laboratory Techniques , Models, Theoretical/methods , Analysis of VarianceABSTRACT
Quantitative data on the components of biological variation (BV) are used for several purposes, including calculating the reference change value (RCV) required for the assessment of the significance of changes in serial results in an individual. Pathology may modify the set point in diseased patients and, more importantly, the variation around that set-point. Our aim was to collate all published BV data in situations other than health. We report the within-subject coefficient of variation (CV(I)) for 66 quantities in 34 disease states. We compared the results with the CV(I) determined in healthy individuals and examined whether the data derived in specific diseases could be useful for clinical applications. For the majority of quantities studied, CV(I) values are of the same order in disease and health: thus the use of RCV derived from healthy subjects for monitoring patients would be reasonable. However, for a small number of quantities considered to be disease specific markers, the CV(I) differed from those in health. This could mean that RCV derived from healthy CV(I) may be inappropriate for monitoring patients in certain diseases. Hence, disease-specific RCVs may be clinically useful.
Subject(s)
Chemistry, Clinical/standards , Algorithms , Body Fluids/chemistry , Chemistry, Clinical/statistics & numerical data , Databases, Factual , Humans , Predictive Value of Tests , Quality Control , Reference ValuesABSTRACT
BACKGROUND: [corrected] Data on within- and between-subject biological variation are available for around 250 analytes commonly used in medical laboratories. METHODS: Integration of this data into the quality system occurs at all three levels of laboratory activity: (a) Preanalytic process: biological variation provides the basis for selecting the most appropriate specimen for analysis, for defining sample stability and for deciding suitable timing between samplings; (b) analytic process: biological variation-derived goals are fundamental for designing internal quality control procedures, and for evaluating laboratory performance; and (c) postanalytic process: delta checks based on within-subject biological variation values are used for validating results and for interpreting serial results from a patient. CONCLUSION: The biological variation is a pillar for managing quality in laboratory medicine.
