Literature DB >> 2679660

Generation and application of data on biological variation in clinical chemistry.

C G Fraser1, E K Harris.   

Abstract

Most clinical chemical analytes vary in a random manner around a homeostatic set point. Replicate analyses of a series of specimens collected from a group of subjects allows estimation of analytical, within and between subject components of variation. The preferred experimental procedures and statistical methods for evaluation of data and analysis of variance are described; a detailed example is provided in the Appendix. The many uses of data on biological variation in clinical chemistry are reviewed, including setting analytical goals, deciding the significance of changes in serial results from an individual, evaluating the utility of conventional population-based reference values in patient management, and other applications.

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Year:  1989        PMID: 2679660     DOI: 10.3109/10408368909106595

Source DB:  PubMed          Journal:  Crit Rev Clin Lab Sci        ISSN: 1040-8363            Impact factor:   6.250


  110 in total

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Journal:  J Endocrinol Invest       Date:  2018-12-05       Impact factor: 4.256

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Journal:  Clin Chem       Date:  2011-04-25       Impact factor: 8.327

Review 3.  Haematocrit: within-subject and seasonal variation.

Authors:  Poul Thirup
Journal:  Sports Med       Date:  2003       Impact factor: 11.136

4.  Critical difference applied to exercise-induced oxidative stress: the dilemma of distinguishing biological from statistical change.

Authors:  Gareth W Davison; Tony Ashton; Jane McEneny; Ian S Young; Bruce Davies; Damian M Bailey
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Review 5.  Bone metabolism markers in sports medicine.

Authors:  Giuseppe Banfi; Giovanni Lombardi; Alessandra Colombini; Giuseppe Lippi
Journal:  Sports Med       Date:  2010-08-01       Impact factor: 11.136

6.  Reference change values of blood analytes from physically active subjects.

Authors:  Lázaro Alessandro S Nunes; René Brenzikofer; Denise Vaz de Macedo
Journal:  Eur J Appl Physiol       Date:  2010-05-06       Impact factor: 3.078

7.  Urinary cytokine and chemokine profiles across the menstrual cycle in healthy reproductive-aged women.

Authors:  Brian W Whitcomb; Sunni L Mumford; Neil J Perkins; Jean Wactawski-Wende; Elizabeth R Bertone-Johnson; Kristine E Lynch; Enrique F Schisterman
Journal:  Fertil Steril       Date:  2014-02-26       Impact factor: 7.329

8.  Biological variations of some analytes in renal posttransplant patients: a different way to assess routine parameters.

Authors:  Ozlem Goruroglu Ozturk; Saime Paydas; Mustafa Balal; Gulhan Sahin; Esin Damla Ziyanoglu Karacor; Sedefgul Yuzbasioglu Ariyurek; Akgun Yaman
Journal:  J Clin Lab Anal       Date:  2013-11       Impact factor: 2.352

9.  Analytical and biological variability in biomarker measurement in the Hispanic Community Health Study/Study of Latinos.

Authors:  Bharat Thyagarajan; Annie Green Howard; Ramon Durazo-Arvizu; John H Eckfeldt; Marc D Gellman; Ryung S Kim; Kiang Liu; Armando J Mendez; Frank J Penedo; Gregory A Talavera; Marston E Youngblood; Lihui Zhao; Daniela Sotres-Alvarez
Journal:  Clin Chim Acta       Date:  2016-10-15       Impact factor: 3.786

10.  Iterative Outlier Removal: A Method for Identifying Outliers in Laboratory Recalibration Studies.

Authors:  Christina M Parrinello; Morgan E Grams; Yingying Sang; David Couper; Lisa M Wruck; Danni Li; John H Eckfeldt; Elizabeth Selvin; Josef Coresh
Journal:  Clin Chem       Date:  2016-05-19       Impact factor: 8.327

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