2009
DOI: 10.1515/jlm.2009.015
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An improved indirect approach for determining reference limits from intra-laboratory data bases exemplified by concentrations of electrolytes / Ein verbesserter indirekter Ansatz zur Bestimmung von Referenzgrenzen mittels intra-laboratorieller Datensätze am Beispiel von Elektrolyt-Konzentrationen

Abstract: Background: The current dogma of establishing intra-laboratory reference limits (RLs) and their periodical reviewing cannot be fulfilled by most laboratories due to the expenses involved. Thus, most laboratories adopt RLs from external sources often neglecting the problems of transferability. Presently accepted validation concepts still require experimental expenses. Several attempts were undertaken to derive RLs from the large data pools stored in modern laboratory information systems. Former indirect procedu… Show more

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Cited by 31 publications
(3 citation statements)
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“…One of the ideas is to utilize the LIS storage data to establish biological reference intervals. Over the past decades, this idea has been developed and improved, and a relatively mature methodological system has been established [20][21][22] .…”
Section: Discussionmentioning
confidence: 99%
“…One of the ideas is to utilize the LIS storage data to establish biological reference intervals. Over the past decades, this idea has been developed and improved, and a relatively mature methodological system has been established [20][21][22] .…”
Section: Discussionmentioning
confidence: 99%
“…A quantile-quantile plot was not applied. ND for serum blood parameters has been used commonly and has been scientifically established [36]. Descriptive statistics included the mean, median, and percentiles.…”
Section: Statistical Analyses Of Datamentioning
confidence: 99%
“…As a result, any tool used to distinguish between healthy and diseased distributions must be understood and applied with a high degree of precision [4]. Several indirect techniques have been developed and are now being utilised to estimate RIs, and the most recent and historically significant approaches are the Bhattacharya method [5] and the visual Hoffman approach [6], the truncated minimum likelihood (TML) method developed by Arzideh et al [7][8][9], the truncated minimum chi-square method developed by Wosniok et al [10] and the updated version of the TML technique developed by Zierk et al called KOSMIC [11] and refineR [12].…”
Section: Introductionmentioning
confidence: 99%