Literature DB >> 31205377

Indirect Reference Intervals: Harnessing the Power of Stored Laboratory Data.

Christopher-John L Farrell1, Lan Nguyen1.   

Abstract

Reference intervals are relied upon by clinicians when interpreting their patients' test results. Therefore, laboratorians directly contribute to patient care when they report accurate reference intervals. The traditional approach to establishing reference intervals is to perform a study on healthy volunteers. However, the practical aspects of the staff time and cost required to perform these studies make this approach difficult for clinical laboratories to routinely use. Indirect methods for deriving reference intervals, which utilise patient results stored in the laboratory's database, provide an alternative approach that is quick and inexpensive to perform. Additionally, because large amounts of patient data can be used, the approach can provide more detailed reference interval information when multiple partitions are required, such as with different age-groups. However, if the indirect approach is to be used to derive accurate reference intervals, several considerations need to be addressed. The laboratorian must assess whether the assay and patient population were stable over the study period, whether data 'clean-up' steps should be used prior to data analysis and, often, how the distribution of values from healthy individuals should be modelled. The assumptions and potential pitfalls of the particular indirect technique chosen for data analysis also need to be considered. A comprehensive understanding of all aspects of the indirect approach to establishing reference intervals allows the laboratorian to harness the power of the data stored in their laboratory database and ensure the reference intervals they report are accurate.

Entities:  

Year:  2019        PMID: 31205377      PMCID: PMC6544248          DOI: 10.33176/AACB-19-00022

Source DB:  PubMed          Journal:  Clin Biochem Rev        ISSN: 0159-8090


  6 in total

1.  The indirect method in the establishment of reference intervals for complement 3 and complement 4: A retrospective study.

Authors:  Jiatong Chai; Zeyu Sun; Dongyang Xing; Qi Zhou; Jiancheng Xu
Journal:  J Taibah Univ Med Sci       Date:  2021-12-01

2.  Establishment of thromboelastography reference intervals by indirect method and relevant factor analyses.

Authors:  Daye Cheng; Xiaoying Li; Shuo Zhao; Yiwen Hao
Journal:  J Clin Lab Anal       Date:  2020-01-31       Impact factor: 2.352

3.  Establishment of Pediatric Reference Intervals for Routine Laboratory Tests in Korean Population: A Retrospective Multicenter Analysis.

Authors:  Ji Yeon Sung; Jong Do Seo; Dae-Hyun Ko; Min-Jeong Park; Sang Mee Hwang; Sohee Oh; Sail Chun; Moon-Woo Seong; Junghan Song; Sang Hoon Song; Sung Sup Park
Journal:  Ann Lab Med       Date:  2021-03-01       Impact factor: 3.464

4.  refineR: A Novel Algorithm for Reference Interval Estimation from Real-World Data.

Authors:  Christopher M Rank; Jakob Zierk; Tatjana Ammer; André Schützenmeister; Hans-Ulrich Prokosch; Manfred Rauh
Journal:  Sci Rep       Date:  2021-08-06       Impact factor: 4.379

5.  Indirect estimation of reference intervals for thyroid parameters using advia centaur XP analyzer.

Authors:  Bosa Mirjanić-Azarić; Neda Milinković; Natasa Bogavac-Stanojević; Sanja Avram; Tanja Stojaković-Jelisavac; Darja Stojanović
Journal:  J Med Biochem       Date:  2022-04-08       Impact factor: 2.157

6.  The establishment of neuron-specific enolase reference interval for the healthy population in southwest China.

Authors:  Qiang Miao; Bei Cai; Xuedan Gao; Zhenzhen Su; Junlong Zhang
Journal:  Sci Rep       Date:  2020-04-14       Impact factor: 4.379

  6 in total

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