{"title":"Indirect reference intervals using an R pipeline","authors":"Dustin R. Bunch","doi":"10.1016/j.jmsacl.2022.02.004","DOIUrl":null,"url":null,"abstract":"<div><h3>Background</h3><p>Indirect reference intervals require robust statistical approaches to separate the pathological and healthy values. This can be achieved with a data pipeline created in R, a freely available statistical programming language.</p></div><div><h3>Methods</h3><p>A data pipeline was created to ingest, partition, normalize, remove outliers, and identify reference intervals for testosterone (Testo; n = 7,207) and aspartate aminotransferase (AST; n = 5,882) using data sets from NHANES.</p></div><div><h3>Results</h3><p>The estimates for AST and Testo determined by this pipeline approximated current RIs. Care should be taken when using this pipeline as there are limitations that depend on the pathology of the analyte and the data set being used for RI estimation.</p></div><div><h3>Conclusions</h3><p>R can be used to create a robust statistical reference interval pipeline.</p></div>","PeriodicalId":52406,"journal":{"name":"Journal of Mass Spectrometry and Advances in the Clinical Lab","volume":null,"pages":null},"PeriodicalIF":3.1000,"publicationDate":"2022-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2667145X22000050/pdfft?md5=8b513f5edfb6148b1e837e73de9d6aba&pid=1-s2.0-S2667145X22000050-main.pdf","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Mass Spectrometry and Advances in the Clinical Lab","FirstCategoryId":"3","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2667145X22000050","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MEDICAL LABORATORY TECHNOLOGY","Score":null,"Total":0}
引用次数: 2
Abstract
Background
Indirect reference intervals require robust statistical approaches to separate the pathological and healthy values. This can be achieved with a data pipeline created in R, a freely available statistical programming language.
Methods
A data pipeline was created to ingest, partition, normalize, remove outliers, and identify reference intervals for testosterone (Testo; n = 7,207) and aspartate aminotransferase (AST; n = 5,882) using data sets from NHANES.
Results
The estimates for AST and Testo determined by this pipeline approximated current RIs. Care should be taken when using this pipeline as there are limitations that depend on the pathology of the analyte and the data set being used for RI estimation.
Conclusions
R can be used to create a robust statistical reference interval pipeline.
求助内容：
应助结果提醒方式：
京公网安备 11010802042870号
