The Importance of Interpolation in Computerized Growth Charting.
Computer growth charting is increasingly available for clinical and research applications. The LMS method is used to define the growth curves on the charts most commonly used in practice today. The data points for any given chart are at discrete points, and computer programs may simply round to the...
| Publicado en: | Journal of Medical Systems Vol. 40; no. 1; pp. 1 - 6 |
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| Autores principales: | , |
| Formato: | equations & formulas research tables/charts Journal Article |
| Publicado: |
Springer Nature
Jan2016
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=115925229&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 115925229 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 01485598 4N0 jtl: Journal of Medical Systems issn: 01485598 maglogo: N pubinfo: dt: Jan2016 vid: 40 iid: 1 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 115925229 115925229 115925229 10.1007/s10916-015-0389-x 115925229 ppf: 1 ppct: 5 formats: fmt: @attributes: type: P tig: atl: The Importance of Interpolation in Computerized Growth Charting. aug: au: Kiger, James Taylor, Sarah affil: Department of Pediatrics, Medical University of South Carolina, 165 Ashley Ave, MSC 917 Charleston 29425 USA sug: subj: Growth Computers and Computerization Charting Algorithms Human Descriptive Statistics Infant, Newborn Infant World Health Organization Centers for Disease Control and Prevention (U.S.) Child, Preschool Male Female Electronic Health Records Automation Infant, Newborn: birth-1 month Infant: 1-23 months Child, Preschool: 2-5 years Male Female ab: Computer growth charting is increasingly available for clinical and research applications. The LMS method is used to define the growth curves on the charts most commonly used in practice today. The data points for any given chart are at discrete points, and computer programs may simply round to the closest LMS data point when calculating growth centiles. We sought to determine whether applying an interpolation algorithm to the LMS data for commonly used growth charts may reduce the inherent errors which occur with rounding to the nearest data point. We developed a simple, easily implemented interpolation algorithm to use with LMS data. Using published growth charts, we compared predicted growth centiles using our interpolation algorithm versus a standard rounding approach. Using a test scenario of a patient at the 50th centile in weight, compared to using our interpolation algorithm, the method of simply rounding to the nearest data point resulted in maximal z-score errors in weight of the following: 2.02 standard deviations for the World Health Organization 0-to-23 month growth chart, 1.07 standard deviations for the Fenton preterm growth chart, 0.71 standard deviations for the Olsen preterm growth chart, and 0.11 standard deviations for the CDC 2-to-18 year growth chart. Failure to include an interpolation algorithm when designing computerizing growth charts can lead to large errors in centile and z-score calculations. pubtype: Academic Journal doctype: equations & formulas research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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