• Media type: E-Article
  • Title: The REALAB Project: A New Method for the Formulation of Reference Intervals Based on Current Data
  • Contributor: Grossi, Enzo; Colombo, Roberto; Cavuto, Silvio; Franzini, Carlo
  • imprint: Oxford University Press (OUP), 2005
  • Published in: Clinical Chemistry
  • Language: English
  • DOI: 10.1373/clinchem.2005.047787
  • ISSN: 0009-9147; 1530-8561
  • Keywords: Biochemistry (medical) ; Clinical Biochemistry
  • Origination:
  • Footnote:
  • Description: <jats:title>Abstract</jats:title><jats:p>Background: In a primary healthcare center concerned more with maintaining wellness than with diagnosing and monitoring illness, it is particularly important to compare patients’ results with reference intervals derived from a matched population by use of defined statistical methods.</jats:p><jats:p>Methods: Laboratory results over a 3-year period (∼15 000 000 records; 197 350 individuals) were retrieved from our laboratory information system. An inclusion/exclusion procedure for individual patients was applied based on (a) presence of at least 1 of 23 previously defined “basic tests”; (b) only 1 measurement per test by the laboratory over the 3-year period; (c) for each test, absence of any abnormality in the correlated tests. Before the third step, correlations among quantities were assessed by a Spearman correlation matrix, comparing each of the 23 basic tests with all remaining tests by use of a novel multivariate algorithm.</jats:p><jats:p>Results: The initial sample group (n = 197 350) was reduced stepwise by the selection criteria outlined above to 166 027, then to 93 649, and finally to 61 246 individuals constituting our reference sample group. Results from the last 2 groups were used to calculate sex-specific, and in some cases age-related, reference limits for the 23 basic tests and for 13 additional quantities. Reference limits were calculated throughout this study by nonparametric estimation of percentiles.</jats:p><jats:p>Conclusion: Reference values derived by retrospective analysis of large samples of data obtained at a given institution are particularly suitable for the evaluation of results for the presenting patient population at that institution.</jats:p>