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  • 1.
    Gellerstedt, Martin
    University West, School of Business, Economics and IT, Divison of Informatics.
    Partitioning reference values of several Gaussian subpopulations with unequal prevalence--a procedure with computer program support2006In: Clinical Chemistry and Laboratory Medicine, ISSN 1434-6621, E-ISSN 1437-4331, Vol. 44, no 10, p. 1258-63Article in journal (Refereed)
    Abstract [en]

    BACKGROUND: To be able to interpret laboratory values, it is essential to develop population-based reference intervals. A crucial consideration is whether a reference interval should be divided into subpopulations or not, so-called partitioning. There are established methods for deciding whether partitioning should be done or not. However, these methods are only applicable when partitioning into two subpopulations is considered. The primary aim of this study was to suggest a procedure that was also valid for several subpopulations. The method assumes that these subpopulations are Gaussian. Furthermore, a secondary aim was to provide a tailor-made computer program to support calculations. METHODS: The fundamental idea is to partition reference intervals if the proportions of the distributions of the subpopulations outside the combined reference limit deviate from the nominal value of 0.025. This is made possible by finding the combined reference interval using an equation solver algorithm. RESULTS: It was found that an equation solver algorithm could easily identify the combined reference interval when combining two or more subpopulations, even if these subpopulations had unequal prevalences. It was also found that this could be done even if the ratio between samples does not reflect the ratio between prevalences. Using this algorithm, it was possible to study whether the proportion outside the combined reference limits in any of several subpopulations deviated from the nominal 0.025 by such a magnitude that partitioning was recommended. When similar figures to those found in earlier studies with other methods were tested, the procedure showed consistent results with these methods. The procedure was also found to be applicable when several subpopulations were considered. As a practical result of the study, a tailor-made computer program was developed and is now provided over the Internet. CONCLUSIONS: The suggested procedure could serve as an alternative or complement to existing methods. The procedure provides calculations of the combined reference interval, even if sample fractions do not reflect prevalence fractions. The important advantage with the suggested procedure is the generalisation to the situation when several Gaussian subpopulations, possibly with unequal prevalences, are considered. Finally, since a tailor-made computer program is provided, the procedure is simple to use.

  • 2.
    Gellerstedt, Martin
    et al.
    University West, School of Business, Economics and IT, Division of Computer Science and Informatics.
    Petersen, Per Hyltoft
    University of Bergen, Bergen, Norway.
    Partitioning reference values for several subpopulations using cluster analysis.2007In: Clinical Chemistry and Laboratory Medicine, ISSN 1434-6621, E-ISSN 1437-4331, Vol. 45, no 8, p. 1026-32Article in journal (Refereed)
    Abstract [en]

    BACKGROUND: A crucial question when developing reference intervals is whether different subpopulations need their own reference interval or if a single joint reference interval can be used. It is reasonable to use partitioned reference intervals in situations where a single interval results in considerable variation in sensitivity between subpopulations. The aim of partitioning is to harmonize the sensitivity of the reference intervals, i.e., to make the sensitivity similar for all patients, regardless of patient characteristics. Statistical criteria to identify when partitioning is adequate have been developed over the last two decades. These criteria are applicable when considering two subpopulations, but recently a procedure for considering several subpopulations has been developed. When several subpopulations are considered, there is a possibility that some subpopulations could form a group or cluster that could share a common reference interval. However, there is no formal systematic approach to indicate how to divide these subpopulations into clusters. The aim of this study was to suggest such a systematic approach for clustering. METHODS: A clustering technique was applied to data including several subpopulations. The technique is based on measuring the distance between separated reference limits and successively pooling subpopulations divided by short distances. A cluster is defined by a group of subpopulations that are close to each other and that differ from subpopulations in another cluster. A cluster recruits new subpopulations as long as the subpopulations can be pooled without violating a partitioning criterion. CONCLUSIONS: We have suggested a procedure for partitioning a number of Gaussian (or Gaussian-transformable) subpopulations into clusters. This is the only formalized procedure indicating how to analyze several subpopulations and identify a suitable number of groups and reference intervals. Using a computer program developed for partitioning issues, the approach was easy to adopt.

  • 3.
    Monneret, Denis
    et al.
    Department of Metabolic Biochemistry, La Pitié Salpêtrière-Charles Foix University Hospital, Paris, France.
    Gellerstedt, Martin
    University West, School of Business, Economics and IT, Divison of Informatics. Department of Surgery, Institute of Clinical Sciences, University of Gothenburg, Scandinavian Surgical Outcomes Research Group, Sahlgrenska University Hospital, Gothenburg, Sweden.
    Bonnefont-Rousselot, Dominique
    Paris Descartes University, Faculty of Pharmacy, Department of Biochemistry, Paris, France.
    Determination of age- and sex-specific 99th percentiles for high-sensitive troponin T from patients: An analytical imprecision- and partitioning-based approach2018In: Clinical Chemistry and Laboratory Medicine, ISSN 1434-6621, E-ISSN 1437-4331, Vol. 56, no 5, p. 818-829Article in journal (Other academic)
    Abstract [en]

    Detection of acute myocardial infarction (AMI) is mainly based on a rise of cardiac troponin with at least one value above the 99th percentile upper reference limit (99th URL). However, circulating high-sensitive cardiac troponin T (hs-cTnT) concentrations depend on age, sex and renal function. Using an analytical imprecision-based approach, we aimed to determine age- A nd sex-specific hs-cTnT 99th URLs for patients without chronic kidney disease (CKD). A 3.8-year retrospective analysis of a hospital laboratory database allowed the selection of adult patients with concomitant plasma hs-cTnT (<300 ng/L) and creatinine concentrations, both assayed twice within 72 h with at least 3 h between measurements. Absence of AMI was assumed when the variation between serial hs-cTnT values was below the adjusted-analytical change limit calculated according to the inverse polynomial regression of analytical imprecision. Specific URLs were determined using Clinical and Laboratory Standards Institute (CLSI) methods, and partitioning was tested using the proportion method, after adjustment for unequal prevalences. After outlier removal (men: 8.7%; women: 6.6%), 1414 men and 1082 women with estimated glomerular filtration rate (eGFR) ≥60 mL/min/1.73 m2 were assumed as non-AMI. Partitioning into age groups of 18-50, 51-70 and 71-98 years, the hs-cTnT 99th URLs adjusted on French prevalence were 18, 33, 66 and 16, 30, 84 ng/L for men and women, respectively. Age-partitioning was clearly required. However, sex-partitioning was not justified for subjects aged 18-50 and 51-70 years for whom a common hs-cTnT 99th URLs of about 17 and 31 ng/L could be used. Based on a laboratory approach, this study supports the need for age-specific hs-cTnT 99th URLs. © 2017 Walter de Gruyter GmbH.

  • 4.
    Monneret, Denis
    et al.
    Department of Biochemistry and Molecular Biology, South Lyon Hospital Group, Hospices Civils de Lyon (HCL), 165 Chemin du Grand Revoyet, Pierre-Bénite, 69495, France.
    Gellerstedt, Martin
    University West, School of Business, Economics and IT, Divison of Informatics.
    Roche, Frédéric
    Department of Clinical and Exercise Physiology, University Hospital of Saint-Etienne, Saint-Etienne, France; EA 4607 SNA-EPIS, PRES Lyon, Saint-Etienne, France .
    Bonnefont-Rousselot, Dominique
    Department of Metabolic Biochemistry, La Pitié Salpêtrière-Charles Foix University Hospital (AP-HP), Paris, France; CNRS UMR8258, INSERM U1022, Faculty of Pharmacy, Sorbonne Paris Cité, Paris Descartes University, Paris, France.
    Outlier removal methods for skewed data: Impact on age-specific high-sensitive cardiac troponin T 99th percentiles2019In: Clinical Chemistry and Laboratory Medicine, ISSN 1434-6621, E-ISSN 1437-4331, Vol. 57, no 10, p. E244-E247Article in journal (Refereed)
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