In:
Clinical Chemistry and Laboratory Medicine (CCLM), Walter de Gruyter GmbH, Vol. 57, No. 5 ( 2019-04-24), p. 730-739
Abstract:
Conventional establishment of reference intervals for hematological analytes is challenging due to the need to recruit healthy persons. Indirect methods address this by deriving reference intervals from clinical laboratory databases which contain large datasets of both physiological and pathological test results. Methods We used the “Reference Limit Estimator” (RLE) to establish reference intervals for common hematology analytes in adults aged 18–60 years. One hundred and ninety-five samples from 44,519 patients, measured on two different devices in a tertiary care center were analyzed. We examined the influence of patient cohorts with an increasing proportion of abnormal test results, compared sample selection strategies, explored inter-device differences, and analyzed the stability of reference intervals in simulated datasets with varying overlap of pathological and physiological test results. Results Reference intervals for hemoglobin, hematocrit, red cell count and platelet count remained stable, even if large numbers of pathological samples were included. Reference intervals for red cell indices, red cell distribution width and leukocyte count were sufficiently stable, if patient cohorts with the highest fraction of pathological samples were excluded. In simulated datasets, estimated reference limits shifted, if the pathological dataset contributed more than 15%–20% of total samples and approximated the physiological distribution. Advanced sample selection techniques did not improve the algorithm’s performance. Inter-device differences were small except for red cell distribution width. Conclusions The RLE is well-suited to create reference intervals from clinical laboratory databases even in the challenging setting of a adult tertiary care center. The procedure can be used as a complement for reference interval determination where conventional approaches are limited.
Type of Medium:
Online Resource
ISSN:
1437-4331
,
1434-6621
DOI:
10.1515/cclm-2018-0771
Language:
Unknown
Publisher:
Walter de Gruyter GmbH
Publication Date:
2019
detail.hit.zdb_id:
1492732-9
SSG:
15,3
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