BACKGROUND: Laboratories today face increasing pressure to automate operations due to increasing workloads and the need to reduce expenditure. Few studies to date have focussed on the laboratory automation of preanalytical coagulation specimen processing. In the present study, we examined whether a clinical chemistry automation protocol meets the preanalytical requirements for the analyses of coagulation. METHODS: During the implementation of laboratory automation, we began to operate a pre- and postanalytical automation system. The preanalytical unit processes blood specimens for chemistry, immunology and coagulation by automated specimen processing. As the production of platelet-poor plasma is highly dependent on optimal centrifugation, we examined specimen handling under different centrifugation conditions in order to produce optimal platelet deficient plasma specimens. To this end, manually processed models centrifuged at 1500 g for 5 and 20 min were compared to an automated centrifugation model at 3000 g for 7 min. RESULTS: For analytical assays that are performed frequently enough to be targets for full automation, Passing-Bablok regression analysis showed close agreement between different centrifugation methods, with a correlation coefficient between 0.98 and 0.99 and a bias between -5% and +6%. For seldom performed assays that do not mandate full automation, the Passing-Bablok regression analysis showed acceptable to poor agreement between different centrifugation methods. CONCLUSIONS: A full automation solution is suitable and can be recommended for frequent haemostasis testing.
BACKGROUND: Laboratories today face increasing pressure to automate operations due to increasing workloads and the need to reduce expenditure. Few studies to date have focussed on the laboratory automation of preanalytical coagulation specimen processing. In the present study, we examined whether a clinical chemistry automation protocol meets the preanalytical requirements for the analyses of coagulation. METHODS: During the implementation of laboratory automation, we began to operate a pre- and postanalytical automation system. The preanalytical unit processes blood specimens for chemistry, immunology and coagulation by automated specimen processing. As the production of platelet-poor plasma is highly dependent on optimal centrifugation, we examined specimen handling under different centrifugation conditions in order to produce optimal platelet deficient plasma specimens. To this end, manually processed models centrifuged at 1500 g for 5 and 20 min were compared to an automated centrifugation model at 3000 g for 7 min. RESULTS: For analytical assays that are performed frequently enough to be targets for full automation, Passing-Bablok regression analysis showed close agreement between different centrifugation methods, with a correlation coefficient between 0.98 and 0.99 and a bias between -5% and +6%. For seldom performed assays that do not mandate full automation, the Passing-Bablok regression analysis showed acceptable to poor agreement between different centrifugation methods. CONCLUSIONS: A full automation solution is suitable and can be recommended for frequent haemostasis testing.
Authors: Janne Cadamuro; Cornelia Mrazek; Alexander B Leichtle; Ulrike Kipman; Thomas K Felder; Helmut Wiedemann; Hannes Oberkofler; Georg M Fiedler; Elisabeth Haschke-Becher Journal: Biochem Med (Zagreb) Date: 2017-11-24 Impact factor: 2.313
Authors: Cornelia Mrazek; Giuseppe Lippi; Martin H Keppel; Thomas K Felder; Hannes Oberkofler; Elisabeth Haschke-Becher; Janne Cadamuro Journal: Biochem Med (Zagreb) Date: 2020-06-15 Impact factor: 2.313