Diagnostic sample transport via pneumatic tube systems: data logger and their algorithms are sensitive to transport effects

Author:

Ninnemann Jana1,Zylla Stephanie12,Streichert Thomas3ORCID,Otto Benjamin4,Haenel Mattis5,Nauck Matthias12,Petersmann Astrid16

Affiliation:

1. Institute of Clinical Chemistry and Laboratory Medicine, University Medicine Greifswald , Greifswald , Germany

2. DZHK (German Centre for Cardiovascular Research), Partner Site Greifswald, University Medicine Greifswald , Greifswald , Germany

3. Institute of Clinical Chemistry, Faculty of Medicine and University Hospital, University Hospital Cologne , Cologne , Germany

4. Department of Internal Medicine , University Medical Center, Hamburg-Eppendorf , Hamburg , Germany

5. Max Planck Institute of Plasma Physics, Sub-institute Greifswald , Greifswald , Germany

6. Institute of Clinical Chemistry and Laboratory Medicine, University Medicine Oldenburg , Oldenburg , Germany

Abstract

Abstract Objectives Many hospitals use pneumatic tube systems (PTS) for transport of diagnostic samples. Continuous monitoring of PTS and evaluation prior to clinical use is recommended. Data loggers with specifically developed algorithms have been suggested as an additional tool in PTS evaluation. We compared two different data loggers. Methods Transport types – courier, conventional (cPTS) and innovative PTS (iPTS) – were monitored using two data loggers (MSR145® logger, CiK Solutions GmbH, Karlsruhe, Germany, and a prototype developed at the University Medicine Greifswald). Data loggers differ in algorithm, recording frequencies and limit of acceleration detection. Samples from apparently healthy volunteers were split among the transport types and results for 37 laboratory measurands were compared. Results For each logger specific arbitrary units were calculated. Area-under-the-curve (AUC)-values (MSR145®) were lowest for courier and highest for iPTS and increased with increasing recording frequencies. Stress (St)-values (prototype logger) were obtained in kmsu (1,000*mechanical stress unit) and were highest for iPTS as well. Statistical differences between laboratory measurement results of transport types were observed for three measurands sensitive for hemolysis. Conclusions The statistical, but not clinical, differences in the results for hemolysis sensitive measurands may be regarded as an early sign of preanalytical impairment. Both data loggers record this important interval of beginning mechanical stress with a high resolution indicating their potential to facilitate early detection of preanalytical impairment. Further studies should identify suitable recording frequencies. Currently, evaluation and monitoring of diagnostic sample transport should not only rely on data loggers but also include diagnostic samples.

Publisher

Walter de Gruyter GmbH

Subject

Biochemistry (medical),Clinical Biochemistry,General Medicine

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