Pneumatic tube transportation of urine samples Sandvig ...

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Pneumatic tube transportation of urine samples

Sandvig Andersen, Eline; Brandslund, Ivan

Published in: Clinical Chemistry and Laboratory Medicine DOI: 10.1515/cclm-2020-1198 Publication date: 2021 Document version: Final published version

Citation for pulished version (APA): Sandvig Andersen, E., & Brandslund, I. (2021). Pneumatic tube transportation of urine samples. Clinical Chemistry and Laboratory Medicine, 59(5), 905-911.

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Clin Chem Lab Med 2021; 59(5): 905?911

Eline Sandvig Andersen* and Ivan Brandslund

Pneumatic tube transportation of urine samples

Received August 6, 2020; accepted November 6, 2020; published online November 23, 2020

Abstract

Objectives: Pneumatic tube transportation of samples is an effective way of reducing turn-around-time, but evidence of the effect of pneumatic tube transportation on urine samples is lacking. We thus wished to investigate the effect of pneumatic tube transportation on various components in urine, in order to determine if pneumatic tube transportation of these samples is feasible. Methods: One-hundred fresh urine samples were collected in outpatient clinics and partitioned with one partition being carried by courier to the laboratory, while the other was sent by pneumatic tube system (Tempus600). Both partitions were then analysed for soluble components and particles, and the resulting mean difference and limits of agreement were calculated. Results: Albumin, urea nitrogen, creatinine, protein and squamous epithelial cells were unaffected by transportation in the Tempus600 system, while bacteria, renal tubular epithelial cells, white blood cells and red blood cells were affected and potassium and sodium may have been affected. Conclusions: Though pneumatic tube transportation did affect some of the investigated components, in most cases the changes induced were clinically acceptable, and hence samples could be safely transported by the Tempus600 pneumatic tube system. For bacteria, white blood cells and red blood cells local quality demands will determine if pneumatic tube transportation is appropriate.

Keywords: albumin; bacteria; creatinine; leukocytes; pneumatic tube transportation; proteinuria; Tempus600; turn-around-time; urinalysis; urinary tract infection.

*Corresponding author: Eline Sandvig Andersen, MD, Biochemistry and Immunology, University Hospital of Southern Denmark, Vejle, Denmark, E-mail: eline.sandvig.andersen@rsyd.dk. . org/0000-0001-5461-6976 Ivan Brandslund, Department of Biochemistry and Immunology, Lillebaelt Hospital, University Hospital of Southern Denmark, Vejle, Denmark; and Department of Regional Health Research, University of Southern Denmark, Vejle, Denmark

Introduction

Transportation of samples in pneumatic tube systems (PTS) is an effective way of reducing sample transportation time and thus total turn-around-time (TAT) for sample analysis [1?4]. This form of transportation is documented for blood samples [1, 3, 5, 6], but to the knowledge of the authors, no documentation regarding pneumatic tube transportation (PTT) of urine samples has been published.

Reduction of transportation time of urine may be especially relevant for components with limited stability over time [7, 8], as a reduction of transportation time can help secure timely analysis of these components. Further, in some situations, such as screening for urinary tract infections (UTI) or proteinuria, low TATs are clinically required. This is often achieved by the use of point-of-care-tests (POCT), but if total TAT for centralized urine analyses can be reduced to less than 1 h, through the use of PTT, as reported for blood samples [1, 3, 4], this may render POCT unnecessary. Before this can be implemented, however, documentation of the effects of PTT is necessary [6].

PTT affects the samples through physical stress, changes in temperature and changes in transportation time. Through these factors, PTT of blood samples can cause bubble formation [9], affect gas exchange within the sample tube [1] as well as affect the stability of the cellular components [9], and hence, affect analysis results. Still, many blood components remain stable enough for safe transport through PTS [1, 3, 5].

It is, however, not certain that this is also the case for urine samples. Urine contains many of the same constituents as blood, but at different concentrations. Cell stability is affected by pH and osmolality of the surrounding fluid [10], and while these factors are relatively stable in blood, they differ widely in urine, potentially causing a difference in susceptibility to PTT.

We therefore wished to investigate the effect of PTT of urine samples on various components (see Table 1 and 2) including protein, albumin and creatinine for evaluation of proteinuria as well as bacteria and white blood cells (WBC) for the detection of UTI. We wanted to know if PTT induced systematic or random errors on the analysis results obtained. If so, we wished to estimate the magnitude of error in order to evaluate if PTT of the sample was appropriate for the given component.

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Andersen and Brandslund: Pneumatic tube transportation of urine samples

Table : Soluble components.

Courier PTS

Difference (PTS-courier)

Analyte

Unit n

Range Mean Mean

Mean difference Limits of agreement, Expected limits

(%CI)

% (% CI) of agreement, %

Albumin

mg/L

-. . .

-. (-. to -. to . (-.

.)

to .)

Albumin

mg/L

.- . (-. to .) -. to . (-.

to .)

Albumin-to-creatinine mg/mmol .-. . . . (-. to -. to . (-.

ratio

.)

to .)

Albumin-to-creatinine mg/mmol .- . .

. (-. to -. to . (-.

ratio

.)

to .)

Creatinine

mmol/L .-. . . -. (-. to -. to . (-.

.)

to .)

Creatinine

mmol/L .-. . . -. (-. to -. to . (-.

.)

to .)

Potassium

mmol/L

.- . .

. (-. to -. to . (-.

.)

to .)a

Protein

g/L

.-. . . . (-. -. to . (-.

to .)

to .)

Protein

g/L

.-. . . -. (-. -. to . (-.

to .)

to .)

Sodium

mmol/L -. . .

. (-. to -. to . (-.

.)

to .)a

Sodium

mmol/L -

. (-. to -. to . (-.

.)

to .)

Urea nitrogen

mmol/L .- . (-. to -. to . (-.

.)

to .)

? ?. N/A N/A ?. ?. ?. ? ? ?. ?. ?

The Table shows the number of pairs of samples (n), range and mean of the courier-carried samples, mean of the pneumatic tube transported samples, mean difference between pairs (tempus-transported minus courier-carried) in original units, limits of agreement (LoA) in % with % confidence intervals (CI) and expected LoAs in %. aLoA significantly different from expected LoA (% confidence), suggesting the possible induction of a systematic or random error.

Materials and methods

Samples

One-hundred fresh urine samples were collected through convenience sampling from the outpatient blood collection clinics at Lillebaelt Hospital, Denmark. Patients, who delivered a fresh urine sample at the clinic, were asked for permission to use any remaining urine for this evaluation. For patients who gave oral consent, any excess urine was aliquoted into four labelled 3-mL vacuum tubes with no additives (Greiner bio-one, Kremsm?nster, Austria) using a urine transfer device (straw) (Greiner bio-one, Kremsm?nster, Austria). No information regarding the patients was recorded, and the samples were processed anonymously.

The evaluation was performed in compliance with the Helsinki Declaration, Danish law and European data-protection regulations.

Transport and analysis

When patients delivered a urine sample, a lab technician was waiting to receive the sample immediately. The sample was transported to the

urine lab by foot (a maximum of approximately 30 m) and aliquoted. No mixing procedure was applied.

Of each set of four sample tubes, two were carried by courier to the laboratory, while the other two were sent by PTS (Tempus600, Sarstedt, Bording, Denmark).

The Tempus600 is a one-way pneumatic tube system in which the samples are transported by compressed air through flexible tubes, without the use of cartridges [1, 2, 11]. Its peak acceleration is around 16 g [2, 12]. The samples transported by PTS were automatically received on the GLP transport track (GLP Systems, Hamburg, Germany), where they were retained until the matching couriercarried samples arrived.

Subsequently two samples from each set (one carried and one sent by PTS) were automatically transferred to the centrifuges, centrifuged at 2654 g for 5 min and thereafter sent to the Cobas8000 modules (c502, c702 and ISE-modules (Roche, Basel, Switzerland)) in random order. The other pair of tubes were collected in a GLP output module and manually transferred to the UF-5000 (Sysmex Corporation, Kobe, Japan) without prior centrifugation. For every second sample-pair, the courier carried sample was run first and vice versa.

Albumin, urea nitrogen, creatinine, potassium, protein and sodium was analysed on the Cobas8000 system. Bacteria, red blood cells (RBC), renal tubular epithelial cells (RTEC), squamous

Andersen and Brandslund: Pneumatic tube transportation of urine samples

907

Table : Particles.

Courier PTS

Difference (PTS-courier)

Particle

Unit n Range Mean Mean

Bacteria

?/L .?

Bacteria Red blood cells

?/L ? ?/L ?. . .

Red blood cells

?/L ?

Renal tubular epithelial cells ?/L .?. . .

Renal tubular epithelial cells ?/L .? . .

Squamous epithelial cells

?/L .?. . .

Squamous epithelial cells White blood cells

?/L ?

?/L ?

Mean difference (%CI)

Limits of agreement, % (% CI)

. (-. to .)

. (-. to ) . (.?.)a

. (-. to .) . (.?.)a

-. (-. to .)

-. (-. to .)

-. (-. to .) . (-. to )

- to (- to )b

- to (- to ) - to b (- to )

- to (- to )b - to (- to )b

- to (- to )

- to (- to )

- to (- to ) - to (- to )b

Expected limits of agreement, %

?

? ?

? ?

?

?

? ?

The Table shows the number of pairs of samples (n), range and mean of the courier-carried samples, mean of the pneumatic tube transported

samples, mean difference between pairs (tempus-transported minus courier-carried) in original units, limits of agreement (LoA) in % with % confidence intervals (CI) and expected LoAs in %. aMean difference significantly different from zero (% confidence), suggesting a bias between transportation methods. bLoA significantly different from expected LoA (% confidence), suggesting the possible induction of a systematic or random error.

epithelial cells (SQEC) and white blood cells (WBC) were analysed on the UF-5000. The UF-5000 counts multiple particle types simultaneously and all quantitatively counted components reported by the UF-5000 were included in the analysis. Further, the calculated parameter albumin-to-creatinine ratio was included in the evaluation.

Statistics

All data analysis was performed using Excel 2016 (Microsoft, Redmond, USA) and SAS Enterprise Guide 7.1 (SAS institute, Cary, USA). Code used for processing in SAS Enterprise Guide is available as Supplemental Material 1.

For all components, plots of the data were performed as described by Bland and Altman [13]. Plots were made in both original units and using natural logarithmic transformation. Based on these plots, it was evaluated whether division into groups depending on mean analyte concentration, was necessary.

For each group with at least 10 sample pairs after exclusion of pairs with mean concentration below the limit of detection (LoD), the following was calculated: Mean difference with 95% Confidence intervals (CI). Limits of agreement (LoA) with 95% CI [13]. The LoAs signify the range within which 95% of the differences between paired measurements will lie, while the mean difference is a measure of the bias between the two transportation methods.

The mean difference is reported in natural units while the LoAs are reported in % difference relative to the courier-carried sample. Plots of the mean value of each pair of measurements against the ratio of the values were plotted.

For evaluating whether the differences detected were due to analytical or preanalytical variation, expected limits of agreement

based on analytical variation were calculated for comparison, as described by Andersen et al. [1], using the formula

LoAexpected = ?1.96 2CVa2

where CVa is the analytical coefficient of variation (CV%). If the limits of agreement found exceed the expected analytical

limits of agreement, this signified a possible preanalytical systematic or random error.

For analyses on the Cobas8000 modules, where each sample was sent to one of two instruments, the CVa was estimated on internal control materials run on both instruments within 1 h of each other during the period of sample collection.

On the UF-5000, each pair of samples was run consecutively on the same instrument.

For UF-5000 analyses, the CVas were estimated using Poisson statistics, where the SDa is given by the square root of the number of particles counted. Based on the mean concentration in each group and the volume counted by the UF-5000 for each particular particle type, CVas were calculated. For RBC, bacteria, WBC and EC, the theoretical CVas were confirmed using own data as well as data from the literature (Supplemental Material 2, [14]). See Supplemental Material 2 for details regarding CVas.

Results for soluble components are reported with three significant figures, while results for particles are reported with two significant figures.

Results

All planned analyses were performed on all 100 samples. One set of samples prompted an error during analysis for potassium, and hence was excluded from the statistical

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Andersen and Brandslund: Pneumatic tube transportation of urine samples

analysis of the potassium results. One sample tube was not filled to capacity, but was not excluded from the analysis. Results for soluble components are shown in Table 1.

For sodium ................
................

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