Pneumatic tube validation: Reducing the need for donor samples by integrating a vial-embedded data logger

Jerk (d(acceleration)/dt) as an operative variable in pneumatic tube transport (PTT)

BACKGROUND

Jerk, the rate of change of acceleration (d(acceleration)/dt), is a known operative variable in public transportation safety, but this term has never appeared in the literature regarding pneumatic tube transport (PTT) and specimen integrity. We investigated profiles of acceleration and jerk for 2 PTT routes within our hospital system.

METHODS

Acceleration data were collected for PTT for 2 routes (A, B) using an accelerometer. Acceleration vectors (a) were analyzed in terms of distributions of jerk (da/dt), and distributions of θ, the angle between successive acceleration vectors.

RESULTS

Routes A and B had transit times of approximately 300 s. Acceleration vectors (a) ranged in magnitude from 0 to 8 g. For B, a > 1.2 g comprised 29.0% of results, compared to 13.5% of results for A (ratio = 2.1). Jerk ranged from 0 to 94 g/s. For B, jerk > 0.5 g/s comprised 71.9% of results, compared to 32.5% of results for A (ratio = 2.2). θ ranged from 0 to 180 degrees. For B, θ > 5 degrees comprised 59.3% of results, compared to 26.6% of results for A (ratio = 2.2).

CONCLUSION

Differences in distribution in acceleration, jerk, and θ ran in parallel as variables for comparison between 2 PTT routes. Jerk and θ are likely to be operative variables in effects of PTT.

Comparison of a two-step Tempus600 hub solution single-tube vs. container-based, one-step pneumatic transport system

OBJECTIVES

Efficient and timely transportation of clinical samples is pivotal to ensure accurate diagnoses and effective patient care. During the transportation process, preservation of sample integrity is crucial to avoid pre-analytical aberrations on laboratory results. Here, we present a comparative analysis between a two-step Tempus600 hub solution single-tube and a one-step, container-based pneumatic transport system (PTS) from Airco, for the in-house transportation of blood samples.

METHODS

Ten blood samples from healthy volunteers were split in 10 mL collection tubes filled at full or half capacity for transportation with the two PTS (about 250 m). To compare the impact of transportation, markers of hemolysis such as lactate dehydrogenase (LDH), potassium (K+), and the hemolysis index (HI), were determined. Additionally, differences in HI in routine samples and repeated transportation was investigated. To assess and compare the mechanistic impact profiles, we recorded the acceleration profiles of the two PTS using a shock data logger.

RESULTS

Transportation using the Tempus600 hub solution resulted in 49 and 46 % higher HI with samples filled to total or half capacity, respectively. Routine samples transported with the Tempus600 hub solution showed a higher median HI by 23 and 33 %. Additionally, shock logger analysis showed an elevated amount of shocks (6.5 fold) and shock intensities (1.8 fold).

CONCLUSIONS

The Tempus600 hub solution caused an increased number of unreportable LDH or K+ results based on the hemolysis index. However, it was only statistically significant for LDH (p<0.01 and p<0.08) - while the comparisons for K+ were not statistically significant (p<0.28 and p<0.56).

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

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.

Impact of blood collection devices and mode of transportation on peripheral venous blood gas parameters

BACKGROUND

Peripheral venous blood (PVB) gas analysis has become an alternative to arterial blood gas (BG) analysis in assessing acid-base balance. This study aimed to compare the effects of blood collection devices and modes of transportation on peripheral venous BG parameters.

METHODS

PVB-paired specimens were collected from 40 healthy volunteers into blood gas syringes (BGS) and blood collection tubes (BCT), transported by either a pneumatic tube system (PTS) or human courier (HC) to the clinical laboratory, and compared using a two-way ANOVA or Wilcoxon signed-rank test. To determine clinical significance, the PTS and HC-transported BGS and BCT biases were compared to the total allowable error (TEA).

RESULTS

PVB partial pressure of oxygen (pO2), fractional oxyhemoglobin (FO2Hb), fractional deoxyhemoglobin (FHHb), and oxygen saturation (sO2) showed statistically significant differences between BGS and BCT (p < 0.0001). Compared to HC-transported BGS and BCT, statistically significant increases in pO2, FO2Hb, sO2, oxygen content (only in BCT) (all p < 0.0001), and base excess extracellular (only in BCT; p < 0.0014) concentrations and a statistically significant decrease in FHHb concentration (p < 0.0001) were found in BGS and BCT delivered by PTS. The biases between PTS- and HC-transported BGS and BCT exceeded the TEA for many BG parameters.

CONCLUSIONS

Collecting PVB in BCT is unsuitable for pO2, sO2, FO2Hb, FHHb, and oxygen content determinations.

Investigation of the effects of pneumatic tube transport system on routine biochemistry, hematology, and coagulation tests in Ankara City Hospital

OBJECTIVES

Academics are far from a consensus regarding the effects of pneumatic tube system (PTS) delivery on sample integrity and laboratory test results. As for the reasons for conflicting opinions, each PTS is uniquely designed, sample tubes and patient characteristics differ among studies. This study aims to validate the PTS utilized in Ankara City Hospital for routine chemistry, coagulation, and hematology tests by comparing samples delivered via PTS and porter.

METHODS

The study comprises 50 healthy volunteers. Blood samples were drawn into three biochemistry, two coagulation, and two hemogram tubes from each participant. Each of the duplicate samples was transferred to the emergency laboratory via Swiss log PTS (aka PTS-immediately) or by a porter. The last of the biochemistry tubes were delivered via the PTS, upon completion of coagulation of the blood (aka PTS-after). The results of the analysis in these groups were compared with multiple statistical analyses.

RESULTS

The study did not reveal any correlation between the PTS and serum hemolysis index. There were statistically significant differences in several biochemistry tests. However, none of them reached the clinical significance threshold. Basophil and large unidentified cell (LUC) tests had poor correlations (r=0.47 and r=0.60; respectively) and reached clinical significance threshold (the average percentages of bias, 10.2%, and 15.4%, respectively). The remainder of the hematology and coagulation parameters did not reach clinical significance level either.

CONCLUSIONS

The modern PTS validated in this study is safe for sample transportation for routine chemistry, coagulation, and hematology tests frequently requested in healthy individuals except for basophil and LUC.