Random variation and systematic error caused by various preanalytical variables, estimated by linear mixed-effects models

Blood Sample Transportation by Pneumatic Transportation Systems: A Systematic Literature Review

BACKGROUND

Pneumatic transportation systems (PTSs) are increasingly used for transportation of blood samples to the core laboratory. Many studies have investigated the impact of these systems on different types of analyses, but to elucidate whether PTSs in general are safe for transportation of blood samples, existing literature on the subject was systematically assessed.

METHODS

A systematic literature review was conducted following the preferred reporting items for systematic reviews and metaanalyses (PRISMA) Statement guidelines to gather studies investigating the impact of PTS on analyses in blood samples. Studies were extracted from PubMed and Embase. The search period ended November 2016.

RESULTS

A total of 39 studies were retrieved. Of these, only 12 studies were conducted on inpatients, mainly intensive care unit patients. Blood gases, hematology, and clinical chemistry were well investigated, whereas coagulation, rotational thromboelastometry, and platelet function in acutely ill patients were addressed by only 1 study each. Only a few parameters were affected in a clinically significant way (clotting time parameter in extrinsic system thromboelastometry, pO2 in blood gas, multiplate analysis, and the hemolysis index).

CONCLUSIONS

Owing to their high degree of heterogeneity, the retrieved studies were unable to supply evidence for the safety of using PTSs for blood sample transportation. In consequence, laboratories need to measure and document the actual acceleration forces in their existing PTS, instituting quality target thresholds for these measurements such as acceleration vector sums. Computer modeling might be applied to the evaluation of future PTS installations. With the increasing use of PTS, a harmonized, international recommendation on this topic is warranted.

Preanalytical investigations of phlebotomy: methodological aspects, pitfalls and recommendations

Phlebotomy is often addressed as a crucial process in the pre-analytical phase, in which a large part of laboratory errors take place, but to date there is not yet a consolidated methodological paradigm. Seeking literature, we found 36 suitable investigations issued between 1996 and 2016 (April) dealing with the investigation of pre-analytical factors related to phlebotomy. We found that the largest part of studies had a cohort of healthy volunteers (22/36) or outpatients (11/36), with the former group showing a significantly smaller median sample size (N = 20, IQR: 17.5-30 and N = 88, IQR: 54.5-220.5 respectively, P < 0.001). Moreover, the largest part investigated one pre-analytical factor (26/36) and regarded more than one laboratory test (29/36), and authors preferably used paired Student’s t-test (17/36) or Wilcoxon’s test (11/36), but calibration (i.e. sample size calculation for a detectable effect) was addressed only in one manuscript. The Bland-Altman plot was often the preferred method used to estimate bias (12/36), as well as the Passing-Bablok regression for agreement (8/36). However, often papers did assess neither bias (12/36) nor agreement (24/36). Clinical significance of bias was preferably assessed comparing to a database value (16/36), and it resulted uncorrelated with the size of the effect produced by the factor (P = 0.142). However, the median effect size (ES) resulted significantly larger if the associated factor was clinically significant instead of non-significant (ES = 1.140, IQR: 0.815-1.700 and ES = 0.349, IQR: 0.228-0.531 respectively, P < 0.001). On these evidences, we discussed some recommendations for improving methodological consistency, delivering reliable results, as well as ensuring accessibility to practical evidences.

Plasma degradome affected by variable storage of human blood

Background

The successful application of—omics technologies in the discovery of novel biomarkers and targets of therapeutic interventions is facilitated by large collections of well curated clinical samples stored in bio banks. Mining the plasma proteome holds promise to improve our understanding of disease mechanisms and may represent a source of biomarkers. However, a major confounding factor for defining disease-specific proteomic signatures in plasma is the variation in handling and processing of clinical samples leading to protein degradation. To address this, we defined a plasma proteolytic signature (degradome) reflecting pre-analytical variability in blood samples that remained at ambient temperature for different time periods after collection and prior to processing.

Methods

We obtained EDTA blood samples from five healthy volunteers (n = 5), and blood tubes remained at ambient temperature for 30 min, 8, 24 and 48 h prior to centrifugation and isolation of plasma. Naturally occurred peptides derived from plasma samples were compared by label-free quantitative LC–MS/MS. To profile protein degradation, we analysed pooled plasma samples at T = 30 min and 48 h using PROTOMAP analysis. The proteolytic pattern of selected protein candidates was further validated by immunoblotting.

Results

A total of 820 plasma proteins were surveyed by PROTOMAP, and for 4 % of these, marked degradation was observed. We show distinct proteolysis patterns for talin-1, coagulation factor XI, complement protein C1r, C3, C4 and thrombospondin, and several proteins including S100A8, A9, annexin A1, profiling-1 and platelet glycoprotein V are enriched after 48 h blood storage at ambient temperature. In particular, thrombospondin protein levels increased after 8 h and proteolytic fragments appeared after 24 h storage time.

Conclusions

The overall impact of blood storage at ambient temperature for variable times on the plasma proteome and degradome is relatively minor, but in some cases can cause a potential bias in identifying and assigning relevant proteomic markers. The observed effects on the plasma proteome and degradome are predominantly triggered by limited leucocyte and platelet cell activation due to blood handling and storage. The baseline plasma degradome signature presented here can help filtering candidate protein markers relevant for clinical biomarker studies.

Electronic supplementary material

The online version of this article (doi:10.1186/s12014-016-9126-9) contains supplementary material, which is available to authorized users.