Laboratory sample stability. Is it possible to define a consensus stability function? An example of five blood magnitudes.

BACKGROUND: The stability limit of an analyte in a biological sample can be defined as the time required until a measured property acquires a bias higher than a defined specification. Many studies assessing stability and presenting recommendations of stability limits are available, but differences among them are frequent. The aim of this study was to classify and to grade a set of bibliographic studies on the stability of five common blood measurands and subsequently generate a consensus stability function. METHODS: First, a bibliographic search was made for stability studies for five analytes in blood: alanine aminotransferase (ALT), glucose, phosphorus, potassium and prostate specific antigen (PSA). The quality of every study was evaluated using an in-house grading tool. Second, the different conditions of stability were uniformly defined and the percent deviation (PD%) over time for each analyte and condition were scattered while unifying studies with similar conditions. RESULTS: From the 37 articles considered as valid, up to 130 experiments were evaluated and 629 PD% data were included (106 for ALT, 180 for glucose, 113 for phosphorus, 145 for potassium and 85 for PSA). Consensus stability equations were established for glucose, potassium, phosphorus and PSA, but not for ALT. CONCLUSIONS: Time is the main variable affecting stability in medical laboratory samples. Bibliographic studies differ in recommedations of stability limits mainly because of different specifications for maximum allowable error. Definition of a consensus stability function in specific conditions can help laboratories define stability limits using their own quality specifications.

Spanish Preanalytical Quality Monitoring Program (SEQC), an overview of 12 years' experience.

BACKGROUND: Preanalytical variables, such as sample collection, handling and transport, may affect patient results. Preanalytical phase quality monitoring should be established in order to minimize laboratory errors and improve patient safety. METHODS: A retrospective study (2001-2013) of the results obtained through the Spanish Society of Clinical Biochemistry and Molecular Pathology (SEQC) External quality assessment (preanalytical phase) was performed to summarize data regarding the main factors affecting preanalytical phase quality. Our aim was to compare data from 2006 to 2013 with a previously published manuscript assessing the 2001-2005 period. RESULTS: A significant decrease in rejection rates was observed both for blood and urine samples. For serum samples, the most frequent rejection causes in the first period were non-received samples (37.5%), hemolysis (29.3%) and clotted samples (14.4%). Conversely, in the second period, hemolysis was the main rejection cause (36.2%), followed by non-received samples (34.5%) and clotted samples (11.1%). For urine samples, the main rejection cause overall was a non-received sample (up to 86.1% of cases in the second period, and 81.6% in the first). For blood samples with anticoagulant, the number of rejections also decreased. While plasma-citrate-ESR still showed the highest percentages of rejections (0.980% vs. 1.473%, p<0.001), the lowest corresponded to whole-blood EDTA (0.296% vs. 0.381%, p<0.001). CONCLUSIONS: For the majority of sample types, a decrease in preanalytical errors was confirmed. Improvements in organization, implementation of standardized procedures in the preanalytical phase, and participation in a Spanish external quality assessment scheme may have notably contributed to error reduction in this phase.

Harmonization in hemolysis detection and prevention. A working group of the Catalonian Health Institute (ICS) experience.

BACKGROUND: Hemolysis is the main cause of non-quality samples in clinical laboratories, producing the highest percentage of rejections in the external assurance programs of preanalytical quality. The objective was to: 1) study the agreement between the detection methods and quantification of hemolysis; 2) establish comparable hemolysis interference limits for a series of tests and analytical methods; and 3) study the preanalytical variables which most influence hemolysis production. METHODS: Different hemoglobin concentration standards were prepared using the reference method. Agreement was studied between automated methods [hemolytic indexes (HI)] and reference method, as well as the interference according to hemolysis degree in various biochemical tests was measured. Preanalytical variables which could influence hemolysis production were studied: type of extraction, type of tubes, transport time, temperature and centrifugation conditions. RESULTS: Good agreement was obtained between hemoglobin concentrations measured using the reference method and HI, for the most of studied analyzers, particularly those giving quantitative HI. The hemolysis interference cut-off points obtained for the majority of tests studied (except LDH, K) are dependent on the method/analyzer utilized. Furthermore, discrepancies have been observed between interference limits recommended by the manufacturer. The preanalytical variables which produce a lower percentage of hemolysis rejections were: centrifugation at the extraction site, the use of lower volume tubes and a transport time under 15 min at room temperature. CONCLUSIONS: The setting of interference limits (cut-off) for each used test/method, and the study of preanalytical variability will assist to the results harmonization for this quality indicator.

Laboratorio clínico 2.0 / Laboratory Medicine 2.0

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