Preanalytical mistakes in samples from primary care patients.

BACKGROUND Preanalytical mistakes (PAMs) in samples usually led to rejection upon arrival to the clinical laboratory. However, PAMs might not always be detected and result in clinical problems. Thus, PAMs should be minimized. We detected PAMs in samples from Primary Health Care Centres (PHCC) served by our central laboratory. Thus, the goal of this study was to describe the number and types of PAMs, and to suggest some strategies for improvement. METHODS The presence of PAMs, as sample rejection criteria, in samples submitted from PHCC to our laboratory during October and November 2007 was retrospectively analysed. RESULTS Overall, 3885 PAMs (7.4%) were detected from 52,669 samples for blood analyses. This included missed samples (n=1763; 45.4% of all PAMs, 3.3% of all samples), haemolysed samples (n=1408; 36.2% and 2.7%, respectively), coagulated samples (n=391; 10% and 0.7%, respectively), incorrect sample volume (n=110; 2.8% and 0.2%, respectively), and others (n=213; 5.5% and 0.4%, respectively). For urine samples (n=18,852), 1567 of the samples were missing (8.3%). CONCLUSIONS We found the proportion of PAMs in blood and urine samples to be 3-fold higher than that reported in the literature. Therefore, strategies for improvement directed towards the staff involved, as well as an exhaustive audit of preanalytical process are needed. To attain this goal, we first implemented a continued education programme, financed by our Regional Health Service and focused in Primary Care Nurses.

Sources of pre-analytical variations in yield of DNA extracted from blood samples: analysis of 50,000 DNA samples in EPIC.

The European Prospective Investigation into Cancer and nutrition (EPIC) is a long-term, multi-centric prospective study in Europe investigating the relationships between cancer and nutrition. This study has served as a basis for a number of Genome-Wide Association Studies (GWAS) and other types of genetic analyses. Over a period of 5 years, 52,256 EPIC DNA samples have been extracted using an automated DNA extraction platform. Here we have evaluated the pre-analytical factors affecting DNA yield, including anthropometric, epidemiological and technical factors such as center of subject recruitment, age, gender, body-mass index, disease case or control status, tobacco consumption, number of aliquots of buffy coat used for DNA extraction, extraction machine or procedure, DNA quantification method, degree of haemolysis and variations in the timing of sample processing. We show that the largest significant variations in DNA yield were observed with degree of haemolysis and with center of subject recruitment. Age, gender, body-mass index, cancer case or control status and tobacco consumption also significantly impacted DNA yield. Feedback from laboratories which have analyzed DNA with different SNP genotyping technologies demonstrate that the vast majority of samples (approximately 88%) performed adequately in different types of assays. To our knowledge this study is the largest to date to evaluate the sources of pre-analytical variations in DNA extracted from peripheral leucocytes. The results provide a strong evidence-based rationale for standardized recommendations on blood collection and processing protocols for large-scale genetic studies.