PubMed · 16028472
The source did not provide an abstract. Follow the original record for more information.
Explore connections, maps & timelines
Chuck Millstein. 2005. The first ACA.. https://pubmed.ncbi.nlm.nih.gov/16028472/
Cite the original work for its findings. Save a collection to share your selection of sources.
KEEP EXPLORING
BACKGROUND: Integrated systems that combine clinical chemistry and immunoassay analyzers are used routinely. Sample to sample carryover is an inherent risk and can cause erroneously high patient test results for immunoassays. IVD manufacturers and laboratories must be aware of this phenomenon and guard against it. METHODS: We used a sample carryover protocol that directs the clinical chemistry module to process samples with very high immunoassay analyte concentrations followed by samples with very low concentrations for the same analyte. Low concentration samples were then tested by the immunoassay module to determine if the clinical chemistry module caused primary sample tube to primary sample tube carryover of the immunoassay analyte. RESULTS: Sample carryover was assessed on the Abbott ci8200 for HBsAg, AFP, beta-hCG, and PSA. Observed HBsAg carryover met the design specification of <0.1 ppm. Carryover for the other analytes was <0.1 ppm or below the assay limit of detection. CONCLUSIONS: IVD manufacturers must design integrated systems to minimize primary specimen tube carryover and avoid analytical laboratory error that can impact patient safety. Carryover testing is difficult for clinical laboratories to perform in order to verify system performance. Laboratories must consider the potential for specimen carryover and its impact on results whether moving primary sample tubes between separate analyzers or using an integrated system.
BACKGROUND: The use of nanotechnologies for diagnostic applications shows great promise to meet the rigorous demands of the clinical laboratory for sensitivity and cost-effectiveness. New nanodiagnostic tools include quantum dots (QDs), gold nanoparticles, and cantilevers. QDs, which are the most promising nanostructures for diagnostic applications, are semiconductor nanocrystals characterized by high photostability, single-wavelength excitation, and size-tunable emission. QDs and magnetic nanoparticles can be used for barcoding of specific analytes. Gold and magnetic nanoparticles are key components of the bio-barcode assay, which has been proposed as a future alternative to the PCR. METHODS: We examined articles published over the past 10 years investigating the use of QDs, gold nanoparticles, cantilevers, and other nanotechnologies in promising diagnostic applications. RESULTS: Several nanodiagnostic assays have been developed, including a QD-based assay capable of detecting biotinylated prostate-specific antigen (PSA) at 0.38 ng/L, a bio-barcode assay capable of detecting 30 amol/L PSA in a 10-microL sample, and another able to detect 50 molecules of the Alzheimer marker amyloid beta-derived diffusible ligand in 10 microL of cerebrospinal fluid. CONCLUSIONS: Nanodiagnostics promise increased sensitivity, multiplexing capabilities, and reduced cost for many diagnostic applications as well as intracellular imaging. Further work is needed to fully optimize these diagnostic nanotechnologies for clinical laboratory setting and to address the potential health and environmental risks related to QDs.
BACKGROUND: The reporting interval is the bin size used to report numerical pathology results and must be determined for every analyte. The influence of the size of the reporting interval on the critical difference (CD) between two results from the same patient has not been addressed previously. METHODS: The effect of changing the reporting-interval size (RIS) on CDs was modeled by use of a spreadsheet application. The findings were applied to data on CDs with analytical precision values from our laboratory. RESULTS: As the RIS increases relative to the combined analytical and within-person biological variation, there is an approximately linear increase in the CD from the value determined by use of published techniques. The revised estimate is as follows: CD = 2(1/2) x z x (SDa(2) + SDi(2))(1/2) + 1.5 x RIS, where CD, SD, and RIS are all in the same units. This effect is seen for any probability associated with the critical difference and for both uni- and bidirectional changes. CONCLUSIONS: The choice of reporting interval should be made in the light of assay requirements. Where there is a clinical need for detection of small changes in analyte concentration, the reporting interval should be kept small relative to the combined variation attributable to assay precision and within-person biological variation.