Researchers often decide whether to average multiple results in order to produce more precise data, and clinicians often decide whether to repeat a laboratory test in order to confirm its validity or to follow a trend. Some of the major sources of variation in laboratory tests (analytical imprecision, within-subject biological variation and between-subject variation) and the effects of averaging multiple results from the same sample or from the same person over time are discussed quantitatively in this article. This analysis leads to the surprising conclusion that the strategy of averaging multiple results is only necessary and effective in a limited range of research studies. In clinical practice, it may be important to repeat a test in order to eliminate the possibility of a rare type of error that has nothing to do analytical imprecision or within-subject variation, and for this reason, paradoxically, it may be most important to repeat tests with the highest sensitivity and/or specificity (i.e., ones that are critical for clinical decision-making).
[Show abstract][Hide abstract] ABSTRACT: The problem of medical errors has recently received a great deal of attention, which will probably increase. In this minireview, we focus on this issue in the fields of laboratory medicine and blood transfusion.
We conducted several MEDLINE queries and searched the literature by hand. Searches were limited to the last 8 years to identify results that were not biased by obsolete technology. In addition, data on the frequency and type of preanalytical errors in our institution were collected.
Our search revealed large heterogeneity in study designs and quality on this topic as well as relatively few available data and the lack of a shared definition of "laboratory error" (also referred to as "blunder", "mistake", "problem", or "defect"). Despite these limitations, there was considerable concordance on the distribution of errors throughout the laboratory working process: most occurred in the pre- or postanalytical phases, whereas a minority (13-32% according to the studies) occurred in the analytical portion. The reported frequency of errors was related to how they were identified: when a careful process analysis was performed, substantially more errors were discovered than when studies relied on complaints or report of near accidents.
The large heterogeneity of literature on laboratory errors together with the prevalence of evidence that most errors occur in the preanalytical phase suggest the implementation of a more rigorous methodology for error detection and classification and the adoption of proper technologies for error reduction. Clinical audits should be used as a tool to detect errors caused by organizational problems outside the laboratory.
[Show abstract][Hide abstract] ABSTRACT: Concentrations of inflammatory and hemostatic variables are influenced by biological variation, which is the natural within-subject variation over time.
The aim of this study was to determine fibrinogen, C-reactive protein (CRP), platelet aggregation, thrombin generation and prothrombin time (PT): (i) the number of repeated measurements needed to obtain the true habitual concentration of an individual; (ii) the recommended analytical imprecision for diagnosis and monitoring; (iii) the recommended analytical bias; (iv) the contribution of analytical imprecision to test result variability; (v) the index of individuality; (vi) the reference change value; and (vii) the seasonal variation.
We collected 520 blood samples over a 1-year period from 40 healthy individuals, and determined the between-subject, within-subject and seasonal variation in fibrinogen, CRP, platelet aggregation, thrombin generation and PT.
One or two repeated measurements were sufficient to establish the true habitual concentration, except for platelet aggregation and peak thrombin generation, where at least four and nine repeated measurements were needed, respectively. For diagnosis, the maximal recommended coefficient of analytical variation (CV) was 4%-27%, except for CRP (77.7%). For monitoring, these CVs were on average 3% lower. Recommended analytical bias varied between 1.7% and 33.2%. Finally, seasonal variation was observed in concentrations of fibrinogen and thrombin generation, which could explain approximately 11% of their total variation.
This study provides insights into the biological variability of selected inflammatory and hemostatic markers, which can be used for sample size calculations and to determine the analytical quality specifications for their respective assays.
Journal of Thrombosis and Haemostasis 07/2009; 7(8):1247-55. DOI:10.1111/j.1538-7836.2009.03488.x · 5.72 Impact Factor
Data provided are for informational purposes only. Although carefully collected, accuracy cannot be guaranteed. The impact factor represents a rough estimation of the journal's impact factor and does not reflect the actual current impact factor. Publisher conditions are provided by RoMEO. Differing provisions from the publisher's actual policy or licence agreement may be applicable.