Term
| How does EDTA and citrate differ in their effects on calcium? |
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Definition
EDTA chelates calcium (attaches in 6 places)
citrate* forms an ionic bond with calcium
**this is also the mechanism of anti-coagulant action of oxalates |
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Term
| What is the major mechanism through with heparin inhibits coagulation? |
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Definition
activation of antithrombin
**heparin also inhibits activity of other coagulation factors (including thrombin, factor 2a) and inhibits Ca via ionic bonding, but these effects are less pronounced than the activation of antithrombin |
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Term
| What is the first rule of significant figures? |
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Definition
Retain only 1 uncertain figure
**using appropriate significant figures helps to distinguish biologically significant changes in analytes from those associated with the inherent imprecision of the assay |
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Term
| What are the ideal/adequate numbers of individuals to generate population based reference intervals? What is the absolute minimum number? |
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Definition
| 120 is ideal, 60 is adequate, 40 is the minimum |
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Term
| What proportion of the total reference population do reference intervals represent? |
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Definition
the center 95%
** If the data is normally (gaussian) distributed it represents the mean +/- 2 SD, if the data is skewed then nonparametric methods must be used to calculate the center 95% and the mean +/- 2 SD will not be accurate |
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Term
| With regards to ROC curves what is the true positive rate equivalent to? False positive rate? |
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Definition
True positive rate = diagnostic sensitivity
False positive rate = 1 - diagnostic specificity |
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Term
| How should you interpret a 45 degree slope on a ROC curve? |
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Definition
| the test is no better at classifying individuals as diseased or healthy than random classification |
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Term
| What does the ROC curve plot? |
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Definition
| true positive rate against false positive rate |
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Term
| What is the definition of analytical precision? |
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Definition
aka reproducibility, the ability of an assay to get the same result if the sample is analyzed several times, expressed as CV (SD/mean)
**if there is poor analytical precision there is random error. There can be some acceptable random error as long as the analyte measured doesn't has a relatively high degree of biologic variation. If an analyst is very tightly regulated in serum the analytical imprecision can complicate interpretation of seemingly biologically relevant changes in analyte concentration. |
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Term
| How is analytical precision (reproducibility) evaluated in the lab? |
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Definition
Repeated analysis of control solutions enables assessment of precision
*control solution can be a solution in which the analyte's concentration is known (e.g. standard) but more frequently the concentration of the control solution is determine by multiple measurements of a sample/pool by the assay being assessed. |
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Term
| How is analytical precision typically expressed? |
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Definition
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Term
| Within the analytical range of an assay, CVs are typically higher at lower or upper analyte concentrations? |
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Definition
CVs are typically highest at lower concentrations
**If SD remains constant at all analyte concentrations |
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Term
| How can usual standard deviation be used to asses wether changes in an analytes' concentration reflect significant biologic change as opposed to changes secondary to analytical variation? |
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Definition
Usual standard deviation (USD)
* USD is an average of SD from the last 3-6 months of QA values. If the change in the patient sample is >3x the USD it is probably due to a true biologic change |
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Term
| What is the definition of analytical accuracy? |
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Definition
Analytical accuracy is the closeness of the agreement between the measured value of an analyte and its true value
**methods of establishing the "true" value of an analyte vary considerably. May be the method obtained using a gold standard, or mean concentration determine by numerous observations by the best available method |
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Term
| What is the definition of analytical specificity? |
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Definition
| analytical specificity is the ability of an assay to detect only the substance of interest e.g. how susceptible is the assay to interfering substances |
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Term
| What is the definition of the detection limit? |
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Definition
Detection limit is the smallest concentration or quantity of an analyte that can be detected with reasonable certainty for a given analytical range, it defines the lowest value of an assay's analytical range.
**a low detection limit is necessary for analytes in which only small amounts are typically measured |
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Term
| What is analytical sensitivity and how does it differ from the detection limit? |
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Definition
Analytical sensitivity describes how well an assay can detect actual changes in analyte concentration, across the entire analytical range
*vs. detection limit applies only the the lowest limit of the analytical range. They are related concepts because both relate to small changes in concentration. |
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Term
| Which of the Wesgard rules for QA more best at detecting systematic error? |
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Definition
2S2 rule- run is rejected when two consecutive control measurements exceed, the same mean + 2SD or the same mean - 2SD, of previous control sample values
41S rule- a run is rejected when four consecutive control measurements exceed the same mean + 1 SD, or the same mean - 1SD
10x rule- a run is rejected when 10 consecutive control measurements fall on one side of the mean |
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Term
| Which of the Wesgard rules for QA more best at detecting random error? |
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Definition
13s rule- a run is rejected when a single QC measurement exceeds the mean +/- 3SD of previous control samples
R4s rule- a run is rejected when one control measurement in a group exceeds the mean + 2SD and another exceeds the mean - 2SD |
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Term
| What type of graph is typically used to evaluate the performance of QC material? |
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Definition
| Levey-jennings control charts |
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Term
| How can you determine what # sigma an assay is on the basis of the total allowable error of the assay and the SD of the analyte concentration near levels of significant clinical decision making? |
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Definition
divide total allowable error by SD at clinical decision point to determine the sigma of an assay
e.g. TEa= 10mg/dl, SD at clinical decision point is 5mg/dl, the assay is a 2 sigma assay, relatively imprecise so stringent QA procedures (e.g. westward rules) would need to be used to detect unacceptable errors that could be mistaken for true biologic changes
vs. TEa= 10mg/dl, SD @ clinical decision making point is 2 mg/dl, this is a 5 sigma assay. Less stringent QA procedures could be used because it is unlikely that random errors would create clinically relevant changes in analyte concentration |
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Term
| What is the difference between CLSI (clinical laboratory standards institute) and bland-altman bias plots? |
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Definition
For both the difference between the new and old (reference) method are plotted on the Y axis.
For CLSI plot: the results obtained using the old (reference) method are plotted on the X axis
For Bland-Altman: the mean of results obtained by both methods are plotted on the X axis. This plot does NOT assume that the old (reference) method is more accurate. |
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Term
| What is the difference between deming regression method comparison and passing bablok method comparison? |
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Definition
| Deming regression assumes that the imprecision of the assays is normally distributed |
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Term
| What technique can be used to assess agreement between semi-quantitative methods (e.g. 1+, 2+, mild, moderate)? |
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Definition
Kappa agreement
*calculated Kappa value provides a guide to the degree of agreement between methods, if a weighted kappa method is use the degree of disagreement between methods is also calculated |
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Term
| What is the definition of diagnostic sensitivity? How can you calculate it? |
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Definition
The frequency with which the diagnostic test is positive in animals that actually have the disease of interest
*very few false negative results
Dx sensitivity = true test positive/ true test positive + false negative |
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Term
| With regards to diagnostic sensitivity/specificity, maximization of which of these properties is ideal for a screening test (screening for the presence of disease)? |
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Definition
| High diagnostic sensitivity is ideal for use as a test to screen for the presence of disease |
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Term
| What is the definition of diagnostic specificity? How can you calculate it? |
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Definition
diagnostic specificity is the frequency in which a test is negative, in patients that do not have the disease. *very few false positives
dx specificity= true negative/ true negative + false positive |
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Term
| With regards to diagnostic sensitivity/specificity, maximization of which of these properties is ideal for a confirmatory test ? |
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Definition
| High diagnostic specificity (few false positives), if the result is positive, there is a high likelihood that the patient has the disease in question |
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Term
| What is the difference between analytical accuracy and diagnostic accuracy? |
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Definition
analytical accuracy describes the performance of an assay in representing the true value of the analyte being measured (often challenging to truly assess because gold standards are few in veterinary medicine)
diagnostic accuracy describes the performance of an assay in identifiying true positive and true negative disease status in patients |
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Term
| What is the definition of diagnostic accuracy and how can you calculate it? |
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Definition
diagnostic accuracy is the frequency at which the test correctly identifies true positives and true negatives
diagnostic accuracy= true test positive + true test negative/ all animals tested |
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Term
| What is the definition of the positive predictive value of a test? How is it calculated? |
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Definition
Positive predictive value is the likelihood that an animal with a positive test result actually has the disease
positive predictive value = true positive / true positive + false positive |
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Term
| What is the definition of the negative predictive value of a test? How is it calculated? |
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Definition
Negative predictive value is the likelihood that an animal with a negative test result really does not have the disease
negative predictive value = true negative / true negative + false negative |
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Term
| How does disease prevalence affect the likelihood of false positive or false negative results? |
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Definition
Low prevalence of disease increases the likelihood of false positives, high prevalence increases the likelihood of false negatives
Another way to say this is when there is low disease prevalence the positive predictive value of a test decreases and when there is high disease prevalence the negative predictive value decreases. |
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Term
| What does the area under the curve of a ROC curve specify? |
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Definition
| the diagnostic accuracy of the test, that is with a larger area under the curve, the test has a higher diagnostic accuracy |
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Term
| What is the minimum number of individuals to sample that could still provide valuable herd-based test results (regardless of herd size)? |
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Definition
7-12 animals
**although greater numbers of test individuals would provide results with tighter confidence limits. Remember, individuals to be tested must belong to defined groups of similar age, lactation state, environmental conditions and nutritional management. |
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Term
| What analytes can be valuable when assessing energy balance in herd-based testing for cattle? |
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Definition
low HCT (early-mid lactation)
high beta-hydroxybutyrate (early-mid lactation)
high nonesterified fatty acids (2-14days prior to calving)
**serum [urea] can always be used to assess ruminal balance of energy and available protein
***because these tests are being done in healthy animals to attempt to identify subclinical disease results are often within reference intervals. Data can be evaluated by comparing mean herd values to mean values from a reference herd, established expelled means for the group of interest, plotting running graphs to look for changes over time etc. |
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Term
| What is the minimum number of individuals that should be sampled for generation of RI when the distribution of results for most analytes is gaussian? |
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Definition
minimum of 40 individuals (100+ is preferred)
*in this case RI is mean +/- 2 SD, aka 95% confidence interval. If less than 40 individuals are available the upper and lower values measured should me used to create an estimated RI. |
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Term
| How should reference intervals be generated for analytes that don't display a gaussian distribution? |
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Definition
data can be transformed to approximate gaussian distribution (at mean +/- 2SD / 95% confidence intervals determined)
or
percentiles are used (esp. if a large population is sampled) to determine upper [(n+1) x 0.975] and lower [(n+1) x 0.025] limits of RI |
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Term
| What is the definition of disease prevalence? |
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Definition
the percentage of animals in a given population that have a certain disease
(TP+FN)/ (TP+TN+FP+FN) |
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Term
| What type of error does CV represent? |
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Definition
Random error
**CV is SD/mean x 100 |
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Term
| What is critical difference and how does it relate to test interpretation? |
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Definition
Critical difference is calculated from the CV of an assay with the intra-individual CV for an assay.
e.g. automated TWCC has a CV of 3.7%, intra-individual CV for TWCC in healthy lab beagles is 12.1%, and the calculated critical difference is 35%
This means that TWCC has to change be 35% or more to represent a true biologic change |
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