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10 Cards in this Set
- Front
- Back
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Based on a normal distribution of quality control (QC) data, which description of a QC rule best represents imprecision? For each case, assume that the same QC material is used in one run.
a. Three sequential observations for a QC specimen that exceed 2 standard deviations from the target value in the same direction b. 10 sequential observations that fall between 3 and 4 standard deviations above the mean c. Eight sequential observations that exceed one standard deviation in the same direction from the target value d. Six sequential observations that all fall exactly one and a half standard deviation below the mean e. Two sequential observations with a range of four standard deviations between the two values |
e.Choice A represents systematic bias. Choices B and C represent both systematic bias and a trend. Choice D represents a shift and demonstrates excellent precision. Choice E represents a system demonstrating poor precision.
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Levey-Jennings chart represents the “low” glucose quality control whose mean has been established at 80 mg/dL (represented by the solid horizontal line). Values for 3 consecutive days of the run are indicated by the three asterisks. The dotted lines represent standard deviations (SD) above and below the mean and are labeled with the corresponding glucose value in mg/dL in parentheses. What is the probability that the event below occurred by chance alone?
a. 1:64,000 b. 1:32,000 c. 1:16,000 d. 1:8,000 e. 1:4,000 |
a.Another way of asking the same question is: “What is the probability that three consecutive values will fall greater than 2 SD above the mean or greater than 90 mg/dL?” This question can be viewed as a normal (Gaussian) distribution with a 95% confidence interval. The probability that one value will fall outside of this 95% confidence interval is 5%. However, the probability of one value falling greater than 2 SD above the mean is 2.5% (1/40). Therefore, the probability that three consecutive values will all fall greater than 2 SD above the mean is the product of each of the individual probabilities or (1/40)(1/40)(1/40) or 1 in 64,000. This event is not likely to occur by chance alone.
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Which of the following equations best describes the coefficient of variation?
A. Σxi/n B. Σ (xi-mean)2/(n-1) C. true positives/(true positives - false negatives) D. standard deviation/mean × 100 E. true positives/(true positives + false positives) |
D. standard deviation/mean × 100.
When discussing test results, the concepts of accuracy and precision are frequently encountered and are often confused. Accuracy refers to how close a particular value is to a gold standard reference value. Precision, however, is a description of how reproducible a particular result is. Precision can be mathematically expressed with the coefficient of variation, which compares the deviation from the mean to the mean value, expressed as a percentage. CV = SD/mean × 100. |
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Which of the following are affected by pre-test probability? (you can choose more than one)
A. sensitivity B. specificity C. positive predictive value D. negative predictive value E. relative risk |
C. positive predictive value, D. negative predictive value, E. relative risk.
Pretest probability is a function of the prevalence of a condition. When prevalence is high, the positive predictive value of a test is also usually high, while the negative predictive value is low. When the prevalence of a disease is low, the opposite occurs - low PPV, high NPV. The relative risk is also affected by prevalence in a similar fashion. |
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Which equation best describes sensitivity?
A. true positives divided by the sum of true positives plus false negatives B. true negatives divided by the sum of true negatives plus false positives C. true positives divided by the sum of true positives plus false positives D. true negatives divided by the sum of true negatives plus false negatives E. none of the above |
A. true positives divided by the sum of true positives plus false negatives.
It's easy to get overwhelmed with terms when sensitivity and specificity are brought up. In essence, the sensitivity of a test is the ability of a test to rule out (you can use the mnemonic, SnOUT) a disease. That is, a sensitive test is one that must be able to detect those that have the disease, so it makes sense that sensitivity is defined as the number of people who test positive divided by the number of people who actually have the disease (true positives + false negatives). As a result, a sensitive test is an excellent screening tool. On the other hand, a specific test is one that can “rule in” a disease (SpIN). Specificity is defined as the number of people who test negative for a disease divided by the number of people WITHOUT the disease (true negatives + false positives). For this reason, a specific test is best used as a post-screening test to differentiate false positives from true negatives. |
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What is the purpose of a receiver operating characteristic (ROC) curve?
A. to graphically determine the positive predictive value of a given test B. to calculate the standard deviation of a set of values C. to determine the prevalence of a particular condition D. to measure the ability of a test to perform reliably E. to determine the performance characteristics of a test at different cut-off values |
E. to determine the performance characteristics of a test at different cut-off values.
If you would have used the classic test-taking skill of choosing the longest answer, you would have nailed this one. If you didn't, maybe the explanation will help. Plotting sensitivity on the Y axis and 1-specificity on the X axis for a set of values, then connecting the values will generate a ROC curve. The purpose of the curve is to determine the specificity or sensitivity of a test at any given value. As sensitivity increases, specificity decreases (or 1-specificity increases), leading to a curve. The area under the curve is a function of the accuracy of the test. |
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What is the most standardized definition of the reference interval for a test?
A. +/- 1 SD of the mean B. +/- 2 SD of the mean C. +/- 3 SD of the mean D. sensitivity divided by specificity E. a value calculated from the ROC curve |
B. +/- 2 SD from the mean.
The central 95% of results (+/- 2 SD) obtained from healthy persons is most commonly used as the reference interval. This means that 5% of healthy individuals will have values that fall out of the reference interval. In addition, a particular reference interval many not apply to another population. |
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All of the following are categories of CLIA-regulated lab tests, except:
A. waived tests B. provider-performed microscopy C. low complexity testing D. moderate complexity testing E. high complexity testing |
C. low complexity testing.
Tests are listed in order of increasing CLIA regulation. Waived tests have the least regulation - follow manufacturer's instructions and good laboratory practices. Similarly, provider-performed microscopy, such as ferning tests must also follow the same guidelines. The vast majority of standard laboratory tests fall under the moderate complexity category. In addition to following the rules for waived tests, labs providing moderate complexity testing must have a standard operating procedure in addition to performing and documenting calibration, controls, and quality control. High complexity testing must adhere to the same rules as moderate complexity testing but must also document the validation of the assay, since most high complexity testing is created in house. |
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What is the purpose of a Levey-Jennings curve?
A. to calculate the mean of a new control sample B. to calculate the standard deviation of a new control sample C. to determine “in control” and “out of control” runs D. all of the above E. none of the above |
D. all of the above.
Test runs are made with a new control sample to create a Levey-Jennings plot and determine the mean and standard deviation. From then on, the control is run on a regular basis and the results are plotted on the Levey-Jennings plot created previously. The results of the plot are interpreted according to the Westgard rules to determine if a test is “in control” or “out of control”. |
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All of the following are shorthand for Westgard rules, except:
A. 1:3s rule B. 2:2s rule C. R:4s rule D. 4:1s rule E. 10:10s rule |
E. 10:10s rule.
The missing rule is the 10:mean rule. Each rule is a shorthand means of representation. The “s” in each stands for standard deviation, while the number preceding it stands for the number of values. For example, the 1:3s rule states, “Is one value + or - 3 SD from the mean?”, the 2:2s rule: “Are 2 consecutive values + or - 2 SD on the same side of the mean?” R:4s means, “Are any 2 values >4 SD from each other?” and 4:1s: “Are any 4 values >1 SD on the same side of the mean?”. Finally, the 10:mean rule asks, “Are any 10 values on the same side of the mean?” Any run that violates one of the Westgard rules is labeled as “out of control.” The results from this run should not be reported and the assay re-run. |
