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Lab Man > Chapter 7: Postanalysis > Flashcards

Chapter 7: Postanalysis Flashcards

1
Q

Indicate problem with the specimens or an issue with the result
Prevent the release of erroneous laboratory

A

Alarms and Flags

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2
Q

Additional Steps in Flagging Specimens

A
  • by automated instrument itself
  • by specialized middleware
  • by laboratory information system
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3
Q

Flags for Problem Specimen

A
  • sample contain amounts inadequate for reliable analysis

- presence of high concentration of interfering substances in the specimen

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4
Q
  • instrument that can often analyze more than 100 samples per hour
A

Automated Cell Counters

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5
Q

What type of samples can be reported immediately?

A

Normal Sample or Samples that show Quantitative Abnormalities

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6
Q

Flagged for preparation of blood smear and further evaluation

A

Samples that could contain qualitative abnormalities

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7
Q

What happens to an analyte concentration outside the validated linear range?

A
  • increase in signal linearity related to inc. in conc.
  • above the linear range, the machine dilutes and renanalyze sample
  • below LR, sample is reported as “less than the limit of detection”
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8
Q

The process of conparing a current laboratory result with results obtained on a previous specimen from the same patient

A

Delta Checks

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9
Q

Types of Errors Detected by Delta Checks

A
  • preanalytic and analytic issues
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10
Q

May not be readily detectable

Must be reported immediately to a healthcare provider

A

Critical Values

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11
Q

Required rapid communication of laboratory results

A

Federal Law, Regulatory Agencies, and Joint Commission

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12
Q

Develops a crticial values policy that meets the needs of the patients and staff served by the laboratory

A

Medical Director of the Laboratory

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13
Q

Definition of Reference Intervals

A

Laboratory Results vs Reference or Normal Range

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14
Q
  • Range of values into which 95% of non-diseased individuals will fall
  • *some of these analytes is defined as “greater than” or “less than” a certain value
  • some have been defined by prof. org. w/out adherence to the 95% rule
A

Reference Ranges

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15
Q

Does not require reference intervals except if the patient population was clearly distinct and exhibited range of values

A

Standardization

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16
Q

The Joint Committee for Traceability in Laboratory Machine establishes process for standardization by:

A
  1. Identifying
  2. Reviewing against agreed criteria
  3. Publishing list(s) of Higher Order Certified Reference Materials and Reference Measurement Procedures
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17
Q

Calibrating and using materials traceable to isotope dilution mass spectrometry reference measurement procedure

A

Reduce Interlaboratory Variability

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18
Q

Factors that Influence Reference Ranges

A 
Age
Genetic background
Exposure to environmental factors
Sample collection container
Sample transport
Time between specimen collection and analysis
Sample storage before analysis
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19
Q

Determination of Reference Ranges

A
  • Testing at least 120 SAMPLES from nondiseased individuals in each “partition”
  • Transference
  • Verication by another lab’s or the manufacturer’s reference interval if the analyte was not previously tested for the lab
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20
Q

Verification of a reference interval that was previously established for a different method

A

Transference

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21
Q

Result of assay imprecision

A

Analytic Variability

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22
Q

Due to biologic changes that cause analyte levels to fluctuate over time

A

Intraindividuality Variability

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23
Q

Occurs becauuse of factors specific to individual patients

A

Interindividuality Variation

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24
Q

The sum analytic and intraindividuality variability

A

Random Variability

25
Q

Used for disease classification (positive or negative)

A

Threshold

26
Q

Based on the results that are seen in 95% of the healthy population

A

Reference Range / Interval

27
Q

Determined by comparing test’s ability to discern true disease from nondisease

A

Diagnostic Accuracy

28
Q

Used to discern true disease from nondisease

A

Diagnostic Gold Standard

29
Q

The non-overlapping areas of the two patient distribution.

A

True Results

30
Q

Classified as Abnormal

A

True Positive (TP)

31
Q

Classified as Normal

A

True Negative (TN)

32
Q

Used to discriminate disease from normal populations

A

Single Cutoff

33
Q

The overlapping areas of the two patient distribution

A

False Results

34
Q

INCORRECTLY classified as NORMAL

A

False-Negative (FN)

35
Q

INCORRECTLY classified as ABNORMAL

A

False-Positive (FP)

36
Q

The error of True Positive

A

False-Negative

37
Q

The error of True Negative

A

False-Positive

38
Q

Measures of diagnostic accuracy

Indicators in distinguishing the presence and absence of disease at a chosen cutoff

A

Sensitivity and Specificity

39
Q

● The ability of a test to detect disease.
● The proportion of persons with the disease.
● TRUE POSITIVE (TP)
● Identifies a greater proportion of persons with the disease.

A

Sensitivity

40
Q

● The ability of a test to detect the absence of disease
● The proportion of persons without the disease.
● TRUE-NEGATIVE (TN)
● Excludes a greater proportion of persons without the disease.

A

Specificity

41
Q

Effect of Altering the Test Cutoff

A

● Altering the cutoff changes a test’s sensitivity and
specificity.
● An inverse relationship between SENSITIVITY
AND SPECIFICITY is noted.

42
Q

For tests where high values indicate disease,
lowering cutoff (cutoff line moved to the left)
will lead to more diseased patients being
classified as abnormal.

A

HIGH SENSITIVITY

43
Q

If the cutoff is raised (the cutoff line moved to the
right), more non-diseased patients are classified
correctly.

A

HIGH SPECIFICITY.

44
Q

The Need for High Sensitivity vs High Specificity

A

● False results such as FP (false-positive) and FN
(false-negative) can lead to misdiagnosis and
inappropriate clinical management.
● SENSITIVITY should be HIGH to capture the
majority of cases. (Lowering cutoff)
● SPECIFICITY can be INCREASED to exclude all
persons without the disease. (Increasing cutoff).

45
Q

 sometimes referred to as positive predictive
value
 may be understood as the probability that a positive test indicates disease
 it is the proportion of persons with a positive
test who have truly the disease.

A

PREDICTIVE VALUE OF A POSITIVE TEST

46
Q

 Referred to as negative predictive value
 Is the probability that a negative test indicates
absence of disease
 It is the proportion of persons with a negative test who are true without disease

A

PREDICTIVE VALUE OF A NEGATIVE TEST

47
Q

Relationship of Prevalence and Posttest Probability

A

The higher the prevalence, or pretest probability, the higher the posttest probability, or predictive value of a positive test.

48
Q
  • Shows that sensitivity and specificity influence the predictive value.
  • Describes the relationship between posttest and pretest probability of disease or no disease based on the sensitivity and specificity of the test
A

Bayes Theorem

49
Q

Also known as priori probability, is the prevalence of the disease in the patient’s clinical setting
- used in conjunction with the characteristics of diagnostic accuracy as summarized in the sensitivity and specificity of the test.

A

Pretest probability

50
Q

Also known as posteriori probability, is the probability of disease in the posttest situation and is commonly referred to as the predictive value of the test.

A

Posttest probability

51
Q

● A convenient measure that combines sensitivity
and specificity into a single number
specificity into a single number.
● An assessment of test performance, and not of
disease status, in the patient being tested.

A

Likelihood Ratio

52
Q

The LR+ is the ratio of two probabilities: the probability of a positive test result when the disease is present (TP) divided by the probability of the same test result when the disease is absent (FP).

A

Likelihood Ratio of a positive test (LR+)

53
Q

A convenient graphic tool that uses a logarithmic
scale to determine posttest probability, given
the LR at a specified cutoff and the pretest
probability

A

FAGAN NOMOGRAM

54
Q

a useful tool for identifying the optimal cutoff
for a diagnostic test by calculating
the sensitivity and specificity combinations
across the entire range of cut off values

A

RECEIVER OPERATOR CHARACTERISTIC CURVE

55
Q

a method that allows one to assess the optimal cutoff
with numeric estimates for clinical impact, or
consequences, of test results.

A

POSITIVITY CRITERION

56
Q

• Is a process by which medical decision can be
made by using as many objective tools as
possible.
• Can help to reduce the uncertainty of medical
decision making.

A

EVIDENCE-BASED MEDICINE

57
Q

5 Steps of EBM

A
  1. Ask a clinical question based on a patient
    encounter
  2. Acquire information by searching for resources
  3. Analyze and critically evaluate the information and reach a conclusion
  4. Apply the information to individual patients
  5. Audit effectiveness and monitor the literature
58
Q

The clinical question can be described in four parts with

acronym of PICO

A
  • Problem
  • Intervention
  • Comparison
  • Outcome

Lab Man (9 decks)

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