Questions and Answers
What does diagnostic sensitivity measure?
Why is high sensitivity important for screening tests?
What does diagnostic specificity indicate?
In diagnostic accuracy, what represents true positives (TP)?
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What is the formula used to calculate sensitivity?
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What does a test with 100% specificity indicate?
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Which parameter indicates the number of cases incorrectly identified as patients?
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What does the accuracy of a diagnostic method depend on?
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Which type of tests require high specificity?
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What does a receiver operator characteristic (ROC) curve compare?
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What is the primary purpose of intralab quality control?
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How are initial control limits established in quality control?
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What indicates that an analytical result cannot be reported?
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What is the benefit of using blind control samples in internal QC testing?
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Which statement about systematic and random errors during quality control is true?
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What is maintained by the analyst after each quality control run?
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What do control samples analyze alongside?
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Which of the following is a key outcome of intralab quality control?
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Why are control samples prepared at two levels during internal QC?
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What program is used to check QC results after each run?
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Study Notes
Diagnostic Sensitivity
- Diagnostic sensitivity measures the test's ability to correctly identify individuals with a disease, yielding valid true-positive results while minimizing false-negative results.
- High sensitivity is crucial for screening tests to ensure no cases are missed.
- Sensitivity can be calculated as:
Sensitivity (%) = (Total number of diseased individuals with positive test result / Total number of diseased individuals tested) × 100
Diagnostic Specificity
- Diagnostic specificity indicates the test's ability to correctly identify individuals without the disease, leading to true-negative results and few false-positive outcomes.
- High specificity is essential for confirmatory tests that validate diagnoses.
- Specificity can be calculated as:
Specificity (%) = (Total number of individuals without disease with negative test result / Total number of individuals tested without disease) × 100
Diagnostic Accuracy
- Accuracy reflects the method's overall ability to distinguish between diseased and healthy individuals using the proportion of true positives (TP) and true negatives (TN).
- Accuracy incorporates both TP and TN along with false positives (FP) and false negatives (FN):
Accuracy = (TP + TN) / (TP + TN + FP + FN)
Key Terminology
- True Positive (TP): Correctly identified cases of disease.
- False Positive (FP): Incorrectly identified cases as having the disease.
- True Negative (TN): Correctly identified healthy cases.
- False Negative (FN): Incorrectly identified healthy cases.
Quality Control Objectives
- Quality control is intended to ensure:
- Stability of the testing machine.
- Quality of reagents used in testing.
- Minimization of technical (operator) errors.
Types of Quality Control
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Intralab Quality Control (Internal QC):
- Involves analyzing control samples alongside patient specimens.
- Detects performance changes from standard operations, essential for daily accuracy and precision monitoring.
- Identifies both random and systematic errors in testing.
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Internal QC employs blind control samples mixed with patient specimens, typically prepared at two levels representing various patient sample types.
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Initial control limits are determined by analyzing a pool over 20 consecutive runs, with periodic reevaluation.
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Results cannot be reported for any analyte declared as "out of control" after internal QC testing.
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A multi-rule quality control program is used for checking QC results after each test run, with hard copies maintained by the analyst.
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Description
Test your understanding of diagnostic sensitivity and specificity. This quiz covers the definitions, importance, and calculations associated with these critical concepts in medical testing. Understand how sensitivity and specificity impact screening tests and disease detection.
