Laboratory Instrumentation, Techniques and Diagnostic Accuracy
Domain focus
This domain tests spectrophotometry, centrifugation, pipetting, calibration, and the diagnostic accuracy concepts of sensitivity, specificity, predictive values and likelihood ratios used to judge laboratory tests.
Core rules
- Beer-Lambert law: absorbance is proportional to concentration and path length at a fixed wavelength.
- Centrifuge speed is expressed as relative centrifugal force, which depends on rotor radius and rpm.
- Air-displacement pipettes are calibrated gravimetrically and must be checked for leaks and tip fit.
- Sensitivity and specificity are intrinsic test properties; predictive values depend on prevalence.
- A positive predictive value falls when prevalence falls, even if sensitivity and specificity are unchanged.
Worked example
In a population of 1,000 people, 100 have disease. A test has 90% sensitivity and 95% specificity. True positives = 90; false positives = 45. PPV = 90 / (90 + 45) = 66.7%. The reasoning: despite good sensitivity and specificity, one-third of positive results are false because prevalence is only 10%. In a low-prevalence screening setting, confirm positive results.
Traps
- Reporting analytical sensitivity as diagnostic sensitivity.
- Using PPV without stating prevalence.
- Ignoring pipette temperature and viscosity during calibration.
- Comparing centrifuges by rpm only, not RCF.