Karteikarten
Diagnostic testing
Karten in diesem Stapel (30)
- 1What are the 4 major reasons for analysing patient samples via lab procedures1 - detect unidentified pathologic state
2 - define, classify, confirm pathophysiological disorder or disease state
3 - eliminate a possible cause of animal's illness
4 - assess changes in pathologic state either due to natural progression of disease or due to medical/surgical therapy - 2What are reference intervals- results we expect to find in healthy animals
- used to help detect pathologic state - 3What are the 8 conditions needed to create a reference interval1 - reference individual
2 - reference population
3 - reference sample group
4 - reference value
5 - reference distribution
6 - reference limit
7 - reference interval
8 - observed value - 4What are reference individuals- fulfill selection criteria
- healthy individuals - 5What is the reference population- all potential reference individuals
- from which the reference individuals are selected to represent a sample of this - 6What is the reference sample groupneeds to be high numbers
60+ - 7What is the reference valuemeasured value
- 8What is the reference distributionGaussian or non Gaussian if running 60/120 patients
- can look at distribution - whether bell shaped curve or skewed - 9What are reference limits- upper and lower limits of centre
- to include 95% of normal individuals - 10What is a reference interval- covers 95% of healthy individuals
- 11What is an observed valuepatients value
compare to reference interval - 12What is gaussian distributionbell shaped curve
use mean +/- standard deviations - 13What is positively skewed distribution- skewed central 95%
- cannot use mean +/- SD
- use 95th percentiles - 14What is reliability- send sample tell result take as the be all and end all
- when actually shades of grey and degrees of probability - 15What is intra-individual variabilityindividual variation
e.g. how one individuals blood glucose changes over time - 16What is inter-individual variability- can be low or high
- between different individuals - 17What conditions are needed for the ideal reference individual in a population based reference interval- inter-individual variability = low
- intra - individual variability = high - 18What happens if both inter individual and intra individual variability are both lownarrow reference interval
not commonly theoretically possible - 19How is a reference population chosen- need each breed in ideal world
- most labs have general dog
- some specific for greyhounds
- in general pop - may want to exclude greyhounds- outliers that widen reference interval - 20What are major determinants in quality of lab results and give the 3 important factors- lab test results will be of the most benefit if they are consistently correct
1 - quality of sample - pre analytical
2 - quality of analysis
3 - quality of lab and patient records - post analytical - 21What are the analytical properties of assays and give the 5 important factors- quality of analysis, how good the assay will perform
1 - analytical precision (reproducible)
2 - analytical accuracy (closeness to true value)
3 - analytical specificity (substance of interest)
4 - detection limit (smallest reliably detected)
5 - analytical sensitivity (smallest change) - 22What does diagnostic sensitivity and specificity depend onwhether have true positives or false positives
- 23What is analytical specificity and how does it differ from analytical sensitivityspecificity - measuring the right thing e.g. wbc count lacks specificity - measures nucleated RBC
sensitivity - smallest amount of change you can reliably detect - 24What is diagnostic sensitivity- the number of true positives out of animals that have disease
- if run tests on diseased animals how often does it give a positive result
- true positives/ (true positives + false negatives) x100
- how many test positive out of all sick animals - 25What is diagnostic specificity- number of true negatives out of all animals that do not have disease
- true negative/ (true negative+ false positive) x100
- how specific assay is that do not have disease - 26What is diagnostic accuracy- most difficult to fulfil
- number of correctly classified animals across whole study
- (true positives + true negatives)/ (true positives + false positive + true negative + false negative) x 100 - 27What is the positive predicted value- number of true positives out of all positive results
- true positives/ (true positives + false positives) x 100 - 28What is the negative predictive value- number of true negative out of all negative results
- true negative/ (true negatives + false negatives) x100 - 29What is needed if have to design study to learn diagnostic sensitivity- animals with the disease
- use different methods
- gold standard = PM or different well established test - 30What is needed if have to design study to learn diagnostic specificity-
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- BSc Pathology Applications Karteikarten am Diagnostic testing, erstellt von Teresa Richards am 15/12/2016.
- Erstellt von
- Teresa Richards
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