Clin Lab - 4.2 Quality Assurance and Control

What are some things that can effect reference ranges?

•Age, gender, and geographic location are examples of factors that affect reference ranges

Problems Resulting from Test Errors: False Positives? False Negatives?

•False Positives can arise due to other factors (such as taking other medications, diet, etc.) They entail the cost and danger of further investigations, labeling, worry for the patient. •False Negatives imply missed cases, so potentially bad outcomes if left undetected or untreated

•A pregnancy test that classifies people as pregnant (positive) or not pregnant (negative): - a person we told is pregnant that really was. - a person we told is not pregnant, and really wasn't. - a person we told is not pregnant, though they really were. Ooops. - a person we told is pregnant, though they weren't. Oh snap.

-True positive -True negative -False negative -False positive

Another Picture Explain Sensitivity

Another Picture Explain Sensitivity

Pathological range diagnoses?

Disease

Functional range assesses risk for?

Disease before the disease develops

Reference ranges are also referred to as? •Established by testing a significant number of __________ individuals -Statistics applied by use of a _________ (normal) distribution curve -Approximately _______% of clinically normal individuals will have test results that fall within + 2 SD

Normal Ranges healthy Gaussian distribution curve 95%

Pic of Table for Validating a test WILL BE ON TEST

Pic of Table for Validating a test WILL BE ON TEST

A test that is more ________ will result in fewer false-negative results.

Sensitive

what is the specificity formula?

Specificity = TN / (FP + TN) * 100

What is the sensitivity formula?

TP / (TP + FN) *100

Specificty is proportion of cases with _________of the disease / condition that gives a ________ result. The assay correctly excludes with a negative result.

absence negative •Example: A certain test is 90% specific -If 100 people are healthy, the test will identify as "normal" 90 of those 100 cases (90%). -The other 10 people (10%) tested will show a "positive" result which is termed false-positive. -The probability of the screening test correctly identifying non-diseased subjects was 90%." -The more specific a test, the fewer false-positive results will be produced.

Sensitivity is defined as?

•The proportion of cases with a specific disease/condition that give a positive test result. Examples: -If 100 people have a certain disease, the test will correctly identify 90 of those 100 cases (90%). -The other 10 people (10%) tested will show a "normal" result which is termed false-negative. -"The probability of the screening test correctly identifying diseased subjects was 90%." -The more sensitive a test, the fewer false-negative results will be produced