Test Diagnostics: Difference between revisions
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For example, the [[Hawkins / Kennedy Test|Hawkins-Kennedy test]] for subacromial impingement has been reported by some to have a specificty of 1.00, or 100%. A positive test result is very likely include those people who have impingement. | For example, the [[Hawkins / Kennedy Test|Hawkins-Kennedy test]] for subacromial impingement has been reported by some to have a specificty of 1.00, or 100%. A positive test result is very likely include those people who have impingement. | ||
=== Predictive values === | |||
Predictive values reflect the proportion of patients with a positive or negative result that are correct results. <ref name=":0" /> These statistics are calculated horizontally from the 2x2 table. The positive predictive value represents the proportion of patients with a positive test result who actually have the condition i.e. A/(A+B), whereas the negative predictive value refers to the proportion of patients who have a negative test result and not the condition i.e. D/(C+D). <ref name=":0" /> | |||
=== Likelihood Ratios === | === Likelihood Ratios === | ||
Revision as of 10:58, 26 May 2022
Original Editor - Tyler Shultz
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Purpose[edit | edit source]
The purpose of this page is to provide users of Physiopedia a quick reference to commonly used diagnostic statistics in physical therapy practice. These statistics are often used to describe the effectiveness of special tests in identifying specific disorders. Knowing the diagnostic accuracy of special tests is important in obtaining an accurate diagnosis, and in turn maximizing treatment outcomes. [1]
Diagnosis in Physical Therapy Practice[edit | edit source]
Physical therapists use the diagnosis of specific conditions to guide their treatment options. Through the physiotherpy assessment, clinicians gather data to evaluate and form clinical judgements. [1] The diagnostic process begins with aquiring relevant data from the history and physical examination. Some data may be used to focus the examination on a specific part of the body, other to identify a specific pathology and some to select an appropriate intervention. [1]
Diagnostic accuracy[edit | edit source]
Determining the diagnostic accuracy i.e. sensitivity and specificity of a test is the first step in the evaluation of a diagnostic test.[2] This is accomplished by comparing the performance of the test in question with a reference or "gold" standard in a 2x2 contigency table. [2]
| 2X2 Table | Reference test positive result | Reference test negative result |
|---|---|---|
| Diagnostic test positive | True positive results
A |
False positive results
B |
| Diagnostic test negative | False negative results
C |
True negative results
D |
Sensitivity[edit | edit source]
Sensitivity is defined as the ability of a test to identify patients with a particular disorder.[3] In other words, it represents the proportion of a population with the target disorder that has a positive result with the diagnostic test i.e A/(A+C). [4] Tests that are highly sensitive are most useful for ruling out a disorder, as people who test negative are more likely not to have the target disorder. "SnNout" is an acronym that can be used to remember that a highly sensitive test and a negative result is good for ruling out the disorder in question.[5]
For example, the Neers Test has been reported to have a sensitivity rating of 0.93 for detecting subacromial impingement. So, if the test is negative, the examiner can be confident that the patient does not have impingement.
Specificity[edit | edit source]
Specificity is the ability of a test to identify patients that do not have the disorder in question.[6] In other words, specificity is the proportion of the population without the target disorder who test negative for the disorder i.e D/(B+D).[7] Therefore, tests that are highly specific are useful for ruling in a disorder. The acronym "SpPin" is commonly used to remember that a test with high specificity and a positive result is good for ruling in a disorder.[8]
For example, the Hawkins-Kennedy test for subacromial impingement has been reported by some to have a specificty of 1.00, or 100%. A positive test result is very likely include those people who have impingement.
Predictive values[edit | edit source]
Predictive values reflect the proportion of patients with a positive or negative result that are correct results. [1] These statistics are calculated horizontally from the 2x2 table. The positive predictive value represents the proportion of patients with a positive test result who actually have the condition i.e. A/(A+B), whereas the negative predictive value refers to the proportion of patients who have a negative test result and not the condition i.e. D/(C+D). [1]
Likelihood Ratios[edit | edit source]
Likelihood ratios are an index measurement that combines the sensitivity and specificty values of a specific test. Likelihood ratios can be used to gauge the performance of a diagnostic test, as it indicates how much a given diagnostic test will lower or raise the pretest probability of the target disorder.[9]
- Positive likelihood ratio (+LR) is the proportion of people who test positive and actually have the disorder. In other words, +LR indicates the shift in probability that favors the existence of a disorder.[10] +LR is usually calculated by: +LR = Sensitivity / (1 - Specificity)
- Negative likelihood ratio (-LR) is the proportion of people who test negative and who do not actually have the disorder. Or, a test with a -LR indicates the shift in probability that favors the absence of the disorder.[11] -LR is usually calculated by: -LR = (1 - Sensitivity)/Specificity
| +LR | -LR | Interpretation |
| > 10.0 | < 0.1 | Generate large and often conclusive shifts in probability |
| 5.0 - 10.0 | 0.1 - 0.2 | Generate moderate shifts in probability |
| 2.0 - 5.0 | 0.2 - 0.5 | Generate small, but sometimes important shifts in probability |
| 1.0 -2.0 | 0.5 - 1.0 | Alter probability to a small and rarely important degree |
Resources[edit | edit source]
STARD Statement for Reporting Diagnostic Accuracy Studies
References[edit | edit source]
- ↑ 1.0 1.1 1.2 1.3 1.4 Fritz J, Wainner R. Examining diagnostic tests: an evidence - based perspective. Phys Ther 2001; 81(9):1546-1564.
- ↑ 2.0 2.1 Fardy J, Barrett B. Evaluation of diagnostic tests. Methods Mol Biol 2015; 1281:289-300.
- ↑ Sackett, D.L., Straws, S.E., Richardson, W.S., et al. (2000) Evidence-based medicine: How to practice and teach EBM.(2nd ed.) London: Harcourt Publishers Limited.
- ↑ Dutton, M. (2008). Orthopaedic: Examination, evaluation, and intervention (2nd ed.). New York: The McGraw-Hill Companies, Inc.
- ↑ Flynn, T.W., Cleland, J.A., Whitman, J.M. (2008). User's guide to the musculoskeletal examination: Fundamentals for the evidence-based clinician. Buckner, Kentucky: Evidence in Motion
- ↑ Sackett, D.L., Straws, S.E., Richardson, W.S., et al. (2000) Evidence-based medicine: How to practice and teach EBM.(2nd ed.) London: Harcourt Publishers Limited.
- ↑ Dutton, M. (2008). Orthopaedic: Examination, evaluation, and intervention (2nd ed.). New York: The McGraw-Hill Companies, Inc.
- ↑ Flynn, T.W., Cleland, J.A., Whitman, J.M. (2008). User's guide to the musculoskeletal examination: Fundamentals for the evidence-based clinician. Buckner, Kentucky: Evidence in Motion
- ↑ Dutton, M. (2008). Orthopaedic: Examination, evaluation, and intervention (2nd ed.). New York: The McGraw-Hill Companies, Inc.
- ↑ Jaeschke, R., Guyatt, J.R., Sackett, D.L. (1994). Users guide to the medical literature. III. How to use an article about a diagnostic test. B. What are the results and will they help me in caring for my patients? JAMA, 27: 703-707.
- ↑ Cleland, J. (2005). Introduction, orthopedic clinical examination: An evidence-based approach for physical therapists. Carlstadt, NJ: Icon Learning Systems, LLC.
- ↑ Jaeschke, R., Guyatt, J.R., Sackett, D.L. (1994). Users guide to the medical literature. III. How to use an article about a diagnostic test. B. What are the results and will they help me in caring for my patients? JAMA, 27: 703-707.
