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Special tests in injury examination

This is an excerpt from Examination of Musculoskeletal Injuries 5th Edition With HKPropel Access by Sandra J. Shultz & Tamara C. Valovich McLeod.

Special Tests
Special tests are unique to specific joints, body segments, or structures and are intended to reproduce the patient’s symptoms or create a comparable sign to help you accurately identify or rule out the presence of a particular injury. For example, special tests for the knee include tests for ligament integrity, the presence of a meniscal tear, or patellofemoral conditions, whereas tests for the shoulder examine glenohumeral instability, labral pathology, and rotator cuff pathology, among other things. Each body segment requires unique tests for examining the degree of injury to the soft tissue structures and bones of its area.

Because special tests are rarely 100% accurate, negative or positive results of a single special test do not necessarily indicate the absence or presence of a specific injury. All the factors of your examination are used in combination to provide a full and consistent injury profile. Sometimes a positive result may falsely occur and complicate your examination results, so that other tests are necessary for achieving accurate results. Your skills and ability to perform the tests can make a big difference in the test results; thus, experience plays an important role in the accuracy of findings from special tests. The condition severity can also affect the diagnostic value of the test.4 Finally, it is important to know the demonstrated accuracy of the special tests themselves, because some are better than others at isolating specific conditions.

As you will note in the region-specific chapters in part II, several special tests can be used for some conditions. Although it is usually not necessary to use all the available tests for a particular condition, you will often want to perform more than one to improve the accuracy of your findings. To aid in this selection, we report the sensitivity, specificity, and likelihood ratios of each special test for which data from well-designed studies are available. The test sensitivity refers to the percentage of time the test yields a positive result when the condition is truly present (true positive test); specificity refers to the percentage of time the test yields a negative result when the condition is truly absent (true negative test)5 (see the Calculation of Sensitivity, Specificity, and Likelihood Ratios sidebar). The sensitivity and specificity of a special test is based on the outcome of the test when compared to a diagnostic gold standard (e.g., confirmation of the condition via magnetic resonance imaging [MRI] or surgical findings). If a test has a high sensitivity score, you will be able to accurately identify all or most patients with a given condition (true positive), but the test could also be positive for those without the condition (false positive). Highly sensitive tests are generally good for ruling out a condition, because the test result is likely to show a negative finding when the injury for which you are testing is truly not present. Conversely, if the test has a high specificity rating, it is a good test for identifying patients who do not have the condition (true negative), but it may also identify negative findings for those who have the condition (false negative). Highly specific tests are good for ruling in a condition, because a positive result usually indicates that the disorder is present. When a test has high scores for both sensitivity and specificity, it is considered a highly accurate test and will require few confirmatory tests. If a test has high sensitivity and low specificity, it may result in a positive finding when the condition is not present. In this case, you should perform additional tests to confirm a positive finding. Conversely, a negative finding from a test with a low sensitivity score and a high specificity score does not mean that the patient does not have the injury. Additional tests should be performed to confirm the negative finding. Figure 2.1 provides exemplar data of what the accuracy of the Lachman’s test might look like in diagnosing an anterior cruciate ligament (ACL) tear (actual data are presented in chapter 17).

Likelihood ratios are more clinician friendly because they combine the sensitivity and specificity of a test to better summarize the diagnostic accuracy of a positive or negative test finding (see the Calculation of Sensitivity, Specificity, and Likelihood Ratios sidebar). The positive likelihood ratio (+LR) denotes the probability that the condition is present if the test is positive. The higher the +LR is, the higher is the probability that a patient has the condition if the test is positive. For the example in figure 2.1, the +LR is 5.5, indicating a positive test is 5.4 times more likely to be found in those who have the condition than in those who do not. Generally, a +LR of 2 or higher is desirable. The negative likelihood ratio (−LR) denotes the probability that the condition is present if the test is negative. The lower the −LR is, the lower the probability that the patient has the condition if the test is negative. For our example, the −LR is 0.21, indicating the examiner will find a positive test in those without the condition in 1 out of 5 times. Generally, a −LR less than 0.5 is desirable.



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