Brachial plexus compression test

Purpose: To determine if applying direct compression to brachial plexus causes radiating symptoms, suggesting mechanically elicitable cervical spine lesions. Patient position: Sitting upright or lying supine. Examiner position: Standing behind while the patient is sitting; Standing on the head side while the patient is lying supine. Procedure: Apply compression directly on the brachial plexus using the fingers or thumb. Outcome: The test is positive if pain or other neural symptoms … Continue reading Brachial plexus compression test

Cervical distraction test

Purpose: To determine if radicular symptoms alleviate on applying traction to the cervical spine. To identify the presence of cervical radiculopathy among patients with upper quadrant pain. Patient Position: Sitting upright, Supine. Examiner Position: Beside the patient, Standing at the patient’s head side. Procedure: Place one hand on the chin and another hand on the occiput. Carefully apply distraction force cephalad. Ask if the radicular symptoms are relieved. … Continue reading Cervical distraction test

Jackson’s compression test

Purpose: To identify the presence of cervical radiculopathy among patients with upper quadrant pain. Patient Position: Sitting upright. Examiner Position: Beside or behind the patient. Procedure: Ask the patient to turn/rotate the head to the unaffected side. Carefully apply axial compression vertically downwards through the head. Repeat the same on the affected side. Outcome: The test is positive if the patient has radiating pain down the arm on the corresponding dermatome ipsilaterally. … Continue reading Jackson’s compression test

Spurling’s test

Purpose: To identify the presence of cervical radiculopathy among patients with upper quadrant pain. Patient Position: Sitting upright. Examiner Position: Standing beside or behind the patient. Procedure: Move the patient’s head into lateral flexion/rotation to the unaffected side. Carefully apply axial compression vertically downwards through the head. Repeat the same on the affected side. Bradley et al. suggestions: Stage 1: Compress the head in neutral position. Stage 2: Compress the head in extension. … Continue reading Spurling’s test

Probability Tree

Clinicians often face complex diagnostic challenges. Such diagnostic dilemmas are typically complicated by the lack of clarity/focus during clinical investigation. The application of the strategy called ‘Decision Analysis’, described by Pauker and Kassirer (1) will help estimate the probability of all possible outcomes in a diagnostic challenge and select an optimal course of action. Let us consider data from the study by Capra et al (2) that … Continue reading Probability Tree

Diagnostic Efficiency

The receiver operating characteristic (ROC) curve is a measure of diagnostic efficiency, which is obtained by graphically plotting a series of true positive rates (sensitivity) against false positive rates (1 – specificity) for a binary outcome system. The ROC curve is a method to visualise the performance of a test with binary outcomes (+ / -) graphically. The area under the ROC (AUROC) curve is equal to the probability … Continue reading Diagnostic Efficiency

Post-test Probability

Post-test probability: is the probability of the presence of a disease after a confirmatory diagnostic test. Method I:  Let us estimate post-test probability by hand calculation using the data from the study by Capra et al (1). To do this, we need to know the pre-test probability and the positive likelihood ratio values. For this purpose, let us assume the pre-test probability as 0.55. And, we will … Continue reading Post-test Probability

Likelihood Ratios

Let us continue using the data from the study by Capra et al (1). The likelihood ratio is the percentage of diseased individuals with a given test result divided by the percentage of healthy individuals with the same test result (2). The likelihood ratios (positive and negative) can be calculated by using the following formulae (2): + LR = sensitivity / (1- specificity) = True positive rate / … Continue reading Likelihood Ratios

Predictive Values

Let us continue our analysis using data from Capra et al (1). After a confirmed MRI diagnosis, we may have the following questions: What is the probability that the patient with a positive MRI result has the disease? or What is the proportion of patients with positive MRI results have the disease? Calculating the post-test probabilities (in other terms, post-test likelihood values or positive/negative predictive values) will help answer these … Continue reading Predictive Values