Acute and chronic whiplash disorders--a review.

OBJECTIVE: This review examines acute and chronic whiplash-associated disorders to facilitate assessment, treatment and rehabilitation for further research and evidence-based practices. DESIGN: A review of the literature. RESULTS AND CONCLUSION: Whiplash-associated disorders account for a large proportion of the overall impairment and disability caused by traffic injuries. Rarely can a definite injury be determined in the acute (or chronic) phase. Crash-related factors have been identified, and several trauma mechanisms possibly causing different injuries have been described. Most whiplash trauma will not cause injury, and the majority of patients (92-95%) will return to work. Litigation is not a major factor. Cognitive impairments are not the same as brain injury. Variables such as pain intensity, restricted motion, neurological symptoms and signs, together with central nervous system symptoms can be used to predict a situation with risk of remaining complaints. Influences of other factors--the same as for other chronic pain conditions--also exist. Persistent/chronic pain is not merely acute pain that persists over time; changes occur at different levels of the pain transmission system. Chronic whiplash-associated disorders are associated with problems concerning social functioning, daily anxieties and satisfaction with different aspects of life. Adequate information, advice and pain medication together with active interventions might be more effective in the acute stage. Early multidisciplinary rehabilitation focusing on cognitive-behavioural changes might be of value. To develop specific treatment and rehabilitation, it is important to identify homogenous subgroups.

The incidence of whiplash trauma and the effects of different factors on recovery.

We performed a prospective study of patients with a whiplash trauma to the cervical spine to describe the incidence of these injuries and to evaluate prognostic factors for disability and recovery. A total of 356 patients were enrolled in the study. All the patients received a comprehensive questionnaire after the injury, and 296 cases responded to the follow-up protocol more than 1 year after the accident. Disability related to the whiplash trauma was used as the outcome variable for the assessment of prognostic factors. The annual incidence of acute whiplash trauma in the catchment area was 4.2 per 1,000 inhabitants and 3.2 per 1,000 for whiplash-associated disorder grades 1-3. Thirty-two percent reported persisting disability at follow-up. The following factors were significantly associated with a poor prognosis: pretraumatic neck pain, low educational level, female gender, and whiplash-associated disorder grades 2-3.

Chronic whiplash associated disorders and neck movement measurements: an instantaneous helical axis approach.

This paper presents an assessment tool for objective neck movement analysis of subjects suffering from chronic whiplash-associated disorders (WAD). Three-dimensional (3-D) motion data is collected by a commercially available motion analysis system. Head rotation, defined in this paper as the rotation angle around the instantaneous helical axis (IHA), is used for extracting a number of variables (e.g., angular velocity and range, symmetry of motion). Statistically significant differences were found between controls and subjects with chronic WAD in a number of variables.

Classification of neck movement patterns related to whiplash-associated disorders using neural networks.

This paper presents a new method for classification of neck movement patterns related to Whiplash-associated disorders (WAD) using a resilient backpropagation neural network (BPNN). WAD are a common diagnosis after neck trauma, typically caused by rear-end car accidents. Since physical injuries seldom are found with present imaging techniques, the diagnosis can be difficult to make. The active range of the neck is often visually inspected in patients with neck pain, but this is a subjective measure, and a more objective decision support system, that gives a reliable and more detailed analysis of neck movement pattern, is needed. The objective of this study was to evaluate the predictive ability of a BPNN, using neck movement variables as input. Three-dimensional (3-D) neck movement data from 59 subjects with WAD and 56 control subjects were collected with a ProReflex system. Rotation angle and angle velocity were calculated using the instantaneous helical axis method and motion variables were extracted. A principal component analysis was performed in order to reduce data and improve the BPNN performance. BPNNs with six hidden nodes had a predictivity of 0.89, a sensitivity of 0.90 and a specificity of 0.88, which are very promising results. This shows that neck movement analysis combined with a neural network could build the basis of a decision support system for classifying suspected WAD, even though further evaluation of the method is needed.