• N S King.
• Rivermead Rehabilitation Centre, Oxford, UK.
• J. Neurol. Neurosurg. Psychiatr. 1996 Jul 1; 61 (1): 75-81.

BackgroundAfter mild and moderate head injuries a range of postconcussion symptoms (PCS) are often reported by patients. Both organic and psychogenic factors can contribute to these. Full recovery from PCS usually occurs within three months of the injury. A significant minority, however, continue to experience symptoms beyond this time. To date, no means of identifying these patients early after injury has been reported. This study investigates whether a combination of neuropsychological, emotional, and traditional measures of severity of head injury taken early after the injury can help predict severity of PCS three months after injury.Methods50 patients with mild or moderate head injury had a range of measures administered at 7-10 days after injury. These included three tests of divided attention, a PCS rating scale-the Rivermead postconcussion symptoms questionnaire (RPQ), the hospital anxiety and depression scale (HADS), the impact of event scale (IES), and post-traumatic amnesia. An RPQ was then completed by all patients three months after injury.ResultsStepwise multiple regression analysis was performed with the RPQ score at three months as the dependent measure. A combination of eight of the scores from the early measures gave a multiple correlation coefficient of R = 0.86 accounting for 74% of the variance in RPQ scores. The most predictive individual measures were the HADS and IES. Regression analysis with RPQ score at 7-10 days as dependent measure showed that 10 of the scores gave a coefficient of R = 0.84 accounting for 71% of the variance.ConclusionsA combination of measures may significantly aid the prediction of persistent PCS. Five measures: HADS, post-traumatic amnesia, SOMC, PASAT, and RPQ are recommended for their predictive value and clinical utility. Independent cross validation studies are required before these results can be generally applied. They do, however, provide valuable indications regarding those measures that are most likely to demonstrate utility.

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