Development of a risk score to guide brain imaging in older patients admitted with falls and confusion

A. J. Brown, M. D. Witham, J. George

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    Abstract

    Objectives: CT scanning of the brain is commonly performed in older people admitted to hospital with a fall, but the yield of positive findings is low. We used audit data to develop a risk-stratification score to guide more efficient use of CT scanning.

    Methods: 12 potential predictors of positive CT findings were derived from a literature review. Case notes of consecutive patients presenting with falls and confusion who had undergone brain imaging were reviewed as part of an ongoing audit. Correlation of each factor with positive CT findings was undertaken and a final risk score was developed. Receiver-operating characteristic analysis was undertaken, an optimum cut-off identified, and positive and negative predictive values were calculated.

    Results: 66 patients with a mean age of 74.8 years were included. 13 of the 66 (20%) brain imaging studies revealed a new pathology. Previous history of falls, atrial fibrillation, head or face trauma, focal neurological signs, warfarin use and a Glasgow coma score of,14 were significant univariate positive predictors. Antecedent dementia was included as a negative predictor. The final weighted score (range -1 to 8 points) gave an area under the curve of 0.83 (95% confidence interval 0.70 to 0.96, p < 0.001). When using a cut-off of 3 points, sensitivity for significant new pathology on brain imaging was 83%, specificity was 89%, positive predictive value was 63% and negative predictive value was 96%.

    Conclusion: A simple weighted risk score may be able to guide the need for brain imaging in older people presenting to hospital with falls. The score requires validation in a larger, prospectively collected cohort.

    Original languageEnglish
    Pages (from-to)756-757
    Number of pages2
    JournalBritish Journal of Radiology
    Volume84
    Issue number1004
    DOIs
    Publication statusPublished - Aug 2011

    Keywords

    • COMMUNITY
    • INJURY
    • MODEL

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