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    The limping child: an algorithm to outrule musculoskeletal sepsis.

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    Authors
    Delaney, R A
    Lenehan, B
    O'sullivan, L
    McGuinness, A J
    Street, J T
    Affiliation
    Department of Trauma and Orthopaedics, Cork University Hospital, Cork, Ireland., Delaney.ruth@gmail.com
    Issue Date
    2012-02-03T15:16:51Z
    MeSH
    Algorithms
    Arthritis, Infectious/diagnosis
    Bone Diseases, Infectious/*diagnosis
    C-Reactive Protein/analysis
    Child
    Child, Preschool
    Female
    *Gait
    Humans
    Infant
    Male
    Multivariate Analysis
    Muscular Diseases/*diagnosis
    Osteomyelitis/diagnosis
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    Citation
    Ir J Med Sci. 2007 Sep;176(3):181-7. Epub 2007 Jul 12.
    Journal
    Irish journal of medical science
    URI
    http://hdl.handle.net/10147/209273
    DOI
    10.1007/s11845-007-0061-7
    PubMed ID
    17624502
    Abstract
    BACKGROUND: The acutely limping child presents a significant diagnostic challenge. AIM: The purpose of this study was to create a clinically useful algorithm to allow exclusion of 'musculoskeletal sepsis' as a differential diagnosis in the child presenting with limp. METHODS: Data were collected on all 286 limping children admitted to our centre over a 3-year-period. Using logistic regression analysis, the predictive model was constructed, to exclude infection. RESULTS: Duration of symptoms, constitutional symptoms, temperature, white cell count and ESR were significantly different in children with musculoskeletal infection (P < 0.05). Multivariate analysis demonstrated that when all three variables of duration of symptoms >1, <5 days; temperature >37.0 degrees C; and ESR >35 mm/h were present, the predicted probability of infection was 0.66, falling to 0.01 when none were present. CONCLUSION: This multivariate model enables us to rule out musculoskeletal infection with 99% certainty in limping children with none of these three presenting variables.
    Language
    eng
    ISSN
    1863-4362 (Electronic)
    0021-1265 (Linking)
    ae974a485f413a2113503eed53cd6c53
    10.1007/s11845-007-0061-7
    Scopus Count
    Collections
    Cork University Hospital

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