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  1. Acute confusion indicators : Risk factors and prevalence using MDS data.

    Article - En anglais

    Long-term care (LTC) Minimum Data Set (MDS) data from a Midwestern state were analyzed to validate whether components of a conceptual model developed from findings in acute care identified acute confusion risk variables in LTC.

    The prevalence of probable acute confusion in this sample was 13.98% (n=324).

    Using a cross-sectional design, both univariate and unconditional stepwise logistic regression analyses were accomplished with presence or absence of probable acute confusion as the outcome variable (N=2,318).

    Variables significantly related to acute confusion by univariate analysis were included in the logistic regression analysis.

    Inadequate fluid intake was the first variable to enter the stepwise equation and was highly significant (OR 3.40,95% CI 2.99-3.81, p<. 0001).

    Other significant variables included a diagnosis of dementia or a fall in the last 30 days.

    Implications for nursing practice, education and research are discussed.

    Mots-clés Pascal : Confusion mentale, Aigu, Indicateur, Prévalence, Facteur risque, Méthodologie, Evaluation, Homme, Epidémiologie, Etats Unis, Amérique du Nord, Amérique

    Mots-clés Pascal anglais : Mental confusion, Acute, Indicator, Prevalence, Risk factor, Methodology, Evaluation, Human, Epidemiology, United States, North America, America

    Logo du centre Notice produite par :
    Inist-CNRS - Institut de l'Information Scientifique et Technique

    Cote : 99-0191059

    Code Inist : 002B30A01A1. Création : 16/11/1999.