The AWOL tool: Derivation and validation of a delirium prediction rule

Authors

  • Vanja C. Douglas MD,

    Corresponding author
    1. Department of Neurology, University of California, San Francisco, San Francisco, California
    • Address for correspondence and reprint requests: Vanja Douglas, MD, UCSF Department of Neurology, Box, Parnassus Ave., M798, San Francisco, CA 94143-0114; Telephone: 415-514-1575; Fax: 415-476-3428; E-mail: Vanja.Douglas@ucsf.edu

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  • Christine S. Hessler MD,

    1. Department of Neurology, University of California, San Francisco, San Francisco, California
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  • Gurpreet Dhaliwal MD,

    1. Department of Medicine, University of California, San Francisco, San Francisco, California
    2. Medical Service, San Francisco Veterans Affairs Medical Center, San Francisco, California
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  • John P. Betjemann MD,

    1. Department of Neurology, University of California, San Francisco, San Francisco, California
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  • Keiko A. Fukuda BA,

    1. Department of Neurology, University of California, San Francisco, San Francisco, California
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  • Lama R. Alameddine MA,

    1. Department of Neurology, University of California, San Francisco, San Francisco, California
    2. Department of Psychology, San Francisco Veterans Affairs Medical Center, San Francisco, California
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  • Rachael Lucatorto MD,

    1. Department of Medicine, University of California, San Francisco, San Francisco, California
    2. Medical Service, San Francisco Veterans Affairs Medical Center, San Francisco, California
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  • S. Claiborne Johnston MD, PhD,

    1. Department of Neurology, University of California, San Francisco, San Francisco, California
    2. Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, California
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  • S. Andrew Josephson MD

    1. Department of Neurology, University of California, San Francisco, San Francisco, California
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Abstract

BACKGROUND

Risk factors for delirium are well-described, yet there is no widely used tool to predict the development of delirium upon admission in hospitalized medical patients.

OBJECTIVE

To develop and validate a tool to predict the likelihood of developing delirium during hospitalization.

DESIGN

Prospective cohort study with derivation (May 2010–November 2010) and validation (October 2011–March 2012) cohorts.

SETTING

Two academic medical centers and 1 Veterans Affairs medical center.

PATIENTS

Consecutive medical inpatients (209 in the derivation and 165 in the validation cohort) over age 50 years without delirium at the time of admission.

MEASUREMENTS

Delirium assessed daily for up to 6 days using the Confusion Assessment Method.

RESULTS

The AWOL prediction rule was derived by assigning 1 point to each of 4 items assessed upon enrollment that were independently associated with the development of delirium (Age ≥ 80 years, failure to spell “World” backward, disOrientation to place, and higher nurse-rated iLlness severity). Higher scores were associated with higher rates of delirium in the derivation and validation cohorts (P for trend < 0.001 and 0.025, respectively). Rates of delirium according to score in the combined population were: 0(1/50, 2%), 1(5/141, 4%), 2(15/107, 14%), 3(10/50, 20%), and 4(7/11, 64%) (P for trend < 0.001). Area under the receiver operating characteristic curve for the derivation and validation cohorts was 0.81 (0.73–0.90) and 0.69 (0.54–0.83) respectively.

CONCLUSIONS

The AWOL prediction rule characterizes medical patients' risk for delirium at the time of hospital admission and could be used for clinical stratification and in trials of delirium prevention. Journal of Hospital Medicine 2013;8:493–499. © 2013 Society of Hospital Medicine

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