Please use this identifier to cite or link to this item: http://dl.yums.ac.ir/handle/Hannan/15297
Title: A Research Algorithm to Improve Detection of Delirium in the Intensive Care Unit
Authors: Pisani, Margaret A;Araujo, Katy LB;Van Ness, Peter H;Ely, E Wesley;Zhang, Ying;Inouye, Sharon
Issue Date: 2006
Publisher: BioMed Central
Description: Introduction: Delirium is a serious and prevalent problem in intensive care units (ICUs). The purpose of this study was to develop a research algorithm to enhance detection of delirium in critically ill ICU patients using chart review to complement a validated clinical delirium instrument. Methods: A prospective cohort study was conducted in 178 patients aged 60 years and older who were admitted to the medical ICU. The Confusion Assessment Method for the ICU (CAM-ICU) and a validated chart review method for detecting delirium were performed daily. We assessed the diagnostic accuracy of the chart-based delirium method using the CAM-ICU as the 'gold standard'. We then used an algorithm to detect delirium first using the CAM-ICU ratings and then chart review when the CAM-ICU was unavailable. Results: When using both the CAM-ICU and the chart-based review, the prevalence of delirium was found to be 80% of patients (143 out of 178) or 64% of patient-days (929 out of 1,457). Of these patient-days, 292 were classified as delirium by the CAM-ICU. The remainder (637 patient-days) were classified as delirium by the validated chart review method when CAM-ICU was missing because the assessment was conducted for weekends or holidays (404 patient-days), when CAM-ICU was not performed because of stupor or coma (205 patient-days), and when the CAM-ICU was negative (28 patient-days). Sensitivity of the chart-based method was 64% and specificity was 85%. Overall agreement between chart and the CAM-ICU was 72%. Conclusion: Eight out of 10 patients in this cohort study developed delirium in the ICU. Although use of a validated delirium instrument with frequent direct observations is recommended for clinical care, this approach may not always be feasible, especially in a research setting. The algorithm proposed here comprises a more comprehensive method for detecting delirium in a research setting, taking into account the fluctuation that occurs with delirium, which is a key component of accurate determination of delirium status. Improving detection of delirium is of paramount importance both to advance delirium research and to enhance clinical care and patient safety.
URI: http://nrs.harvard.edu/urn-3:HUL.InstRepos:dash.current.terms-of-use#LAA
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC1750978/pdf/
http://nrs.harvard.edu/urn-3:HUL.InstRepos:4878058
Other Identifiers: Pisani, Margaret A., Katy L. B. Araujo, Peter H. Van Ness, Ying Zhang, E. Wesley Ely, and Sharon K. Inouye. 2006. A research algorithm to improve detection of delirium in the intensive care unit. Critical Care 10(4): R121.
1364-8535
Appears in Collections:HMS Scholarly Articles

Files in This Item:
Click on the URI links for accessing contents.


Items in HannanDL are protected by copyright, with all rights reserved, unless otherwise indicated.