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      Delirium in Hospitalized Older Adults

      research-article
      , M.D.
      The New England journal of medicine

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          Abstract

          A 75-year-old man is admitted for scheduled major abdominal surgery. He is functionally independent, with mild forgetfulness. His intraoperative course is uneventful, but on postoperative day 2, severe confusion and agitation develop. What is going on? How would you manage this patient’s care? Could his condition have been prevented?

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          Most cited references27

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          Delirium in older persons.

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            Precipitating factors for delirium in hospitalized elderly persons. Predictive model and interrelationship with baseline vulnerability.

            To prospectively develop and validate a predictive model for delirium based on precipitating factors during hospitalization, and to examine the interrelationship of precipitating factors and baseline vulnerability. Two prospective cohort studies, in tandem. General medical wards, university teaching hospital. For the development cohort, 196 patients aged 70 years and older with no delirium at baseline, and for the validation cohort, 312 comparable patients. New-onset delirium by hospital day 9, defined by the Confusion Assessment Method diagnostic criteria. Delirium developed in 35 patients (18%) in the development cohort. Five independent precipitating factors for delirium were identified; use of physical restraints (adjusted relative risk [RR], 4.4; 95% confidence interval [CI], 2.5 to 7.9), malnutrition (RR, 4.0; 95% CI, 2.2 to 7.4), more than three medications added (RR, 2.9; 95% CI, 1.6 to 5.4), use of bladder catheter (RR, 2.4; 95% CI, 1.2 to 4.7), and any iatrogenic event (RR, 1.9; 95% CI, 1.1 to 3.2). Each precipitating factor preceded the onset of delirium by more than 24 hours. A risk stratification system was developed by adding 1 point for each factor present. Rates of delirium for low-risk (0 points), intermediate-risk (1 to 2 points), and high-risk groups (> or equal to 3 points) were 3%, 20%, and 59%, respectively (P < .001). The corresponding rates in the validation cohort, in which 47 patients (15%) developed delirium, were 4%, 20%, and 35%, respectively (P < .001). When precipitating and baseline factors were analyzed in cross-stratified format, delirium rates increased progressively from low-risk to high-risk groups in all directions (double-gradient phenomenon). The contributions of baseline and precipitating factors were documented to be independent and statistically significant. A simple predictive model based on the presence of five precipitating factors can be used to identify elderly medical patients at high risk for delirium. Precipitating and baseline vulnerability factors are highly interrelated and contribute to delirium in independent substantive, and cumulative ways.
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              3D-CAM: derivation and validation of a 3-minute diagnostic interview for CAM-defined delirium: a cross-sectional diagnostic test study.

              Delirium is common, leads to other adverse outcomes, and is costly. However, it often remains unrecognized in most clinical settings. The Confusion Assessment Method (CAM) is the most widely used diagnostic algorithm, and operationalizing its features would be a substantial advance for clinical care.
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                Author and article information

                Contributors
                Journal
                0255562
                5985
                N Engl J Med
                N. Engl. J. Med.
                The New England journal of medicine
                0028-4793
                1533-4406
                24 November 2017
                12 October 2017
                12 October 2018
                : 377
                : 15
                : 1456-1466
                Affiliations
                Division of General Medicine and Primary Care, Department of Medicine, Beth Israel Deaconess Medical Center, and Harvard Medical School — both in Boston
                Author notes
                Address reprint requests to Dr. Marcantonio at Beth Israel Deaconess Medical Center, 330 Brookline Ave., CO-216, Boston, MA 02215, or at emarcant@ 123456bidmcf.harvard.edu
                Article
                PMC5706782 PMC5706782 5706782 nihpa922097
                10.1056/NEJMcp1605501
                5706782
                29020579
                04a82778-5fe7-4f4a-8723-d8b8980f47d5
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