A Predictive Model for Delirium in Hospitalized Elderly Medical Patients Based on Admission Characteristics

doi:10.1059/0003-4819-119-6-199309150-00005

A Predictive Model for Delirium in Hospitalized Elderly Medical Patients Based on Admission Characteristics

From Yale University School of Medicine, New Haven Connecticut. Requests for Reprints: Sharon K. Inouye, MD, MPH, Yale-New Haven Hospital, 20 York Street, Tompkins 15, New Haven, CT 06504. Acknowledgments: The authors thank the patients, families, and physicians from Yale-New Haven Hospital who participated in their study; the nursing staffs and head nurses Cynthia Johnson, Coy Smith, Marg Meglin, Gail Wojtyna, Noreen Fitzmartin, and Dorothy Moniz-Narracci on the medical floors, who participated in daily interviews despite a critical nursing shortage; Mary Lockett and the Yale Emergency Room staff for assistance in screening our patients; Dr. Lisa Berkman for advice on methods; Sandra Ginter, Anne Fasanella, and Mr. William Sharpe for research assistance; Denise Acampora for research and data coordination; Christine Brady for data management and analysis; Wanda Carr for data entry; Geraldine Hawthorne for clerical assistance; and Drs. Leo Cooney and Alvan Feinstein for helpful review of the manuscript. Grant Support: In part by grant 90-44, 91-66 from the Retirement Research Foundation, grant 11 from the Sandoz Foundation for Gerontological Research, a grant from the American Federation for Aging Research, and grant RR05443 from the Biomedical Research Support Grant Program, Division of Research Resources, National Institutes of Health. Dr. Inouye is a Dana Foundation Faculty Scholar and recipient of Academic Award 1K08AG00524-01 from the National Institute on Aging.

Abstract

Objective: To prospectively develop and validate a predictive model for the occurrence of new delirium in hospitalized elderly medical patients based on characteristics present at admission.

Design: Two prospective cohort studies done in tandem.

Setting: University teaching hospital.

Patients: The development cohort included 107 hospitalized general medical patients 70 years or older who did not have dementia or delirium at admission. The validation cohort included 174 comparable patients.

Measurements: Patients were assessed daily for delirium using a standardized, validated instrument. The predictive model developed in the initial cohort was then validated in a separate cohort of patients.

Results: Delirium developed in 27 of 107 patients (25%) in the development cohort. Four independent baseline risk factors for delirium were identified using proportional hazards analysis: These included vision impairment (adjusted relative risk, 3.5; 95% CI, 1.2 to 10.7); severe illness (relative risk, 3.5; CI, 1.5 to 8.2); cognitive impairment (relative risk, 2.8; CI, 1.2 to 6.7); and a high blood urea nitrogen/creatinine ratio (relative risk, 2.0; CI, 0.9 to 4.6). A risk stratification system was developed by assigning 1 point for each risk factor present. Rates of delirium for low- (0 points), intermediate- (1 to 2 points), and high-risk (3 to 4 points) groups were 9%, 23%, and 83% (P < 0.0001), respectively. The corresponding rates in the validation cohort, in which 29 of 174 patients (17%) developed delirium, were 3%, 16%, and 32% (P < 0.002). The rates of death or nursing home placement, outcomes potentially related to delirium, were 9%, 16%, and 42% (P = 0.02) in the development cohort and 3%, 14%, and 26% (P = 0.007) in the validation cohort.

Conclusions: Delirium among elderly hospitalized patients is common, and a simple predictive model based on four risk factors can be used at admission to identify elderly persons at the greatest risk.