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Predicting Mortality in Nursing Home Residents With Lower Respiratory Tract Infection
The Missouri LRI Study
David R. Mehr, MD, MS;
Ellen F. Binder, MD;
Robin L. Kruse, PhD;
Steven C. Zweig, MD, MSPH;
Richard Madsen, PhD;
Lori Popejoy, MSN, RN;
Ralph B. D'Agostino, PhD
JAMA. 2001;286:2427-2436.
Context Lower respiratory tract infection (LRI) is a leading cause of mortality and hospitalization in nursing home residents. Treatment decisions may be aided by a clinical prediction rule that identifies residents at low and high risk of mortality.
Objective To identify patient characteristics predictive of 30-day mortality in nursing home residents with an LRI.
Design, Setting, and Patients Prospective cohort study of 1406 episodes of LRI in 1044 residents of 36 nursing homes in central Missouri and the St Louis, Mo, area between August 15, 1995, and September 30, 1998.
Main Outcome Measure Thirty-day all-cause mortality.
Results Thirty-day mortality was 14.7% (n = 207). In a logistic analysis, using generalized estimating equations to adjust for clustering, we developed an 8-variable model to predict 30-day mortality, including serum urea nitrogen, white blood cell count, body mass index, pulse rate, activities of daily living status, absolute lymphocyte count of less than 800/µL (0.8 x 109/L), male sex, and deterioration in mood over 90 days. In validation testing, the model exhibited reasonable discrimination (c = .76) and calibration (nonsignificant Hosmer-Lemeshow goodness-of-fit statistic, P = .54). A point score based on this model's variables fit to the entire data set closely matched observed mortality. Fifty-two percent of residents had low (score of 0-4) or relatively low (score of 5-6) predicted 30-day mortality, with 2.2% and 6.2% actual mortality, respectively.
Conclusions Our model distinguishes nursing home residents at relatively low risk for mortality due to LRI. If independently validated, our findings could help physicians identify nursing home residents in need of different therapeutic approaches for LRI.
Author Affiliations: Center for Family Medicine Science, Department of Family and Community Medicine, School of Medicine (Drs Mehr, Kruse, and Zweig), Department of Statistics (Dr Madsen), and Sinclair School of Nursing (Ms Popejoy), University of Missouri, Columbia; Department of Internal Medicine, Division of Geriatrics and Gerontology, Washington University School of Medicine, St Louis, Mo (Dr Binder); and Department of Mathematics and Statistics, Boston University, Boston, Mass (Dr D'Agostino).
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