The body mass index is related to the functional capabilities of community-dwelling elderly. The inclusion of this simple measurement in the comprehensive assessment of community-dwelling elderly is supported.

OBJECTIVE: To develop a model estimating the probability of a patient aged 80 years or older having functional limitations 2 months and 12 months after being hospitalized. DESIGN: A prospective cohort study. SETTING: Four teaching hospitals in the US. PARTICIPANTS: Enrolled patients were nonelective hospital admissions aged 80 years or older who stayed in hospital at least 48 hours. The 804 patients who survived and completed an interview at 2 months and the 450 who completed an interview at 12 months were from the 1266 patients in the Hospitalized Elderly Longitudinal Project (HELP) (76% and 47% of survivors, respectively). Median age of the 2-month survivors was 84.7 years. MEASUREMENTS AND MAIN OUTCOMES: Patient function 2 and 12 months after enrollment was defined by the number of dependencies in Activities of Daily Living (ADLs). Ordinal logistic regression models were constructed to predict functional status. Predictors included demographic characteristics, disease category, geriatric conditions, severity of physiologic imbalance, current quality of life, and exercise capacity and ADLs 2 weeks before study admission. RESULTS: Before admission, 39% of patients were functionally independent in ADLs. Of patients who survived and were interviewed at 2 months, 32% were functionally independent, and at 12 months, 36% were independent. Among patients with no baseline dependencies, 42 % had developed one or more limitations 2 months later, and 41 % had limitations 12 months later. The patient's ability to perform activities of daily living at baseline was the most important predictor of functional status at both 2 and 12 months. In a multivariable predictive model, independent predictors of poorer functional status at 2 months included: worse baseline ~~

in the Hospitalized Elderly Longitudinal Project (HELP). Patients were excluded if their length of hospital stay was 48 hours or less or if admitted electively for planned surgery. MEASUREMENTS: A log-normal model of survival time up to 711 days was developed with the following variables: patient demographics, disease category, nursing home residence, severity of physiologic imbalance, chart documentation of weight loss, current quality of life, exercise capacity, and functional status. We assessed whether model accuracy could be improved by including symptoms of depression or history of recent fall, serum albumin, physician's subjective estimate of prognosis, and physician and patient preferences for general approach to care. RESULTS: A total of 1266 patients were enrolled over a 10-month period, (median age 84.9,61% female, 68% with one or more dependency), and 505 (40%) died during an average follow-up of more than 2 years. Important prognostic factors included the Acute Physiology Score of APACHE I11 collected on the third hospital day, modified Glasgow coma score, major diagnosis (ICU categories together, congestive heart failure, cancer, orthopedic, and all other), age, activities of daily living, exercise capacity, chart documentation of weight loss, and global quality of life. The Somers' Dxy for a model including these factors was 0.48 (equivalent Rm 222, Brown University, Providence, RI 02912.to a receiver-operator curve (ROC) area of 0.74, suggesting good discrimination). Bootstrap estimation indicated good model validation (corrected Dxy of 0.46, ROC of 0.73). A nomogram based on this log-normal model is presented to facilitate calculation of median survival time and 10th and 90th percentile of survival time. A count of geriatric syndromes or comorbidities did not add explanatory power to the model, nor did the hospital of patient recruitment, depression, or the patient preferences for general approach to care. The physician's perception of the patient's preferences and the physician's subjective estimate of the patient's prognosis improved the estimate of survival time significantly. CONCLUSIONS: Accurate estimation of length of life for older hospitalized persons may be calculated using a limited amount of clinical information available from the medical chart plus a brief interview with the patient or surrogate. The accuracy of this model can be improved by including measures of the physician's perception of the patient's preferences for care and the physician's subjective estimate of prognosis. J Am Geriatr SOC 48:S16-S24,2000. Key words: prognosis; severity of illness; survival analysis; statistical models; older people uring the past 3 decades, prognostic models have been