Changes in nutritional status during the hospital stay: a predictor of long-term survival

The objectives of this prospective observational study were to assess whether: 1) midarm circumference (MAC), previously shown to predict in-hospital mortality, maintains its prognostic implication after discharge; 2) in-hospital changes in aspecific indicators of the health status are predictors of long-term survival. The study population consisted of 249 patients from the general community [mean age 80 +/- 7 (70-99) years], consecutively discharged from geriatric and medical wards of an acute care hospital. Changes in health status during hospitalization were recorded (dynamic or delta variables) and health-related variables were collected at discharge (discharge variables). The relationship of both sets of variables to survival over a 3-year period was assessed by Cox's proportional hazards regression analysis. The discriminatory efficacy of predictive models was estimated by the Hanley and McNeil method. Survival curves were drawn with the patients alternatively grouped according to the presence or absence of each of the predictive variables. Serum albumin < 3.5 g/dL (hazard rate = 0.57, 95% confidence limits = 0.33-0.96) and dependency in at least one ADL (h.r. = 0.87, c.l. = 0.79-0.98) were found to be associated with increased mortality, and delta MAC (h.r. = 1.03, c.l. = 1.01-1.05), i.e., there was a positive change or no change in MAC from admission to discharge, with increased survival. A slightly weaker predictive model was obtained using only discharge variables. However, Hanley and McNeil's analysis showed that both models were far from achieving the optimal discrimination of high from low risk subjects. Effects on survival of individual variables varied in magnitude and dependency on time. We concluded that measuring in-hospital changes in nutritional status might improve prediction of long-term survival. Attempts should be made to identify variables having the strongest prognostic implications, and to tailor dynamic assessment to the needs of selected categories of patients.