Predicting Prognosis in Internal Medicine: A Short and Long-Term Mortality Comparison Analysis

Introduction The marked increase in life expectancy seen in Portugal in the last five decades led to a change in the profile of patients being most commonly admitted in internal medicine wards. In deciding the best care for these patients, prognostication models are needed in order to reduce readmissions, mortality, and adequate care. We aimed to study short and long-term mortality and predictors of all-cause mortality, independently of cause admission, of patients admitted in an internal medicine ward. Methods This two-part, single-center study enrolled patients from October 2013 to October 2014 with a follow-up of 60 months. Results A total of 681 patients were included; the mean age was 75.86 years with 60.4% females. The most frequent comorbidities were anemia, hypertension, and renal impairment. More than half of the population died in the follow-up period (51.5%). Deaths were significantly higher in the first six months after discharge (53% of all deaths) and then decreased abruptly to 11.6% in the second half-year after discharge. Based on the multivariate logistic regression model, with age over 80 years, anemia and neoplasm were independent predictors of short-term (p<0.001, p=0.001, p<0.001, respectively) and long-term (p<0.001 for the three conditions) mortality. Heart failure (p=0.018) and diabetes (p=0.025) were also predictors of long-term mortality. Conclusion High mortality, mainly in the first six months after discharge, elicits strategies targeting transition of care and close follow-up in the first months, which can be the key to improving outcomes. Identification of patients at higher risk may help design realistic models aiming to improve care for this frail population and decrease morbimortality.