With the prospect of demographic changes in Germany?the number of people over the age of 64 is predicted to increase by about half by the end of 2030 (1)?the question of health care of the elderly is being increasingly highlighted. As people get...

Previous studies have shown that the presence of anemia is associated with increased short- and long-term outcomes in patients with acute myocardial infarction (AMI). This study aims at examining the impact of admission anemia on long-term, all-cause mortality following AMI in patients recruited from a population-based registry. Contrary to most prior studies, we distinguished between patients with mild and moderate to severe anemia. This prospective study was conducted in 2011 patients consecutively hospitalized for AMI that occurred between January 2005 and December 2008. Patients who survived more than 28 days after AMI were followed up until December 2011. Hemoglobin (Hb) concentration was measured at hospital admission and classified according to the World Health Organization (WHO). Mild anemia was defined as Hb concentration of 11 to < 12 g/dL in women and 11 to < 13 g/dL in men; moderate to severe anemia as Hb concentration of < 11 g/dL. Adjusted Cox regression models were calculated to compare survival in patients with and without anemia. Mild anemia and moderate to severe anemia was found in 183 (9.1%) and 100 (5%) patients, respectively. All-cause mortality after a median follow-up time of 4.2 years was 11.9%. The Cox regression analysis showed significantly increased mortality risks in both patients with mild (HR 1.74, 95% CI 1.23–2.45) and moderate to severe anemia (HR 2.05, 95% CI 1.37–3.05) compared to patients without anemia. This study shows that anemia adversely affects long-term survival following AMI. However, further studies are needed to confirm that anemia can solely explain worse long-term outcomes after AMI.

Paradoxically, beneficial effects of overweight and obesity on survival have been found in patients after cardiovascular events such as acute myocardial infarction (AMI). This obesity paradox has not been analyzed in AMI patients with diabetes even though their cardiovascular morbidity and mortality is increased compared to their counterparts without diabetes. Therefore, the objective of this long-term study was to analyze the association between body mass index (BMI) and all-cause mortality in AMI patients with and without diabetes mellitus. Included in the study were 1190 patients with and 2864 patients without diabetes, aged 28-74 years, recruited from a German population-based AMI registry. Patients were consecutively hospitalized between 1 January 2000 and 31 December 2008 with a first ever AMI and followed up until December 2011. Data collection comprised standardized interviews and chart reviews. To assess the association between BMI and long-term mortality from all causes, Cox proportional hazards models were calculated adjusted for risk factors, co-morbidities, clinical characteristics, in-hospital complications as well as medical and drug treatment. AMI patients of normal weight (BMI 18.5-24.9 kg/m2) had the highest long-term mortality rate both in patients with and without diabetes with 50 deaths per 1000 person years and 26 deaths per 1000 person years, respectively. After adjusting for a selection of covariates, a significant, protective effect of overweight and obesity on all-cause mortality was found in AMI patients without diabetes (overweight: hazard ratio (HR) 0.73, 95% confidence interval (CI) 0.58-0.93; p=0.009; obesity: HR 0.64, 95% CI 0.47-0.87; p=0.004). In contrast, an obesity paradox was not found in AMI patients with diabetes. However, stratified analyses showed survival benefits in overweight AMI patients with diabetes who had been prescribed statins prior to AMI (HR 0.51, 95% CI 0.29-0.89, p=0.018) or four evidence-based medications at hospital-discharge (HR 0.52, 95% CI 0.34-0.80, p=0.003). In contrast to AMI patients without diabetes, AMI patients with diabetes do not experience a survival benefit from an elevated BMI. To investigate the underlying reasons for these findings, further studies stratifying their samples by diabetes status are needed.