BackgroundInfectious diseases are a common cause of increased morbidity and mortality in elderly patients. Bacteraemia in the elderly is a difficult diagnosis and a therapeutic challenge due to age-related vicissitudes and to their comorbidities. The main purpose of the study was to assess independent risk factors for in-hospital mortality among the elderly with bacteraemia admitted to an Internal Medicine Ward.MethodsOverall, a cohort of 135 patients, 65 years of age and older, with bacteraemia were retrospectively studied. Data related to demographic information, comorbidities, clinical parameters on admission, source and type of infection, microorganism isolated in the blood culture, laboratory data and empirical antibiotic treatment was recorded from each patient. Multivariate logistic regression was performed to identify independent predictors of all-cause in-hospital mortality.ResultsOf these 135 patients, 45.9% were women. The most common infections in this group of patients were urinary tract infections (46.7%). The main microorganisms isolated in the blood cultures were Escherichia coli (14.9%), Methicillin-resistant Staphylococcus aureus (MRSA) (12.0%), non-MRSA (11.4%), Klebsiella pneumoniae (9.1%) and Enterococcus faecalis (8.0%). The in-hospital mortality was 22.2%. Independent prognostic factors associated with in-hospital mortality were age ≥ 85 years, chronic renal disease, bacteraemia of unknown focus and cognitive impairment at admission (OR, 2.812 [95% CI, 1.039-7.611; p = 0.042]; OR, 6.179 [95% CI, 1.840-20.748; p = 0.003]; OR, 8.673 [95% CI, 1.557-48.311; p = 0.014] and OR, 3.621 [95% CI, 1.226-10.695; p = 0.020], respectively). By multivariate analysis appropriate antibiotic therapy was not associated with lower odds of mortality.ConclusionBacteraemia in the elderly has a high mortality rate. There are no set of signs or clinical features that can predict bacteraemia in the elderly. However, older age (≥ 85 years), chronic renal disease, bacteraemia of unknown focus and severe cognitive impairment adversely affects the outcome of elderly patients with bacteraemia admitted to an Internal Medicine ward.

BackgroundThe risk of coronary heart disease (CHD) is related to environmental factors and genetic variants. Apolipoprotein E (apoE) polymorphisms are heritable determinants of total and low-density lipoprotein cholesterol, with some authors suggesting an association between the ε4 allele and CHD. We investigated the relationship between apoE genotype and age at referral to a specialized lipid clinic by the primary care physician and whether the benefits of treatment with statin differed between genotypes.MethodsWe assessed individual apoE genotypes and lipid blood profile in a total of 463 patients followed at a specialized lipid clinic due to dyslipidemia, with a 3-year median follow-up time. The primary care physician at the time of the referral had no access to the apoE genotyping results. Carriers of apoE ε4/ε2 genotype were excluded.ResultsThe frequencies of ε2, ε3 and ε4 alleles were 7.8, 78.9 and 13.3%, respectively. There were no significant differences between genders. Although with similar lipid profiles and antidyslipidemic drug usage at baseline, ε4-carriers were referred to the clinic at a younger age (44.2 ± 14.7 years) compared with non-ε4 carriers (50.6 ± 13.8 years) (p < 0.001), with a substantially younger age of referral for homozygous E4/4 and for all genotypes with at least one copy of the ε4 allele (p < 0.001 for trend). Although both ε4 and non-ε4 carriers achieved significant reductions in total cholesterol during follow-up (p < 0.001 vs. baseline), the mean relative decrease in total cholesterol levels was higher in non-ε4 carriers (-19.9 ± 2.3%) compared with ε4 carriers (-11.8 ± 2.3%), p = 0.003.ConclusionOur findings support the concept that there is a reduced response to anti-dyslipidemic treatment in ε4 carriers; this can be a contributing factor for the earlier referral of these patients to our specialized lipid clinic and reinforces the usefulness of apoE genotyping in predicting patients response to lipid lowering therapies.