Predicting dementia in primary care patients with a cardiovascular health metric: a prospective population-based study

Background: Improving cardiovascular health possibly decreases the risk of dementia. Primary care practices offer a suitable setting for monitoring and controlling cardiovascular risk factors in the older population. The purpose of the study is to examine the association of a cardiovascular health metric including six behaviors and blood parameters with the risk of dementia in primary care patients. Methods: Participants (N = 3547) were insurants aged >= 55 of the largest German statutory health insurance company, who were enrolled in a six-year prospective population-based study. Smoking, physical activity, body mass index, blood pressure, total cholesterol, and fasting glucose were assessed by general practitioners at routine examinations. Using recommended cut-offs for each factor, the patients' cardiovascular health was classified as ideal, moderate, or poor. Behaviors and blood parameters sub-scores, as well as a total score, were calculated. Dementia diagnoses were retrieved from health insurance claims data. Results are presented as hazard ratios (HRs) and 95 % confidence intervals (95 % CIs). Results: Over the course of the study 296 new cases of dementia occurred. Adjusted for age, sex, and education, current smoking (HR = 1.77, 95 % CI 1.09-2.85), moderate (1.38, 1.05-1.81) or poor (1.81, 1.32-2.47) levels of physical activity, and poor fasting glucose levels (1.43, 1.02-2.02) were associated with an increased risk of dementia. Body mass index, blood pressure, and cholesterol were not associated with dementia. Separate summary scores for behaviors and blood values, as well as a total score showed no association with dementia. Sensitivity analyses with differently defined endpoints led to similar results. Conclusions: Due to complex relationships of body-mass index and blood pressure with dementia individual components cancelled each other out and rendered the sum-scores meaningless for the prediction of dementia

Comparative and Joint Analysis of Two Metagenomic Datasets from a Biogas Fermenter Obtained by 454-Pyrosequencing

Biogas production from renewable resources is attracting increased attention as an alternative energy source due to the limited availability of traditional fossil fuels. Many countries are promoting the use of alternative energy sources for sustainable energy production. In this study, a metagenome from a production-scale biogas fermenter was analysed employing Roche's GS FLX Titanium technology and compared to a previous dataset obtained from the same community DNA sample that was sequenced on the GS FLX platform. Taxonomic profiling based on 16S rRNA-specific sequences and an Environmental Gene Tag (EGT) analysis employing CARMA demonstrated that both approaches benefit from the longer read lengths obtained on the Titanium platform. Results confirmed Clostridia as the most prevalent taxonomic class, whereas species of the order Methanomicrobiales are dominant among methanogenic Archaea. However, the analyses also identified additional taxa that were missed by the previous study, including members of the genera Streptococcus, Acetivibrio, Garciella, Tissierella, and Gelria, which might also play a role in the fermentation process leading to the formation of methane. Taking advantage of the CARMA feature to correlate taxonomic information of sequences with their assigned functions, it appeared that Firmicutes, followed by Bacteroidetes and Proteobacteria, dominate within the functional context of polysaccharide degradation whereas Methanomicrobiales represent the most abundant taxonomic group responsible for methane production. Clostridia is the most important class involved in the reductive CoA pathway (Wood-Ljungdahl pathway) that is characteristic for acetogenesis. Based on binning of 16S rRNA-specific sequences allocated to the dominant genus Methanoculleus, it could be shown that this genus is represented by several different species. Phylogenetic analysis of these sequences placed them in close proximity to the hydrogenotrophic methanogen Methanoculleus bourgensis. While rarefaction analyses still indicate incomplete coverage, examination of the GS FLX Titanium dataset resulted in the identification of additional genera and functional elements, providing a far more complete coverage of the community involved in anaerobic fermentative pathways leading to methane formation

Predicting dementia in primary care patients with a cardiovascular health metric: a prospective population-based study

Background: Improving cardiovascular health possibly decreases the risk of dementia. Primary care practices offer a suitable setting for monitoring and controlling cardiovascular risk factors in the older population. The purpose of the study is to examine the association of a cardiovascular health metric including six behaviors and blood parameters with the risk of dementia in primary care patients. Methods: Participants (N = 3547) were insurants aged >= 55 of the largest German statutory health insurance company, who were enrolled in a six-year prospective population-based study. Smoking, physical activity, body mass index, blood pressure, total cholesterol, and fasting glucose were assessed by general practitioners at routine examinations. Using recommended cut-offs for each factor, the patients' cardiovascular health was classified as ideal, moderate, or poor. Behaviors and blood parameters sub-scores, as well as a total score, were calculated. Dementia diagnoses were retrieved from health insurance claims data. Results are presented as hazard ratios (HRs) and 95 % confidence intervals (95 % CIs). Results: Over the course of the study 296 new cases of dementia occurred. Adjusted for age, sex, and education, current smoking (HR = 1.77, 95 % CI 1.09-2.85), moderate (1.38, 1.05-1.81) or poor (1.81, 1.32-2.47) levels of physical activity, and poor fasting glucose levels (1.43, 1.02-2.02) were associated with an increased risk of dementia. Body mass index, blood pressure, and cholesterol were not associated with dementia. Separate summary scores for behaviors and blood values, as well as a total score showed no association with dementia. Sensitivity analyses with differently defined endpoints led to similar results. Conclusions: Due to complex relationships of body-mass index and blood pressure with dementia individual components cancelled each other out and rendered the sum-scores meaningless for the prediction of dementia

Depressive Symptoms and the Risk of Ischemic Stroke in the Elderly—Influence of Age and Sex

<div><p>Although a relationship between depression and cardiovascular events has been suggested, past study results regarding the risk of stroke in relation to depression by subgroups are ambiguous. The aim of this study was to investigate the influence of depressive symptoms on risk of incident ischemic stroke in elderly according to age and sex. This prospective cohort study followed up 3852 subjects older than 55 years. Baseline depressive symptoms were defined by a score ≥5 on the Geriatric Depression Scale or antidepressant intake. The outcome measure was incident ischemic stroke within 6 years of follow-up. Multivariate Cox-proportional hazard models as well as cumulative survival analyses were computed. A total of 156 ischemic strokes occurred during the study period (24 strokes in the age-group<65 years and 132 strokes in the age-group≥65 years). The distribution of strokes in sex-subgroups was 4.5% in men and 3.7% in women. The multivariate analysis showed an elevated stroke risk (Hazard Ratio (HR): 2.84, 95% CI 1.11–7.29, p = 0.030) in subjects from 55 to 64 years with depressive symptoms at baseline but not in subjects older than 65 years. In the multivariate analysis according to sex the risk was increased in women (HR: 1.62, 95% CI 1.02–2.57, P = 0.043) but not in men. The Cox-regression model for interaction showed a significant interaction between age and sex (HR: 3.24, 95% CI 1.21–8.69, P = 0.020). This study corroborates that depressive symptoms pose an important risk for ischemic stroke, which is particularly remarkable in women and patients younger than 65 years.</p> </div

Kaplan–Meier survival plots for different age groups (<65, ≥65 years) and sex; timeframe between INVADE inclusion (day 0) and event free survival for ischemic stroke between the group taking antidepressants or GDS ≥5 and non-depressive group; for each plot the corresponding number of events and the size of the group is available at the end of the curve.

<p>Kaplan–Meier survival plots for different age groups (<65, ≥65 years) and sex; timeframe between INVADE inclusion (day 0) and event free survival for ischemic stroke between the group taking antidepressants or GDS ≥5 and non-depressive group; for each plot the corresponding number of events and the size of the group is available at the end of the curve.</p

Multivariate Cox-PH Model for the Risk of Stroke in Subjects With and Without Depression (GDS ≥5)/Antidepressant Medication, Adjusted for Known Risk Factors^*.

*<p>Adjusted for age, sex, BMI, smoking, hypertension, diabetes, hyperlipidemia, previous myocardial infarction, previous TIA, previous stroke, history of atrial fibrillation, and physical activity.</p><p>HR, hazard ratio.</p

Multivariate Cox-PH Model for the Risk of ischemic Stroke in Subjects With and Without Depression (GDS ≥5)/Antidepressant Medication, Adjusted for Age and Sex.

<p>Multivariate Cox-PH Model for the Risk of ischemic Stroke in Subjects With and Without Depression (GDS ≥5)/Antidepressant Medication, Adjusted for Age and Sex.</p

Sex-dependent multivariate Cox-PH Model for the Risk of Stroke in Subjects With and Without Depression (GDS ≥5)/Antidepressant Medication, Adjusted for Age.

<p>Sex-dependent multivariate Cox-PH Model for the Risk of Stroke in Subjects With and Without Depression (GDS ≥5)/Antidepressant Medication, Adjusted for Age.</p

Sex-dependent multivariate Cox-PH Model for the Risk of Stroke in Subjects With and Without Depression (GDS ≥5)/Antidepressant Medication, Adjusted for Known Risk Factors^*.

*<p>Adjusted for age, sex, BMI, smoking, hypertension, diabetes, hyperlipidemia, previous myocardial infarction, previous TIA, previous stroke, history of atrial fibrillation, and physical activity.</p><p>HR, hazard ratio.</p