Background

Previous research regarding anxiety as a predictor of future cognitive decline in older adults is limited and inconsistent. We examined the independent relationship between anxiety symptoms and subsequent cognitive decline.

Methods

We included 2,818 community-dwelling older men (mean age = 76.1, SD ±5.3 years) who were followed on an average for 3.4 years. We assessed anxiety symptoms at baseline using the Goldberg Anxiety Scale (GAS; range = 0-9). We assessed cognitive function at baseline and at two subsequent visits using the Modified Mini-Mental State Examination (3MS; global cognition) and the Trails B test (executive function).

Results

At baseline, there were 690 (24%) men with mild anxiety symptoms (GAS 1-4) and 226 (8%) men with moderate/severe symptoms (GAS 5-9). Men with anxiety symptoms were more likely to have depressed mood, poor sleep, more chronic medical conditions, and more impairment in activities of daily living compared to those with no anxiety symptoms. Compared to those with no anxiety symptoms at baseline, men with any anxiety symptoms were more likely to have substantial worsening in Trails B completion time (OR = 1.56, 95% CI 1.19, 2.05). The association was attenuated after adjusting for potential confounders, including depression and poor sleep, but remained significant (OR = 1.40, 95% CI 1.04, 1.88).

Conclusion

In cognitively healthy older men, mild anxiety symptoms may potentially predict future decline in executive functioning. Anxiety is likely a manifestation of an underlying neurodegenerative process rather than a cause.

Objectives

Research is limited and findings conflict regarding anxiety as a predictor of future cognitive decline in the oldest old persons. We examined the relationship between levels of and changes in anxiety symptoms, and subsequent dementia and mild cognitive impairment (MCI) in the oldest old women.

Method

We conducted secondary analyses of data collected from 1425 community-dwelling women (mean age = 82.8, SD ±3.1 years) followed on average for five years. The Goldberg Anxiety Scale was used to assess anxiety symptoms at baseline, and an expert clinical panel adjudicated dementia and MCI at follow-up. Participants with probable cognitive impairment at baseline were excluded.

Results

At baseline, 190 (13%) women had moderate/severe anxiety symptoms and 403 (28%) had mild anxiety symptoms. Compared with those with no anxiety symptoms at baseline, women with mild anxiety symptoms were more likely to develop dementia at follow-up (multivariable-adjusted odds ratio = 1.66, 95% confidence interval 1.12-2.45). No significant association was observed between anxiety symptoms and MCI.

Conclusion

In the oldest old women, our findings suggest that mild anxiety symptoms may predict future risk of dementia, but not MCI. Future studies should explore potential biological mechanisms underlying associations of anxiety with cognitive impairment.

Background: The American Thoracic Society, U.S. Centers for Disease Control and Prevention, European Respiratory Society, and Infectious Diseases Society of America jointly sponsored this new practice guideline on the treatment of drug-resistant tuberculosis (DR-TB). The document includes recommendations on the treatment of multidrug-resistant TB (MDR-TB) as well as isoniazid-resistant but rifampin-susceptible TB.Methods: Published systematic reviews, meta-analyses, and a new individual patient data meta-analysis from 12,030 patients, in 50 studies, across 25 countries with confirmed pulmonary rifampin-resistant TB were used for this guideline. Meta-analytic approaches included propensity score matching to reduce confounding. Each recommendation was discussed by an expert committee, screened for conflicts of interest, according to the Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) methodology.Results: Twenty-one Population, Intervention, Comparator, and Outcomes questions were addressed, generating 25 GRADE-based recommendations. Certainty in the evidence was judged to be very low, because the data came from observational studies with significant loss to follow-up and imbalance in background regimens between comparator groups. Good practices in the management of MDR-TB are described. On the basis of the evidence review, a clinical strategy tool for building a treatment regimen for MDR-TB is also provided.Conclusions: New recommendations are made for the choice and number of drugs in a regimen, the duration of intensive and continuation phases, and the role of injectable drugs for MDR-TB. On the basis of these recommendations, an effective all-oral regimen for MDR-TB can be assembled. Recommendations are also provided on the role of surgery in treatment of MDR-TB and for treatment of contacts exposed to MDR-TB and treatment of isoniazid-resistant TB.

Accurately quantifying species' area requirements is a prerequisite for effective area-based conservation. This typically involves collecting tracking data on species of interest and then conducting home-range analyses. Problematically, autocorrelation in tracking data can result in space needs being severely underestimated. Based on the previous work, we hypothesized the magnitude of underestimation varies with body mass, a relationship that could have serious conservation implications. To evaluate this hypothesis for terrestrial mammals, we estimated home-range areas with global positioning system (GPS) locations from 757 individuals across 61 globally distributed mammalian species with body masses ranging from 0.4 to 4000 kg. We then applied block cross-validation to quantify bias in empirical home-range estimates. Area requirements of mammals <10 kg were underestimated by a mean approximately15%, and species weighing approximately100 kg were underestimated by approximately50% on average. Thus, we found area estimation was subject to autocorrelation-induced bias that was worse for large species. Combined with the fact that extinction risk increases as body mass increases, the allometric scaling of bias we observed suggests the most threatened species are also likely to be those with the least accurate home-range estimates. As a correction, we tested whether data thinning or autocorrelation-informed home-range estimation minimized the scaling effect of autocorrelation on area estimates. Data thinning required an approximately93% data loss to achieve statistical independence with 95% confidence and was, therefore, not a viable solution. In contrast, autocorrelation-informed home-range estimation resulted in consistently accurate estimates irrespective of mass. When relating body mass to home range size, we detected that correcting for autocorrelation resulted in a scaling exponent significantly >1, meaning the scaling of the relationship changed substantially at the upper end of the mass spectrum.