Modeling the Spatial and Temporal Dependence in fMRI Data

Summary Functional magnetic resonance imaging (fMRI) data sets are large and characterized by complex dependence structures driven by highly sophisticated neurophysiology and aspects of the experimental designs. Typical analyses investigating task‐related changes in measured brain activity use a two‐stage procedure in which the first stage involves subject‐specific models and the second‐stage specifies group (or population) level parameters. Customarily, the first‐level accounts for temporal correlations between the serial scans acquired during one scanning session. Despite accounting for these correlations, fMRI studies often include multiple sessions and temporal dependencies may persist between the corresponding estimates of mean neural activity. Further, spatial correlations between brain activity measurements in different locations are often unaccounted for in statistical modeling and estimation. We propose a two‐stage, spatio‐temporal, autoregressive model that simultaneously accounts for spatial dependencies between voxels within the same anatomical region and for temporal dependencies between a subject's estimates from multiple sessions. We develop an algorithm that leverages the special structure of our covariance model, enabling relatively fast and efficient estimation. Using our proposed method, we analyze fMRI data from a study of inhibitory control in cocaine addicts.     

Case–Case Comparison of Candida auris Versus Other Candida Species Bloodstream Infections: Results of an Outbreak Investigation in Colombia

Background

Candida auris is an emerging multidrug-resistant yeast that causes outbreaks in healthcare settings around the world. In 2016, clinicians and public health officials identified patients with C. auris bloodstream infections (BSI) in Colombian healthcare facilities. To evaluate potential risk factors and outcomes for these infections, we investigated epidemiologic and clinical features of patients with C. auris and other Candida species BSI.

Methods

We performed a retrospective case-case investigation in four Colombian acute care hospitals, defining a case as Candida spp. isolated from blood culture during January 2015–September 2016. C. auris BSI cases were compared to other Candida species BSI cases. Odds ratio (OR), estimated using logistic regression, was used to assess the association between risk factors and outcomes.

Results

We analyzed 90 patients with BSI, including 40 with C. auris and 50 with other Candida species. All had been admitted to the intensive care unit (ICU). No significant demographic differences existed between the two groups. The following variables were independently associated with C. auris BSI:?≥?15 days of pre-infection ICU stay (OR: 5.62, CI: 2.04–15.5), evidence of severe sepsis (OR: 3.70, CI 1.19–11.48), and diabetes mellitus (OR 5.69, CI 1.01–31.9).

Conclusion

Patients with C. auris BSI had longer lengths of ICU stay than those with other candidemias, suggesting that infections are acquired during hospitalization. This is different from other Candida infections, which are usually thought to result from autoinfection with host flora.