The first casualty of COVID-19 for patients nearing death was human dignity: Understanding the experience of palliative care patients during the COVID-19 pandemic.

The COVID-19 pandemic changed the way people lived, but also the way they died. It accentuated the physical, psychological, social, and spiritual vulnerabilities of patients approaching death. This study explored the lived experience of palliative inpatients during the pandemic. We conducted interviews with 22 palliative inpatients registered in a Canadian urban palliative care program, aimed to uncover how the pandemic impacted participants' experiences of approaching end-of-life. The reflexive thematic analysis revealed 6 themes: putting off going into hospital, the influence of the pandemic on hospital experience, maintaining dignity in care, emotional impact of nearing death, making sense of end-of-life circumstances and coping with end-of-life. Findings highlight the vulnerability of patients approaching death, and how that was accentuated during the pandemic. Findings reveal how the pandemic strained, threatened, and undermined human connectedness. These lived experiences of palliative inpatients offer guidance for future pandemic planning and strategies for providing optimal palliative care.

"It took so much of the humanness away": Health care professional experiences providing care to dying patients during COVID-19.

COVID-19 has affected healthcare in profound and unprecedented ways, distorting the experiences of patients and healthcare professionals (HCPs) alike. One area that has received little attention is how COVID-19 affected HCPs caring for dying patients. The goal of this study was to examine the experiences of HCPs working with dying patients during the COVID-19 pandemic. Between July 2020-July 2021, we recruited HCPs (N = 25) across Canada. We conducted semi-structured interviews, using a qualitative study design rooted in constructivist grounded theory methodology. The core themes identified were the impact of the pandemic on care utilization, the impact of infection control measures on provision of care, moral distress in the workplace, impact on psychological wellbeing, and adaptive strategies to help HCPs manage emotions and navigate pandemic imposed changes. This is the first Canadian study to qualitatively examine the experiences of HCPs providing care to dying patients during the COVID-19 pandemic. Implications include informing supportive strategies and shaping policies for HCPs providing palliative care.

The comorbidity and cognition in multiple sclerosis (CCOMS) neuroimaging protocol: Study rationale, MRI acquisition, and minimal image processing pipelines.

The Comorbidity and Cognition in Multiple Sclerosis (CCOMS) study represents a coordinated effort by a team of clinicians, neuropsychologists, and neuroimaging experts to investigate the neural basis of cognitive changes and their association with comorbidities among persons with multiple sclerosis (MS). The objectives are to determine the relationships among psychiatric (e.g., depression or anxiety) and vascular (e.g., diabetes, hypertension, etc.) comorbidities, cognitive performance, and MRI measures of brain structure and function, including changes over time. Because neuroimaging forms the basis for several investigations of specific neural correlates that will be reported in future publications, the goal of the current manuscript is to briefly review the CCOMS study design and baseline characteristics for participants enrolled in the three study cohorts (MS, psychiatric control, and healthy control), and provide a detailed description of the MRI hardware, neuroimaging acquisition parameters, and image processing pipelines for the volumetric, microstructural, functional, and perfusion MRI data.

Spatial normalization of multiple sclerosis brain MRI data depends on analysis method and software package.

BACKGROUND: Spatially normalizing brain MRI data to a template is commonly performed to facilitate comparisons between individuals or groups. However, the presence of multiple sclerosis (MS) lesions and other MS-related brain pathologies may compromise the performance of automated spatial normalization procedures. We therefore aimed to systematically compare five commonly used spatial normalization methods for brain MRI - including linear (affine), and nonlinear MRIStudio (LDDMM), FSL (FNIRT), ANTs (SyN), and SPM (CAT12) algorithms - to evaluate their performance in the presence of MS-related pathologies. METHODS: 3 Tesla MRI images (T1-weighted and T2-FLAIR) were obtained for 20 participants with MS from an ongoing cohort study (used to assess a real dataset) and 1 healthy control participant (used to create a simulated lesion dataset). Both raw and lesion-filled versions of each participant's T1-weighted brain images were warped to the Montreal Neurological Institute (MNI) template using all five normalization approaches for the real dataset, and the same procedure was then repeated using the simulated lesion dataset (i.e., total of 400 spatial normalizations). As an additional quality-assurance check, the resulting deformations were also applied to the corresponding lesion masks to evaluate how each processing pipeline handled focal white matter lesions. For each normalization approach, inter-subject variability (across normalized T1-weighted images) was quantified using both mutual information (MI) and coefficient of variation (COV), and the corresponding normalized lesion volumes were evaluated using paired-sample t-tests. RESULTS: All four nonlinear warping methods outperformed conventional linear normalization, with SPM (CAT12) yielding the highest MI values, lowest COV values, and proportionately-scaled lesion volumes. Although lesion-filling improved spatial normalization accuracy for each of the methods tested, these effects were small compared to differences between normalization algorithms. CONCLUSIONS: SPM (CAT12) warping, ideally combined with lesion-filling, is recommended for use in future MS brain imaging studies requiring spatial normalization.