Background: Despite the utility of administrative health data, there remains a lack of patient-centered outcome measures to meaningfully capture morbidity after traumatic brain injury (TBI). We sought to characterize and validate days at home (DAH) as a feasible measure to assess population-level moderate to severe TBI (msTBI) outcomes and health resource utilization. Methods: We utilized linked health administrative data sources to identify adults with msTBI patients presenting to trauma centers in Ontario injured between 2009-2021. DAH at 180 days reflects the total number of days spent alive and at home excluding the days spent institutionalized in acute care, rehabilitation, inpatient mental health settings or post-acute readmissions. Construct and predictive validity were determined; we additionally estimated minimally important difference (MID) in DAH180days. Results: There were 6340 patients that met inclusion criteria. Median DAH180days were 70 days (interquartile range 0-144). Increased health resource utilization at baseline, older age, increasing cranial injury severity and major extracranial injuries were significantly associated with fewer DAH180days. DAH180days was correlated to DAH counts at 1-3 years. The average MID estimate from anchor-based and distribution-based methods was 18 days. Conclusions: We introduce DAH180days as a feasible and sufficiently responsive patient-centered outcome measure with construct, predictive and face validity in an msTBI population.

Background: Employment and personal income loss after traumatic brain injury (TBI) is a major source of post-injury stress and barrier to societal reintegration for affected patients. We sought to quantify the labor market implications for tax-filing adult TBI survivors. Methods: We performed a matched difference-in-difference analysis using a national retrospective cohort of working adult TBI survivors injured between 2007-2017. Linear and logistic mixed effects regressions were used to estimate the magnitude of personal income loss and proportion of patients displaced from the workforce in the three post-injury years (Y+1 to Y+3). Results: Among 18,050 patients identified with TBI, the adjusted average loss of personal annual income was $-7,635 dollars in Y+1 and $-5,000 in Y+3. An additional -7.8% individuals were newly unemployed compared to the pre-injury baseline. For mild, moderate, and severe TBI subgroups, income loss was $-3354, $-6750, and $-17375 respectively in Y+3; the proportion of newly unemployed individuals in Y+3 was 5.8%, 9.2%, and 20% lower than baseline. We estimated 500 million dollars of incurred labor markets losses related to TBI in Canada. Conclusions: This work represents the first national cohort data quantifying the labor market implications of TBI. These results may be used to inform post-injury care pathways and vocational rehabilitation.

Stenotrophomonas maltophilia and Achromobacter xylosoxidans are emerging nosocomial, non-glucose fermenting, Gram-negative pathogens. In this nested case-control trial, independent predictors for S. maltophilia infections were hemodialysis and recent antibiotic usage (overall), while recent usage of fluoroquinolones, was independently associated with A. xylosoxidans infections. Infections were independently associated with multiple worse outcomes.

Spatially resolved transcriptomics (SRT) is a growing field that links gene expression to anatomical context. SRT approaches that use next-generation sequencing (NGS) combine RNA sequencing with histological or fluorescent imaging to generate spatial maps of gene expression in intact tissue sections. These technologies directly couple gene expression measurements with high-resolution histological or immunofluorescent images that contain rich morphological information about the tissue under study. While broad access to NGS-based spatial transcriptomic technology is now commercially available through the Visium platform from the vendor 10× Genomics, computational tools for extracting image-derived metrics for integration with gene expression data remain limited. We developed VistoSeg as a MATLAB pipeline to process, analyze and interactively visualize the high-resolution images generated in the Visium platform. VistoSeg outputs can be easily integrated with accompanying transcriptomic data to facilitate downstream analyses in common programing languages including R and Python. VistoSeg provides user-friendly tools for integrating image-derived metrics from histological and immunofluorescent images with spatially resolved gene expression data. Integration of this data enhances the ability to understand the transcriptional landscape within tissue architecture. VistoSeg is freely available at http://research.libd.org/VistoSeg/.

Africa is experiencing a rapid increase in adult obesity and associated cardiometabolic diseases (CMDs). The H3Africa AWI-Gen Collaborative Centre was established to examine genomic and environmental factors that influence body composition, body fat distribution and CMD risk, with the aim to provide insights towards effective treatment and intervention strategies. It provides a research platform of over 10 500 participants, 40–60 years old, from Burkina Faso, Ghana, Kenya and South Africa. Following a process that involved community engagement, training of project staff and participant informed consent, participants were administered detailed questionnaires, anthropometric measurements were taken and biospecimens collected. This generated a wealth of demographic, health history, environmental, behavioural and biomarker data. The H3Africa SNP array will be used for genome-wide association studies. AWI-Gen is building capacity to perform large epidemiological, genomic and epigenomic studies across several African counties and strives to become a valuable resource for research collaborations in Africa.

I conclude the SCCC21 conference highlighting some of the contrasts we heard about, some specific topics (the statistics of random fields), and discuss how some of these play out in the analysis of cosmic microwave background data. I conclude with a hopeful look at the efficacy of blind analyses in the CMB and elsewhere in cosmology.