Do social support and community engagement act as mechanisms in the association between neighbourhood income inequality and the mental health of mothers in Calgary,Canada? A mediation analysis

PurposeAccording to the social determinants of health framework, income inequality is a potential risk factor for adverse mental health. However, few studies have explored the mechanisms suspected to mediate this relationship. The current study addresses this gap through a mediation analysis to determine if social support and community engagement act as mediators linking neighbourhood income inequality to maternal anxiety and depressive symptoms within a cohort of new mothers living in the City of Calgary, Canada.MethodsData collected at three years postpartum from mothers belonging to the All Our Families (AOF) cohort were used in the current study. Maternal data were collected between 2012 and 2015 and linked to neighbourhood socioeconomic data from the 2006 Canadian Census. Income inequality was measured using Gini coefficients derived from 2006 after-tax census data. Generalized structural equation models were used to quantify the associations between income inequality and mental health symptoms, and to assess the potential direct and indirect mediating effects of maternal social support and community engagement.ResultsIncome inequality was not significantly associated with higher depressive symptoms (β = 0.32, 95%CI = −0.067, 0.70), anxiety symptoms (β = 0.11, 95%CI = −0.39, 0.60), or lower social support. Income inequality was not associated with community engagement. For the depression models, higher social support was significantly associated with lower depressive symptoms (β = −0.13, 95%CI = −0.15, −0.097), while community engagement was not significantly associated with depressive symptoms (β = 0.059, 95%CI = −0.15, 0.27). Similarly, for the anxiety models, lower anxiety symptoms were significantly associated with higher levels of social support (β = −0.17, 95%CI = −0.20, −0.13) but not with higher levels of community engagement (β = 0.14, 95%CI = −0.14, 0.41).ConclusionThe current study did not find clear evidence for social support or community engagement mediating the relationship between neighbourhood income inequality and maternal mental health. Future investigations should employ a broader longitudinal approach to capture changes in income inequality, potential mediators, and mental health symptomatology over time.     

Skin3D: Detection and longitudinal tracking of pigmented skin lesions in 3D total-body textured meshes

We present an automated approach to detect and longitudinally track skin lesions on 3D total-body skin surface scans. The acquired 3D mesh of the subject is unwrapped to a 2D texture image, where a trained objected detection model, Faster R-CNN, localizes the lesions within the 2D domain. These detected skin lesions are mapped back to the 3D surface of the subject and, for subjects imaged multiple times, we construct a graph-based matching procedure to longitudinally track lesions that considers the anatomical correspondences among pairs of meshes and the geodesic proximity of corresponding lesions and the inter-lesion geodesic distances.We evaluated the proposed approach using 3DBodyTex, a publicly available dataset composed of 3D scans imaging the coloured skin (textured meshes) of 200 human subjects. We manually annotated locations that appeared to the human eye to contain a pigmented skin lesion as well as tracked a subset of lesions occurring on the same subject imaged in different poses. Our results, when compared to three human annotators, suggest that the trained Faster R-CNN detects lesions at a similar performance level as the human annotators. Our lesion tracking algorithm achieves an average matching accuracy of 88% on a set of detected corresponding pairs of prominent lesions of subjects imaged in different poses, and an average longitudinal accuracy of 71% when encompassing additional errors due to lesion detection. As there currently is no other large-scale publicly available dataset of 3D total-body skin lesions, we publicly release over 25,000 3DBodyTex manual annotations, which we hope will further research on total-body skin lesion analysis.     

Rationale for a Clinical Trial That Compares Acute Stroke Rehabilitation at Inpatient Rehabilitation Facilities to Skilled Nursing Facilities: Challenges and Opportunities

In the United States, approximately 400,000 patients with acute stroke are discharged annually to inpatient rehabilitation facilities (IRFs) or skilled nursing facilities (SNFs). Typically, IRFs provide time-intensive therapy for an average of 2-3 weeks, whereas SNFs provide more moderately intensive therapy for 4-5 weeks. The factors that influence discharge to an IRF or SNF are multifactorial and poorly understood. The complexity of these factors in combination with subjective clinical indications contributes to large variations in the use of IRFs and SNFs. This has significant financial implications for health care expenditure, given that stroke rehabilitation at IRFs costs approximately double that at SNFs. To control health care spending without compromising outcomes, the Institute of Medicine has stated that policy reforms that promote more efficient use of IRFs and SNFs are critically needed. A major barrier to the formulation of such policies is the highly variable and low-quality evidence for the comparative effectiveness of IRF- vs SNF-based stroke rehabilitation. The current evidence is limited by the inability of observational data to control for residual confounding, which contributes to substantial uncertainty around any magnitude of benefit for IRF- vs SNF-based care. Furthermore, it is unclear which specific patients would receive the most benefit from each setting. A randomized controlled trial addresses these issues, because random treatment allocation facilitates an equitable distribution of measured and unmeasured confounders. We discuss several measurement, practical, and ethical issues of a trial and provide our rationale for design suggestions that overcome some of these issues.     

Performance of risk prediction models for post-operative mortality in patients undergoing liver resection

BackgroundLiver resection is commonly performed for hepatic tumors, however preoperative risk stratification remains challenging. We evaluated the performance of contemporary prediction models for short-term mortality after liver resection in patients with and without cirrhosis.MethodsThis retrospective cohort study examined National Surgical Quality Improvement Program data. We included patients who underwent liver resections from 2014 to 2019. VOCAL-Penn, MELD, MELD-Na, ALBI, and Mayo risk scores were evaluated in terms of model discrimination and calibration for 30-day post-operative mortality.ResultsA total 15,198 patients underwent liver resection, of whom 249 (1.6%) experienced 30-day post-operative mortality. The VOCAL-Penn score had the highest discrimination (area under the ROC curve [AUC] 0.74) compared to all other models. The VOCAL-Penn score similarly outperformed other models in patients with (AUC 0.70) and without (AUC 0.74) cirrhosis.ConclusionThe VOCAL-Penn score demonstrated superior predictive performance for 30-day post-operative mortality after liver resection as compared to existing clinical standards.     

Biological Disease-Modifying Antirheumatic Drugs and Osteoporotic Fracture Risk in Patients with Rheumatoid Arthritis: A Danish Cohort Study

ObjectivesClinical trials have shown a beneficial effect from biological disease-modifying antirheumatic drugs (bDMARDs) on hand or axial bone loss in patients with rheumatoid arthritis; however, it is unclear if this translates to a reduced fracture risk. We investigated the effect of bDMARDs on osteoporotic fracture risk compared to no biological treatment in rheumatoid arthritis.MethodsA cohort of patients with rheumatoid arthritis aged 18+ from DANBIO was linked to population-based health registries in Denmark (2006-2016). Adopting a prevalent new-user design, we matched bDMARD users to bDMARD-naïve patients using time-conditional propensity scores. The risk of incident osteoporotic fractures (including hip, vertebrae, humerus, and forearm) was estimated among the matched patients by Cox proportional hazards models.ResultsOut of 24,678 patients with rheumatoid arthritis, 4265 bDMARD users were matched to the same number of bDMARD-naïve patients (mean age 56.2 years, 74% female). During follow-up, 229 osteoporotic fractures occurred among bDMARD users and 205 fractures among bDMARD-naïve patients (incidence rates 12.1 and 13.0 per 1000 person-years, respectively). The use of bDMARDs was not associated with a reduced risk of osteoporotic fractures among patients with rheumatoid arthritis (hazard ratio 0.97, 95% confidence interval 0.78-1.20), compared with no biological treatment. The risk estimates were similar for all osteoporotic fracture sites.ConclusionWe found no independent beneficial effect from using bDMARDs on reducing the risk of osteoporotic fractures in patients with rheumatoid arthritis.