• Canada
• 2022-2022close
• Canadian Institutes of Health Research close

Severe cognitive impairments and cognitive distortions are core to schizophrenia-spectrum disorders (SSDs) and are associated with deteriorated social functioning. Despite well-established efficacy of group psychosocial therapies targeting cognitive health in SSDs, dissemination of these programs remains limited. Remote delivery offers a promising strategy for increasing the programs' accessibility. Yet, little research has evaluated group therapies for cognitive health delivered in this way. Thus, we aimed to assess, from participants' and therapists' perspectives, the

While there have been reports of increased perinatal anxiety during the COVID-19 pandemic (Stepowicz et al., 2020), there has been a lack of research on the relative importance of objective hardship and subjective distress. In this study, we explored the extent to which resilience, tolerance of uncertainty, and cognitive appraisal of the pandemic's consequences moderate the effect of prenatal objective hardship and subjective distress due to the pandemic on 2-month postpartum anxiety.Data were collected as part of the Birth in the Time of COVID (BITTOC) study. We measured objective hardship and subjective distress, mental health, and potential psychological moderators in 419 pregnant women residing in Australia, and at two months postpartum. Hierarchical multiple regressions were used.Objective hardship and subjective distress independently predicted postpartum anxiety. All three psychological factors moderated the effect of objective hardship on anxiety. For women with low/neutral resilience, or low/moderate tolerance of uncertainty, or a negative cognitive appraisal, greater objective hardship predicted higher postpartum anxiety. Conversely, for women with high resilience, or high tolerance of uncertainty, or neutral/positive cognitive appraisal, there was no association. Only a neutral/positive cognitive appraisal significantly buffered the effect of subjective distress on anxiety.Participants self-selected themselves into the study. The generalizability of our results could be restricted to women of higher socio-economic status.These findings help us better understand options for intervention and assessment of vulnerable women during times of stress, along with the mechanisms by which COVID-related stress during pregnancy contributes to postpartum anxiety.

Objective To develop a quantitative ultrasound (QUS)- and elastography-based model to improve classification of steatosis grade, inflammation grade, and fibrosis stage in patients with chronic liver disease in comparison with shear wave elastography alone, using histopathology as the reference standard. Methods This ancillary study to a prospective institutional review-board approved study included 82 patients with non-alcoholic fatty liver disease, chronic hepatitis B or C virus, or autoimmune hepatitis. Elastography measurements, homodyned K-distribution parametric maps, and total attenuation coefficient slope were recorded. Random forests classification and bootstrapping were used to identify combinations of parameters that provided the highest diagnostic accuracy. Receiver operating characteristic (ROC) curves were computed. Results For classification of steatosis grade S0 vs. S1-3, S0-1 vs. S2-3, S0-2 vs. S3, area under the receiver operating characteristic curve (AUC) were respectively 0.60, 0.63, and 0.62 with elasticity alone, and 0.90, 0.81, and 0.78 with the best tested model combining QUS and elastography features. For classification of inflammation grade A0 vs. A1-3, A0-1 vs. A2-3, A0-2 vs. A3, AUCs were respectively 0.56, 0.62, and 0.64 with elasticity alone, and 0.75, 0.68, and 0.69 with the best model. For classification of liver fibrosis stage F0 vs. F1-4, F0-1 vs. F2-4, F0-2 vs. F3-4, F0-3 vs. F4, AUCs were respectively 0.66, 0.77, 0.72, and 0.74 with elasticity alone, and 0.72, 0.77, 0.77, and 0.75 with the best model. Conclusion Random forest models incorporating QUS and shear wave elastography increased the classification accuracy of liver steatosis, inflammation, and fibrosis when compared to shear wave elastography alone.

Background. Older adults receiving home care services often face decisions related to aging, illness, and loss of autonomy. To inform tailored shared decision making interventions, we assessed their decisional needs by asking about the most common difficult decisions, measured associated decisional conflict, and identified factors associated with it. Methods. In March 2020, we conducted a cross-sectional survey with a pan-Canadian Web-based panel of older adults (≥65 y) receiving home care services. For a difficult decision they had faced in the past year, we evaluated clinically significant decisional conflict (CSDC) using the 16-item Decisional Conflict Scale (score 0–100) with a >37.5 cutoff. To identify factors associated with CSDC, we performed descriptive, bivariable, and multivariable analyses using the stepwise selection method with an assumed entry and exit significance level of 0.15 and 0.20, respectively. Final model selection was based on the Bayesian information criterion. Results. Among 460 participants with an average age of 72.5 y, difficult decisions were, in order of frequency, about housing and safety (57.2%), managing health conditions (21.8%), and end-of-life care (8.3%). CSDC was experienced by 14.6% (95% confidence interval [CI]: 11.5%, 18.1%) of respondents on all decision points. Factors associated with CSDC included household size = 1 (OR [95% CI]: 1.81 [0.99, 3.33]; P = 0.27), household size = 3 (2.66 [0.78, 8.98]; P = 0.83), and household size = 4 (6.91 [2.23, 21.39]; P = 0.014); preferred option not matching the decision made (4.05 [2.05, 7.97]; P < 0.001); passive role in decision making (5.13 [1.78, 14.77]; P = 0.002); and lower quality of life (0.70 [0.57, 0.87]; P<0.001). Discussion. Some older adults receiving home care services in Canada experience CSDC when facing difficult decisions. Shared decision-making interventions could mitigate associated factors. Highlights This is the first study in Canada to assess the decisional needs of older adults receiving care at home and to identify their most common difficult decisions. Difficult decisions most frequently made were about housing and safety. The most significant decisional conflict was experienced by people making decisions about palliative care. When their quality-of-life score was low, older adults experienced clinically significant decision conflict.

Significance Cholesterol is one of the main components found in plasma membranes and is involved in lipid-dependent signaling enabled by integral membrane proteins such as inwardly rectifying potassium (Kir) channels. Similar to other ion channels, most of the Kir channels are down-regulated by cholesterol. One of the very few notable exceptions is Kir3.4, which is up-regulated by this important lipid. Here, we discovered and characterized a molecular switch that controls the impact (up-regulation vs. down-regulation) of cholesterol on Kir3.4. Our results provide a detailed molecular mechanism of tunable cholesterol regulation of a potassium channel.

The story recall subtest of theThe normative sample consisted of 260 healthy individuals aged 50-90 years, all from the province of Quebec, Canada. Analyses were performed to estimate the association between age, sex, and education level on one hand, and immediate and delayed recall performance, on the other hand.The results show that all sociodemographic variables are significantly associated with story recall performance. Normative data are proposed in the form of regression equations.Overall, these norms will be beneficial for the evaluation and detection of episodic memory impairment in middle-aged and older adults.

AbstractAimGlucagon‐like peptide‐1 receptor agonists (GLP1‐RA) improve cardiovascular outcomes in patients with type 2 diabetes (T2D). However, some studies suggest that their effects in patients with heart failure (HF) may be attenuated. We aimed to explore the effects of the GLP1‐RA albiglutide on HF outcomes in patients with and without HF history enrolled in the Harmony Outcomes trial.Methods and resultsHarmony Outcomes enrolled patients with T2D and cardiovascular disease randomized to either albiglutide or placebo over a median follow‐up of 1.6 years. A total of 9462 patients were included, of whom 1922 (20%) had HF history. Patients with HF had more cardiovascular comorbidities, poorer renal function, and had a three to four‐fold higher risk of HF events compared to patients without HF. Compared to placebo, the effect of albiglutide on the composite of cardiovascular death or HF hospitalization was more pronounced among patients without HF (hazard ratio [HR] 0.73, 95% confidence interval [CI] 0.56–0.95) than in patients with HF (HR 1.06, 95% CI 0.79–1.43) (interaction p = 0.062). A similar pattern was observed for HF hospitalizations (interaction p = 0.025). The effect of albiglutide on cardiovascular death, sudden death or ‘pump failure’ death, and all‐cause mortality was also attenuated among patients with HF history, but without significant interaction (p > 0.1). The benefit of albiglutide to reduce atherosclerotic events was consistent regardless of HF history.ConclusionsIn patients with T2D and cardiovascular disease, albiglutide appeared to have no effect in reducing HF‐related events among patients with HF history. These findings, placed in the context of other trials, suggest that GLP1‐RA may not improve HF outcomes in patients with HF.

Alzheimer’s disease (AD) is a progressive neurodegenerative disorder. It is one of the leading sources of morbidity and mortality in the aging population AD cardinal symptoms include memory and executive function impairment that profoundly alters a patient’s ability to perform activities of daily living. People with mild cognitive impairment (MCI) exhibit many of the early clinical symptoms of patients with AD and have a high chance of converting to AD in their lifetime. Diagnostic criteria rely on clinical assessment and brain magnetic resonance imaging (MRI). Many groups are working to help automate this process to improve the clinical workflow. Current computational approaches are focused on predicting whether or not a subject with MCI will convert to AD in the future. To our knowledge, limited attention has been given to the development of automated computer-assisted diagnosis (CAD) systems able to provide an AD conversion diagnosis in MCI patient cohorts followed longitudinally. This is important as these CAD systems could be used by primary care providers to monitor patients with MCI. The method outlined in this paper addresses this gap and presents a computationally efficient pre-processing and prediction pipeline, and is designed for recognizing patterns associated with AD conversion. We propose a new approach that leverages longitudinal data that can be easily acquired in a clinical setting (e.g., T1-weighted magnetic resonance images, cognitive tests, and demographic information) to identify the AD conversion point in MCI subjects with AUC = 84.7. In contrast, cognitive tests and demographics alone achieved AUC = 80.6, a statistically significant difference (n = 669, p &lt; 0.05). We designed a convolutional neural network that is computationally efficient and requires only linear registration between imaging time points. The model architecture combines Attention and Inception architectures while utilizing both cross-sectional and longitudinal imaging and clinical information. Additionally, the top brain regions and clinical features that drove the model’s decision were investigated. These included the thalamus, caudate, planum temporale, and the Rey Auditory Verbal Learning Test. We believe our method could be easily translated into the healthcare setting as an objective AD diagnostic tool for patients with MCI.