Better marital adjustment is associated with lower disease activity in early inflammatory arthritis

Aim: The aim of this study was to examine the association between marital adjustment and disease outcomes in patients with early inflammatory arthritis. Materials and methods: Patients with average disease duration of 7.66 ± 3.79 months were recruited from a larger early inflammatory arthritis registry, which recorded sociodemographic data and disease characteristics. The acute phase reactant C-reactive protein (CRP) levels were measured and disease activity was estimated using the Disease Activity Score in 28 joints (DAS28). Patient and spouse perceived marital adjustment was assessed by the Dyadic Adjustment Scale (DAS). Results: The study sample consisted of 73 patients living with their spouses. The mean age of the study participants was 54.30 ± 12.09 years and 64.4% were female. Patient-perceived marital adjustment (DAS-Patient) was negatively correlated to CRP (P = 0.007) and DAS28 (P = 0.002). On multivariate analysis, DAS-Patient contributed to the dependent variable DAS28 after controlling for CRP. Conclusion: The current study indicates that better marital adjustment is associated with lower disease activity. The possible reciprocal relationship between marital adjustment and illness highlights the relevance for clinicians to include both patients and their spouses in interventions

The Montreal model: an integrative biomedical-psychedelic approach to ketamine for severe treatment-resistant depression

BackgroundSubanesthetic ketamine has accumulated meta-analytic evidence for rapid antidepressant effects in treatment-resistant depression (TRD), resulting in both excitement and debate. Many unanswered questions surround ketamine’s mechanisms of action and its integration into real-world psychiatric care, resulting in diverse utilizations that variously resemble electroconvulsive therapy, conventional antidepressants, or serotonergic psychedelics. There is thus an unmet need for clinical approaches to ketamine that are tailored to its unique therapeutic properties.MethodsThis article presents the Montreal model, a comprehensive biopsychosocial approach to ketamine for severe TRD refined over 6 years in public healthcare settings. To contextualize its development, we review the evidence for ketamine as a biomedical and as a psychedelic treatment of depression, emphasizing each perspectives’ strengths, weaknesses, and distinct methods of utilization. We then describe the key clinical experiences and research findings that shaped the model’s various components, which are presented in detail.ResultsThe Montreal model, as implemented in a recent randomized clinical trial, aims to synergistically pair ketamine infusions with conventional and psychedelic biopsychosocial care. Ketamine is broadly conceptualized as a brief intervention that can produce windows of opportunity for enhanced psychiatric care, as well as powerful occasions for psychological growth. The model combines structured psychiatric care and concomitant psychotherapy with six ketamine infusions, administered with psychedelic-inspired nonpharmacological adjuncts including rolling preparative and integrative psychological support.DiscussionOur integrative model aims to bridge the biomedical-psychedelic divide to offer a feasible, flexible, and standardized approach to ketamine for TRD. Our learnings from developing and implementing this psychedelic-inspired model for severe, real-world patients in two academic hospitals may offer valuable insights for the ongoing roll-out of a range of psychedelic therapies. Further research is needed to assess the Montreal model’s effectiveness and hypothesized psychological mechanisms

Evaluating the Clinical Feasibility of an Artificial Intelligence-Powered, Web-Based Clinical Decision Support System for the Treatment of Depression in Adults: Longitudinal Feasibility Study.

BACKGROUND: Approximately two-thirds of patients with major depressive disorder do not achieve remission during their first treatment. There has been increasing interest in the use of digital, artificial intelligence-powered clinical decision support systems (CDSSs) to assist physicians in their treatment selection and management, improving the personalization and use of best practices such as measurement-based care. Previous literature shows that for digital mental health tools to be successful, the tool must be easy for patients and physicians to use and feasible within existing clinical workflows. OBJECTIVE: This study aims to examine the feasibility of an artificial intelligence-powered CDSS, which combines the operationalized 2016 Canadian Network for Mood and Anxiety Treatments guidelines with a neural network-based individualized treatment remission prediction. METHODS: Owing to the COVID-19 pandemic, the study was adapted to be completed entirely remotely. A total of 7 physicians recruited outpatients diagnosed with major depressive disorder according to the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition criteria. Patients completed a minimum of one visit without the CDSS (baseline) and 2 subsequent visits where the CDSS was used by the physician (visits 1 and 2). The primary outcome of interest was change in appointment length after the introduction of the CDSS as a proxy for feasibility. Feasibility and acceptability data were collected through self-report questionnaires and semistructured interviews. RESULTS: Data were collected between January and November 2020. A total of 17 patients were enrolled in the study; of the 17 patients, 14 (82%) completed the study. There was no significant difference in appointment length between visits (introduction of the tool did not increase appointment length; F2,24=0.805; mean squared error 58.08; P=.46). In total, 92% (12/13) of patients and 71% (5/7) of physicians felt that the tool was easy to use; 62% (8/13) of patients and 71% (5/7) of physicians rated that they trusted the CDSS. Of the 13 patients, 6 (46%) felt that the patient-clinician relationship significantly or somewhat improved, whereas 7 (54%) felt that it did not change. CONCLUSIONS: Our findings confirm that the integration of the tool does not significantly increase appointment length and suggest that the CDSS is easy to use and may have positive effects on the patient-physician relationship for some patients. The CDSS is feasible and ready for effectiveness studies. TRIAL REGISTRATION: ClinicalTrials.gov NCT04061642; http://clinicaltrials.gov/ct2/show/NCT04061642

Search for dark matter produced in association with bottom or top quarks in √s = 13 TeV pp collisions with the ATLAS detector

A search for weakly interacting massive particle dark matter produced in association with bottom or top quarks is presented. Final states containing third-generation quarks and miss- ing transverse momentum are considered. The analysis uses 36.1 fb−1 of proton–proton collision data recorded by the ATLAS experiment at √s = 13 TeV in 2015 and 2016. No significant excess of events above the estimated backgrounds is observed. The results are in- terpreted in the framework of simplified models of spin-0 dark-matter mediators. For colour- neutral spin-0 mediators produced in association with top quarks and decaying into a pair of dark-matter particles, mediator masses below 50 GeV are excluded assuming a dark-matter candidate mass of 1 GeV and unitary couplings. For scalar and pseudoscalar mediators produced in association with bottom quarks, the search sets limits on the production cross- section of 300 times the predicted rate for mediators with masses between 10 and 50 GeV and assuming a dark-matter mass of 1 GeV and unitary coupling. Constraints on colour- charged scalar simplified models are also presented. Assuming a dark-matter particle mass of 35 GeV, mediator particles with mass below 1.1 TeV are excluded for couplings yielding a dark-matter relic density consistent with measurements