Jess G. Fiedorowicz

Background: Depression and anxiety are common in chronic obstructive pulmonary disease (COPD) and are linked to adverse clinical outcomes. Their association with all-cause mortality has not been examined in COPDGene. We assessed this association in non-Hispanic white (NHW) and African American (AA) ever-smokers. We also tested effect modification and compared mortality by antidepressant use.Methods: We analyzed COPDGene participants who completed the Hospital Anxiety and Depression Scale (HADS) at the Phase 2 visit. Depressive (HADS-D) and anxiety (HADS-A) symptoms were modeled per SD and as elevated (≥8). Cox models estimated hazard ratios (HRs) for all-cause mortality in each cohort, adjusting for demographic, socioeconomic, smoking, clinical, and comorbidity variables.Results: Of 3,848 NHW and 1,155 AA participants, 828 (21.5%) and 237 (20.5%) died. Depressive symptoms (per SD) were associated with mortality among NHW (HR: 1.34, 95% CI: [1.25, 1.44]) and AA (1.31, [1.13, 1.52]) participants. Elevated depressive symptoms were associated with mortality among NHW (1.72, [1.40, 2.10]) but not significantly among AA (1.42, [0.97, 2.08]) participants. Anxiety symptoms (per SD) were associated with mortality among NHW (1.22, [1.13, 1.32]) but not AA (1.04, [0.89, 1.22]) participants. No interaction test met the multiplicity threshold. Among NHW participants, elevated depressive symptoms carried higher mortality both with (1.85, [1.34, 2.55]) and without (1.59, [1.24, 2.03]) antidepressant use.Conclusions: Depressive symptoms independently predicted all-cause mortality in NHW and AA ever-smokers. Anxiety symptoms predicted mortality only among NHW participants. These symptoms are prognostic markers that warrant clinical attention and further study.

Metabolic, inflammatory, and neurotrophic measures may provide complementary insight into biological heterogeneity underlying treatment-resistant depression and response to ketamine-based treatments. However, biomarker studies of ketamine treatment have focused on individual markers or biological domains, most commonly inflammatory or neurotrophic, while metabolic measures remain comparatively understudied. All three domains were examined in 30 individuals with treatment-resistant depression receiving eight intranasal esketamine treatments in a real-world clinical setting. Depressive symptoms, metabolic, inflammatory, and neurotrophic biomarkers were assessed before and after treatment. Esketamine treatment was associated with a reduction in Montgomery Åsberg Depression Rating Scale scores (mean decrease 7.7 points, p < 0.001; Cohen’s d = -0.90). Greater metabolic burden, quantified using a composite based on metabolic syndrome criteria and comprising waist circumference, triglycerides, HDL cholesterol, blood pressure, and fasting glucose, was associated with greater reductions in depressive symptoms following treatment, after adjustment for baseline depressive symptom severity (p = 0.032). Fasting glucose decreased following esketamine treatment (mean decrease 1.58 mmol/L, pFDR < 0.001; Cohen’s d = −1.61), without significant changes in body weight. In contrast, baseline inflammatory and neurotrophic composites were not associated with changes in depressive symptoms, and no inflammatory or neurotrophic biomarkers showed significant longitudinal changes. In sensitivity analyses excluding participants with diabetes or prescribed glucose-altering medications, higher baseline serum vascular endothelial growth factor (VEGF) was associated with greater reductions in depressive symptoms (pFDR = 0.043). These findings highlight the value of a multidomain approach and identify metabolic measures as an important domain for understanding heterogeneity in response to esketamine.

Background: Somatic and psychiatric illnesses and multimorbidities increase stress-vulnerability and decrease well-being. Objective: We aimed to identify high-risk disorder profiles for lower well-being and well-being decline under stress, modelling COVID-19 as a natural experiment. Methods: The global Collaborative Outcomes Study on Health and Functioning during Infection Times survey assessed the World Health Organization-Five Well-being Index (WHO-5) (0–100) retrospectively pre-pandemic and intra-pandemically. Mixed-effects models, controlling for demographic/pandemic-related covariates, examined coprimary outcomes: total pre-pandemic WHO-5 and pre-to-intra-pandemic change (estimating β); pre-pandemic WHO-5 pre-pandemic: autism-spectrum disorder (β=−7.00±2.93/OR=1.27–2.65), schizophrenia/schizoaffective disorder (β=−5.39±3.42/OR=1.09–2.64); pre-to-intra-pandemic: major depressive disorder (β=−2.45±0.89/OR=1.25–1.55), post-traumatic stress disorder (β=−1.98±1.42/OR=1.19–1.67)) versus somatic disorders ( pre-pandemic: diarrhoea (β=−3.29±2.49/OR=1.11–2.15), chronic skin disease (CSD) (β=−2.53±1.44/OR=1.11–1.65); pre-to-intra-pandemic: CSD (β=−2.31±1.47/OR=1.23–1.75), injury (β=−2.22±0.99/OR=1.11–1.40)). Multimorbidities were associated with non-linear/supra-additive adverse outcomes beyond single disorders ( pre-pandemic: anorexia nervosa+schizophrenia/schizoaffective disorder (β=−27.58±12.71/OR=1.41–19.94), inflammatory bowel disease+psychosis (β=−24.89±10.59/OR=2.68–24.25), stroke+osteoarthritis (β=−13.68±7.33/OR=1.23–6.48); pre-to-intra-pandemic: haemorrhoids+obsessive-compulsive disorder (β=−8.86±6.54/OR=1.22–5.21), binge-eating disorder/bulimia nervosa+social anxiety disorder (β=−6.87±5.49/OR=0.78–2.85), back pain+retinopathy (β=−6.55±6.54/OR=1.04–4.69)). Dose–response relationships were observed between the number of disorders and poorer well-being ( pre-pandemic per diagnosis: psychiatric (β=−1.22±0.23/OR=1.11–1.17), somatic (β=−0.21±0.13/OR=1.02–1.05); pre-to-intra-pandemic per diagnosis: psychiatric (β=−0.37±0.24/OR=1.04–1.10)). Conclusions: Poor well-being and further decline under stress were observed particularly with psychiatric illnesses and complex psychiatric and mixed psychiatric-somatic multimorbidity. Clinical implications: The finding of supra-additive multimorbidity burden highlights a need for targeted care models, beyond individual conditions. Vulnerable groups require support during crises, beyond COVID-19.

Background: Higher time in sedentary behavior and insufficient physical activity are very common in bipolar disorder (BD). Whereas physical activity and exercise offer significant benefits across mental health, brain health, and heart health in BD. The International Society for Bipolar Disorders Nutrition and Exercise Task Force (NExT) synthesized evidence to evaluate the impacts of sedentary behavior, physical activity, and exercise on illness course, physical health, and treatment outcomes. Methods: A best‐evidence synthesis was conducted using a question‐and‐answer format. We searched PsycINFO, SPORTDiscus, Embase, PubMed, and Web of Science from inception to March 1st, 2026, supplemented by reference lists and existing guidelines. Search terms included combinations of physical activity, exercise, sedentary behavior, and bipolar disorder‐related terms. Results: Observational studies show that individuals with BD exhibit significantly higher sedentary behavior and lower physical activity compared to the general population, with notable discrepancies between self‐reported and objective measurements. Evidence on physical activity's protective role against BD onset is mixed, with some prospective and Mendelian randomization studies suggesting reduced risk, while others report bidirectional or null associations. Preliminary findings from clinical trials indicate that exercise improves overall functioning, reduces mood episode frequency and hospitalizations, and alleviates depressive symptoms, with one pilot study showing an 82% antidepressant response rate. Exercise also shows potential to reduce anxiety and improve sleep, though robust data are limited. Conclusions: Despite limited high‐quality evidence, physical activity and exercise demonstrate promising physical and mental health benefits for individuals with BD. Future research should prioritize multicenter randomized controlled trials, enhanced assessment tools, and accessible, tailored programs to integrate physical activity into routine BD management.

Introduction: Circadian dysfunction is involved in the pathophysiology of bipolar disorders (BD), and circadian‐based interventions are gaining recognition in their management. Moreover, basic and epidemiologic research has generated findings inspiring circadian‐informed self‐ and clinician‐management strategies. Despite these gains, many Clinical Practice Guidelines and clinical training programs have not incorporated this evidence in their recommendations and curricula. This International Society for Bipolar Disorders (ISBD) Chronobiology and Chronotherapy Task Force position paper reports a Delphi‐based expert consensus on what is essential for mental health clinicians to know about the chronobiology and chronotherapy of BD. Methods: An initial pool of statements was extracted from academic and grey literature, and experts could suggest additional statements. Statements were rated on a 5‐point scale (‘essential’; ‘important’; ‘don't know/depends’; ‘unimportant’; ‘should not be included’). Consensus was reached when statements were rated as essential or important by ≥ 80% of experts. Results: Thirty experts from 15 countries in Europe, North and South America, and the Asia Pacific participated (mean age of 55.3 years [SD = 11.8]; 40% female; 83% psychiatrists; mean clinical experience of 26 years [SD = 10.8]). Eight‐hundred‐and‐thirty‐seven statements were rated across three rounds. Consensus was reached on 342 statements spanning four major themes: basic circadian science; circadian health and disruption; chronobiology of BD; and six chronotherapies (e.g., protocols, outcomes, risks/contraindications). Conclusions: An expert consensus was obtained on the essential information about the chronobiology and chronotherapy of BD, intended to help clinicians optimise their management of BD. Dissemination of this knowledge is expected to enhance the training and efficacy of clinicians.

Background: Social robots (SRs) are innovative tools in health care, offering both medical and psychological support for patients with heart failure (HF). For successful implementation, patient acceptability of SRs is crucial. Living in urban areas and having a lower comorbidity burden have been linked to higher acceptability; however, the role of psychological factors remains underexplored. Objective: This study aimed to examine the associations between negative (eg, depression and anxiety) and positive (eg, optimism) psychological factors and personality traits (eg, openness and extraversion) with SR acceptability in patients with HF. Methods: Patients with HF watched brief videos about SRs and completed validated measures of depressive symptoms (Patient Health Questionnaire-9), anxiety symptoms (Generalized Anxiety Disorder-7), positive psychological well-being (Brief Inventory of Thriving), and personality traits (Ten-Item Personality Inventory). Medical information was extracted from patients’ records. SR acceptability was assessed using the Unified Theory of Acceptance and Use of Technology (UTAUT). Pearson correlations and multiple linear regression, adjusted for age, sex, smart technology experience, urbanicity, and comorbidities, were conducted. Results: Of the 101 patients (women: n=36, 35.6%, mean age 68, SD 10 y), 23% (23/101) scored in the clinical range for depression, and 17% (17/101) scored in the clinical range for anxiety. Well-being scores were moderate, and conscientiousness and agreeableness were the most common. UTAUT behavioral intention was moderate; 69% (67/97) of participants were likely to use an SR if available. Well-being scores correlated positively with SR acceptability in 4 of 5 UTAUT subscales, whereas no significant bivariate associations were observed for psychological distress or personality traits. In the multiple regression models, higher Brief Inventory of Thriving scores were associated with increased SR acceptability, including UTAUT facilitating conditions ( B =0.17; P =.01) and behavioral intention ( B =0.17; P =.04), independent of depressive and anxiety symptoms. Conclusions: Psychological well-being is associated with determinants of SR acceptability in patients with HF, while psychological distress and personality traits are not associated with these determinants. These patient-level factors ought to be examined more closely before SR implementation.

Background: Prognostic models for cardiovascular disease (CVD) risk have commonly included predictors such as cholesterol levels. Mental disorders are robust predictors of CVD and associated mortality, leading to approximately 2‐fold increases in risk. This systematic review aimed to narratively summarize the key characteristics, strengths, and limitations of all CVD prediction models that consider mental disorders. Methods: A literature search with medical subject headings/key terms related to CVD, mental disorders and prognostic modeling was conducted in Medline and EMBASE. Included studies were: cohort studies of CVD prediction model development, validation, or recalibration that included mental disorders as prognostic factors/covariate(s), or the population of interest. All studies were screened by 2 independent reviewers, followed by data extraction. The Prediction Model Risk Of Bias Assessment Tool was used to critically appraise bias. A narrative synthesis was used to summarize mental disorder and sociodemographic factor/intersectionality inclusion. Results: There were 31 unique models identified (n=35 records including external validations). Considering these, 77% included mental disorders as a covariate, whereby depression and/or anxiety were the most considered (71%, n=22 studies). Most models were published within the last 5 years, included measures of socioeconomic status; however, many models lacked intersectionality considerations. Only one study was identified with a low risk of bias, while the majority had analytic concerns. Conclusions: Depression and/or anxiety were the most commonly considered mental disorders in modeling, despite larger associations with CVD for other disorders. Further CVD prediction modeling should consider a broader array of mental disorders, and limit methodological biases.

The use of psychedelics has increased in Canada in recent years. Although non-medical psilocybin use is prohibited under the Controlled Drugs and Substance