Coronary artery bypass grafting (CABG) remains one of the most commonly performed cardiac surgeries worldwide. Despite surgical advancements, a significant proportion of patients experience psychological distress following surgery, with depression being particularly common. Current evidence regarding the effectiveness of preoperative psychological interventions in improving postoperative mental health outcomes remains inconclusive. There is a critical need for predictive models that can identify patients at risk of developing clinically significant depressive symptoms (CSDSs) and related psychological conditions after CABG. This multicentre observational study aims to develop and validate prognostic models for predicting CSDSs and other psychological outcomes, including anxiety, post-traumatic stress symptoms and quality of life, 6 weeks after elective CABG surgery.

The study will recruit 300 adult patients undergoing elective CABG (with or without valve intervention) across two Swiss hospitals. Data collected will include demographic, clinical, psychometric, inflammation-related and interoceptive variables. A training set (n=200) will be used to develop predictive models using machine learning, while a held-out test set (n=100) will be used for model validation. The primary outcome prediction will focus on CSDSs, assessed using the Patient Health Questionnaire-9 (PHQ-9), with analyses conducted both categorically (PHQ-9 total score ≥10) and continuously as complementary approaches. Secondary models will address anxiety, using the General Anxiety Disorder Scale-7, post-traumatic stress, using the post-traumatic stress disorder checklist for Diagnostic and Statistical Manual of Mental Disorders-5 and health-related quality of life, using the 12-item Short Form Survey. A simplified ‘light solution’ model with fewer predictors will also be developed for broader applicability. This study will address an important gap in perioperative mental healthcare by identifying key predictors of psychological morbidity following CABG, particularly CSDSs. The resulting models may inform future screening and preventive strategies and improve postsurgical outcomes through early identification and intervention in high-risk individuals.

The responsible ethics committee has reviewed and approved this project (Kantonale Ethikkommission Zürich, BASEC number: 2023-02040). The study minimises participant burden by integrating brief validated instruments and limiting psychiatric interviews to relevant outcomes, while ensuring ethical safeguards and respect for participant rights (including written consent). Results will be shared through peer-reviewed publications, conference presentations and stakeholder meetings involving clinicians and mental health professionals. Findings will also be communicated to participating centres and patient communities in accessible formats.

To determine prognostic factors of disability in multiple sclerosis (MS), that is, (1) identify determinants of the dynamics of disability progression; (2) study the effectiveness of disease-modifying treatments (DMTs); (3) merge determinants and DMTs for creating patient-centred prognostic tools and (4) conduct an economic analysis.

Individuals registered in the French Observatoire Francais de la Sclérose en Plaques (OFSEP) database were included in this OFSEP-high definition cohort if they had a diagnosis of MS, were ≥15 years old and had an Expanded Disability Status Scale (EDSS) score

A cohort of 2842 individuals, 73.4% women, mean (SD) age of 42.7 (11.6) years, median disease duration of 8.8 years, has been recruited from July 2018 to September 2020. The course of MS was relapsing remitting in 67.7%, secondary progressive in 11.9%. The mean annual relapse rate was 0.98. The disease-modifying treatment received was highly effective therapy in 50.3% and moderately effective therapy in 30.7%.

The participants will be followed until December 2026. Disease course up to four landmarks will be examined as predictors of disease progression: (1) diagnosis of MS; (2) relapse activity worsening and independent progression; (3) any recent disease activity and (4) any visit with absence of disease activity in the past 5 years. The marginal effectiveness and tolerability of treatments will be assessed. Stratified algorithms will be proposed for medical decision-making. Economic evaluation of disease cost and cost-effectiveness of new DMTs will be conducted from a public payer perspective.

NCT03603457.